The brain is one of the most complex organ in the human body that works with billions of cells. A cerebral tumor occurs when there is an uncontrolled division of cells that form an abnormal group of cells around or within the brain. This cell group can affect the normal functioning of brain activity and can destroy healthy cells. Brain tumors are classified as benign or low grade Grade 1 and 2 and malignant tumors or high grade Grade 3 and 4 . The proposed methodology aims to differentiate between normal brain and tumor brain Benign or Melign . The proposed method in this paper is automated framework for differentiate between normal brain and tumor brain. Then our method is used to predict the diseases accurately. Then these methods are used to predict the disease is affected or not by using a comparison method. These methodology are validated by a comprehensive set of comparison against competing and well established image registration methods, by using real medical data sets and classic measures typically employed as a benchmark by the medical imaging community our proposed method is mostly used in medical field. It is used to easily detect the diseases. We demonstrate the accuracy and effectiveness of the preset framework throughout a comprehensive set of qualitative comparisons against several influential state of the art methods on various brain image databases. Sanmathi. R | Sujitha. K | Susmitha. G | Gnanasekaran. S ""Tumor Detection and Classification of MRI Brain Images using SVM and DNN"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30192.pdf
Paper Url : https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30192/tumor-detection-and-classification-of-mri-brain-images-using-svm-and-dnn/sanmathi-r
Brain Tumor is basically the unusual growth of some new cells found in the brain. This can happen in any area of the brain. Tumor are categorized by finding the origin of the cell which has tumor and if the cells are cancerous or not. Segmentation process is carried out to find if brain tumor exists or not, then the response of the patient to the tests performed is collected, different therapy sessions and also by creating models which has tumor growth in it. This one is different from the other types of tumor. Anyone can suffer from this disease. Primary tumors are basically Benign or Malignant. Here, we propose CNN Convolutional Neural Network based approach for improving accuracy. It also have capacity to detect certain features without any interaction from human beings. With the help of this model it classifies whether the MRI brain scan has tumor or not. There are other different algorithms, but this paper shows that CNN gives more accuracy than the rest. This model gives validation accuracy between 77 85 . gives more precise and accurate results. CNN also let us to train large data sets and cross validate results, hence the most easy and reliable model to use. Anagha Jayakumar | Mehtab Mehdi "Brain Tumor Detection using Neural Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38105.pdf Paper URL : https://www.ijtsrd.com/computer-science/other/38105/brain-tumor-detection-using-neural-network/anagha-jayakumar
Today, computer aided system is widely used in various fields. Among them, the brain tumor detection is an important task in medical image processing. Early diagnosis of brain tumors plays an important role in improving treatment possibilities and increases the survival rate of the patients. Manual segmentation of brain tumors for cancer diagnosis, from large amount of Magnetic Resonance Imaging MRI images generated in clinical routine, is a difficult and time consuming task or even generates errors. So, the automatic brain tumor segmentation is needed to segment tumor. The purpose of the thesis is to detect the brain tumor quickly and accurately from the MRI brain image. In the system, the average filter is used to remove noise and make smooth an input MRI image and threshold segmentation is applied to segment tumor region from MRI brain images. Region properties method is used to detect the tumor region exactly. And then, the equation of the tumor region in the system is effectively applied in any shape of the tumor region. Moe Moe Aye | Kyaw Kyaw Lin "Brain Tumor Detection System for MRI Image" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27864.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/27864/brain-tumor-detection-system-for-mri-image/moe-moe-aye
3D Segmentation of Brain Tumor ImagingIJAEMSJORNAL
A brain tumor is a collection of anomalous cells that grow in or around the brain. Brain tumors affect the humans badly, it can disrupt proper brain function and be life-threatening. In this project, we have proposed a system to detect, segment, and classify the tumors present in the brain. Once the brain tumor is identified at the very beginning, proper treatments can be done and it may be cured.
An evaluation of automated tumor detection techniques of brain magnetic reson...Salam Shah
Image processing is a technique developed by computer and Information technology scientist and being used in all field of research including medical sciences. The focus of this paper is the use of image processing in tumor detection from the brain Magnetic Resonance Imaging (MRI). For the brain tumor detection, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are the prominent imaging techniques, but most of the experts prefer MRI over CT. The traditional method of tumor detection in MRI images is a manual inspection which provides variations in the results when analyzed by different experts, therefore, in view of the limitations of the manual analysis of MRI, there is a need for an automated system that can produce globally acceptable and accurate results. There is enough amount of published literature available to replace the manual inspection process of MRI images with the digital computer system using image processing techniques. In this paper, we have provided a review of digital image processing techniques in the context of brain MRI processing and critically analyzed them for the identification of the gaps and limitations of the techniques so that the gaps can be filled and limitations of various techniques can be improved for precise and better results.
Brain Tumor is basically the unusual growth of some new cells found in the brain. This can happen in any area of the brain. Tumor are categorized by finding the origin of the cell which has tumor and if the cells are cancerous or not. Segmentation process is carried out to find if brain tumor exists or not, then the response of the patient to the tests performed is collected, different therapy sessions and also by creating models which has tumor growth in it. This one is different from the other types of tumor. Anyone can suffer from this disease. Primary tumors are basically Benign or Malignant. Here, we propose CNN Convolutional Neural Network based approach for improving accuracy. It also have capacity to detect certain features without any interaction from human beings. With the help of this model it classifies whether the MRI brain scan has tumor or not. There are other different algorithms, but this paper shows that CNN gives more accuracy than the rest. This model gives validation accuracy between 77 85 . gives more precise and accurate results. CNN also let us to train large data sets and cross validate results, hence the most easy and reliable model to use. Anagha Jayakumar | Mehtab Mehdi "Brain Tumor Detection using Neural Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38105.pdf Paper URL : https://www.ijtsrd.com/computer-science/other/38105/brain-tumor-detection-using-neural-network/anagha-jayakumar
Today, computer aided system is widely used in various fields. Among them, the brain tumor detection is an important task in medical image processing. Early diagnosis of brain tumors plays an important role in improving treatment possibilities and increases the survival rate of the patients. Manual segmentation of brain tumors for cancer diagnosis, from large amount of Magnetic Resonance Imaging MRI images generated in clinical routine, is a difficult and time consuming task or even generates errors. So, the automatic brain tumor segmentation is needed to segment tumor. The purpose of the thesis is to detect the brain tumor quickly and accurately from the MRI brain image. In the system, the average filter is used to remove noise and make smooth an input MRI image and threshold segmentation is applied to segment tumor region from MRI brain images. Region properties method is used to detect the tumor region exactly. And then, the equation of the tumor region in the system is effectively applied in any shape of the tumor region. Moe Moe Aye | Kyaw Kyaw Lin "Brain Tumor Detection System for MRI Image" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27864.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/27864/brain-tumor-detection-system-for-mri-image/moe-moe-aye
3D Segmentation of Brain Tumor ImagingIJAEMSJORNAL
A brain tumor is a collection of anomalous cells that grow in or around the brain. Brain tumors affect the humans badly, it can disrupt proper brain function and be life-threatening. In this project, we have proposed a system to detect, segment, and classify the tumors present in the brain. Once the brain tumor is identified at the very beginning, proper treatments can be done and it may be cured.
An evaluation of automated tumor detection techniques of brain magnetic reson...Salam Shah
Image processing is a technique developed by computer and Information technology scientist and being used in all field of research including medical sciences. The focus of this paper is the use of image processing in tumor detection from the brain Magnetic Resonance Imaging (MRI). For the brain tumor detection, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are the prominent imaging techniques, but most of the experts prefer MRI over CT. The traditional method of tumor detection in MRI images is a manual inspection which provides variations in the results when analyzed by different experts, therefore, in view of the limitations of the manual analysis of MRI, there is a need for an automated system that can produce globally acceptable and accurate results. There is enough amount of published literature available to replace the manual inspection process of MRI images with the digital computer system using image processing techniques. In this paper, we have provided a review of digital image processing techniques in the context of brain MRI processing and critically analyzed them for the identification of the gaps and limitations of the techniques so that the gaps can be filled and limitations of various techniques can be improved for precise and better results.
MRI Image Segmentation Using Gradient Based Watershed Transform In Level Set ...IJERA Editor
Brain image classification is one of the utmost imperative parts of clinical investigative tools. Brain images
typically comprise noise, inhomogeneity and sometimes deviation. Therefore, precise segmentation of brain
images is a very challenging task. Nevertheless, the process of perfect segmentation of these images is very
important and crucial for a spot-on diagnosis by clinical tools. Also, intensity inhomogeneity often arises in realworld
images, which presents a substantial challenge in image segmentation. The most extensively used image
segmentation algorithms are region-based and usually rely on the homogeneousness of the image intensities in
the sections of interest, which often fail to afford precise segmentation results due to the intensity
inhomogeneity. This Research presents a more accurate segmentation using Gradient Based watershed
transform in level set method for a medical diagnosis system. Experimental results proved that our method
validating a much better rate of segmentation accuracy as compare to the traditional approaches, results are also
validated in terms of certain Measure properties of image regions like eccentricity, perimeter etc.
A Review on Brain Disorder Segmentation in MR ImagesIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Brain Image Fusion using DWT and Laplacian Pyramid Approach and Tumor Detecti...INFOGAIN PUBLICATION
Image fusion is the process of combining important information from two or more images into a single image. The resulting image will be more enhanced than any of the input pictures. The idea of combining multiple image modalities to furnish a single, more enhanced image is well established, special fusion methods have been proposed in literature. This paper is based on image fusion using laplacian pyramid and Discreet Wavelet Transform (DWT) methods. This system uses an easy and effective algorithm for multi-focus image fusion which uses fusion rules to create fused image. Subsequently, the fused image is obtained by applying inverse discreet wavelet transform. After fused image is obtained, watershed segmentation algorithm is applied to detect the tumor part in fused image.
DETECTING BRAIN TUMOUR FROM MRI IMAGE USING MATLAB GUI PROGRAMMEIJCSES Journal
Engineers have been actively developing tools to detect tumors and to process medical images. Medical image segmentation is a powerful tool that is often used to detect tumors. Many scientists and researchers are working to develop and add more features to this tool. This project is about detecting Brain tumors from MRI images using an interface of GUI in Matlab. Using the GUI, this program can use various combinations of segmentation, filters, and other image processing algorithms to achieve the best results.
We start with filtering the image using Prewitt horizontal edge-emphasizing filter. The next step for detecting tumor is "watershed pixels." The most important part of this project is that all the Matlab programs work with GUI “Matlab guide”. This allows us to use various combinations of filters, and other
image processing techniques to arrive at the best result that can help us detect brain tumors in their early stages.
Performance analysis of automated brain tumor detection from MR imaging and CT scan using basic image processing techniques based on various hard and soft computing has been performed in our work. Moreover, we applied six traditional classifiers to detect brain tumor in the images. Then we applied CNN for brain tumor detection to include deep learning method in our work. We compared the result of the traditional one having the best accuracy (SVM) with the result of CNN. Furthermore, our work presents a generic method of tumor detection and extraction of its various features.
Integrated Modelling Approach for Enhancing Brain MRI with Flexible Pre-Proce...IJECEIAES
The assurance of an information quality of the input medical image is a critical step to offer highly precise and reliable diagnosis of clinical condition in human. The importance of such assurance becomes more while dealing with important organ like brain. Magnetic Resonance Imaging (MRI) is one of the most trusted mediums to investigate brain. Looking into the existing trends of investigating brain MRI, it was observed that researchers are more prone to investigate advanced problems e.g. segmentation, localization, classification, etc considering image dataset. There is less work carried out towards image preprocessing that potential affects the later stage of diagnosing. Therefore, this paper introduces a novel model of integrated image enhancement algorithm that is capable of solving different and discrete problems of performing image pre-processing for offering highly improved and enhanced brain MRI. The comparative outcomes exhibit the advantage of its simplistic implemetation strategy.
Image Segmentation and Identification of Brain Tumor using FFT Techniques of ...IDES Editor
The image processing tools are extensively used on
the development of new algorithms and mathematical tools
for the advanced processing of medical and biological images.
Given an MRI scan, first segment the tumor region in the
MRI brain image and study the pixel intensity values. A
detailed procedure using Matlab script is written to extract
tumor region in CT scan Brain Image and MRI Scan Brain
Image. MRI Scan has higher resolution and easier
identification compare to CT scan Brain image. Fast Fourier
Transform is used here to study the tumor region of MRI
Brain Image in terms of its pixel intensity. Types of FFT like
Zero padded FFT, Windowed FFT are used to study the signal
converted from the MRI Brain Image. It is found that lesser
spectral leakage for Zero Padded Windowed FFT than other
Types of FFT and hence the tumor cell identification is easier
than other methods. Finally higher pixel intensity values of
the cells gives identification of presence and activeness of
tumor cells.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Brain Tumor Detection using MRI ImagesYogeshIJTSRD
Brain tumor segmentation is a very important task in medical image processing. Early diagnosis of brain tumors plays a crucial role in improving treatment possibilities and increases the survival rate of the patients. For the study of tumor detection and segmentation, MRI Images are very useful in recent years. One of the foremost crucial tasks in any brain tumor detection system is that the detachment of abnormal tissues from normal brain tissues. Because of MRI Images, we will detect the brain tumor. Detection of unusual growth of tissues and blocks of blood within the system is seen in an MRI Imaging. Brain tumor detection using MRI images may be a challenging task due to the brains complex structure.In this paper, we propose an image segmentation method to detect tumors from MRI images using an interface of GUI in MATLAB. The method of distinguishing brain tumors through MRI images is often sorted into four sections of image processing as pre processing, feature extraction, image segmentation, and image classification. During this paper, weve used various algorithms for the partial fulfillment of the necessities to hit the simplest results that may help us to detect brain tumors within the early stage. Deepa Dangwal | Aditya Nautiyal | Dakshita Adhikari | Kapil Joshi "Brain Tumor Detection using MRI Images" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Advances in Engineering, Science and Technology - 2021 , May 2021, URL: https://www.ijtsrd.com/papers/ijtsrd42456.pdf Paper URL : https://www.ijtsrd.com/engineering/computer-engineering/42456/brain-tumor-detection-using-mri-images/deepa-dangwal
A novel framework for efficient identification of brain cancer region from br...IJECEIAES
Diagnosis of brain cancer using existing imaging techniques, e.g., Magnetic Resonance Imaging (MRI) is shrouded with various degrees of challenges. At present, there are very few significant research models focusing on introducing some novel and unique solutions towards such problems of detection. Moreover, existing techniques are found to have lesser accuracy as compared to other detection schemes. Therefore, the proposed paper presents a framework that introduces a series of simple and computationally cost-effective techniques that have assisted in leveraging the accuracy level to a very higher degree. The proposed framework takes the input image and subjects it to non-conventional segmentation mechanism followed by optimizing the performance using directed acyclic graph, Bayesian Network, and neural network. The study outcome of the proposed system shows the significantly higher degree of accuracy in detection performance as compared to frequently existing approaches.
This paper primarily focuses on to employ a novel approach to classify the brain tumor and its area. The Tumor is an uncontrolled enlargement of tissues in any portion of the human body. Tumors are of several types and have some different characteristics. According to their characteristics some of them are avoidable and some are unavoidable. Brain tumor is serious and life threatening issues now days, because of today’s hectic lifestyle. Medical imaging play important role to diagnose brain tumor .In this study an automated system has been proposed to detect and calculate the area of tumor. For proposed system the experiment carried out with 150 T1 weighted MRI images. The edge based segmentation, watershed segmentation has applied for tumor, and watershed segmentation has used to extract abnormal cells from the normal cells to get the tumor identification of involved and noninvolved areas so that the radiologist differentiate the affected area. The experiment result shows tumor extraction and area of tumor find the weather it is benign and malignant.
Glioblastomas brain tumour segmentation based on convolutional neural network...IJECEIAES
Brain tumour segmentation can improve diagnostics efficiency, rise the prediction rate and treatment planning. This will help the doctors and experts in their work. Where many types of brain tumour may be classified easily, the gliomas tumour is challenging to be segmented because of the diffusion between the tumour and the surrounding edema. Another important challenge with this type of brain tumour is that the tumour may grow anywhere in the brain with different shape and size. Brain cancer presents one of the most famous diseases over the world, which encourage the researchers to find a high-throughput system for tumour detection and classification. Several approaches have been proposed to design automatic detection and classification systems. This paper presents an integrated framework to segment the gliomas brain tumour automatically using pixel clustering for the MRI images foreground and background and classify its type based on deep learning mechanism, which is the convolutional neural network. In this work, a novel segmentation and classification system is proposed to detect the tumour cells and classify the brain image if it is healthy or not. After collecting data for healthy and non-healthy brain images, satisfactory results are found and registered using computer vision approaches. This approach can be used as a part of a bigger diagnosis system for breast tumour detection and manipulation.
MRI Image Segmentation by Using DWT for Detection of Brain Tumorijtsrd
Brain tumor segmentation is one of the critical tasks in the medical image processing. Some early diagnosis of brain tumor helps in improving the treatment and also increases the survival rate of the patients. The manual segmentation for cancer diagnosis of brain tumor and generation of MRI images in clinical routine is difficult and time consuming. The aim of this research paper is to review of MRI based brain tumor segmentation methods for the treatment of cancer like diseases. The magnetic resonance imaging used for detection of tumor and diagnosis of tissue abnormalities. The computerized medical image segmentation helps the doctors in treatment in a simple way with fast decision making. The brain tumor segmentation assessed by computer based surgery, tumor growth, developing tumor growth models and treatment responses. This research focuses on the causes of brain tumor, brain tumor segmentation and its classification, MRI scanning process and different segmentation methodologies. Ishu Rana | Gargi Kalia | Preeti Sondhi ""MRI Image Segmentation by Using DWT for Detection of Brain Tumor"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25116.pdf
Paper URL: https://www.ijtsrd.com/computer-science/bioinformatics/25116/mri-image-segmentation-by-using-dwt-for-detection-of-brain-tumor/ishu-rana
MRI Image Segmentation Using Gradient Based Watershed Transform In Level Set ...IJERA Editor
Brain image classification is one of the utmost imperative parts of clinical investigative tools. Brain images
typically comprise noise, inhomogeneity and sometimes deviation. Therefore, precise segmentation of brain
images is a very challenging task. Nevertheless, the process of perfect segmentation of these images is very
important and crucial for a spot-on diagnosis by clinical tools. Also, intensity inhomogeneity often arises in realworld
images, which presents a substantial challenge in image segmentation. The most extensively used image
segmentation algorithms are region-based and usually rely on the homogeneousness of the image intensities in
the sections of interest, which often fail to afford precise segmentation results due to the intensity
inhomogeneity. This Research presents a more accurate segmentation using Gradient Based watershed
transform in level set method for a medical diagnosis system. Experimental results proved that our method
validating a much better rate of segmentation accuracy as compare to the traditional approaches, results are also
validated in terms of certain Measure properties of image regions like eccentricity, perimeter etc.
A Review on Brain Disorder Segmentation in MR ImagesIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Brain Image Fusion using DWT and Laplacian Pyramid Approach and Tumor Detecti...INFOGAIN PUBLICATION
Image fusion is the process of combining important information from two or more images into a single image. The resulting image will be more enhanced than any of the input pictures. The idea of combining multiple image modalities to furnish a single, more enhanced image is well established, special fusion methods have been proposed in literature. This paper is based on image fusion using laplacian pyramid and Discreet Wavelet Transform (DWT) methods. This system uses an easy and effective algorithm for multi-focus image fusion which uses fusion rules to create fused image. Subsequently, the fused image is obtained by applying inverse discreet wavelet transform. After fused image is obtained, watershed segmentation algorithm is applied to detect the tumor part in fused image.
DETECTING BRAIN TUMOUR FROM MRI IMAGE USING MATLAB GUI PROGRAMMEIJCSES Journal
Engineers have been actively developing tools to detect tumors and to process medical images. Medical image segmentation is a powerful tool that is often used to detect tumors. Many scientists and researchers are working to develop and add more features to this tool. This project is about detecting Brain tumors from MRI images using an interface of GUI in Matlab. Using the GUI, this program can use various combinations of segmentation, filters, and other image processing algorithms to achieve the best results.
We start with filtering the image using Prewitt horizontal edge-emphasizing filter. The next step for detecting tumor is "watershed pixels." The most important part of this project is that all the Matlab programs work with GUI “Matlab guide”. This allows us to use various combinations of filters, and other
image processing techniques to arrive at the best result that can help us detect brain tumors in their early stages.
Performance analysis of automated brain tumor detection from MR imaging and CT scan using basic image processing techniques based on various hard and soft computing has been performed in our work. Moreover, we applied six traditional classifiers to detect brain tumor in the images. Then we applied CNN for brain tumor detection to include deep learning method in our work. We compared the result of the traditional one having the best accuracy (SVM) with the result of CNN. Furthermore, our work presents a generic method of tumor detection and extraction of its various features.
Integrated Modelling Approach for Enhancing Brain MRI with Flexible Pre-Proce...IJECEIAES
The assurance of an information quality of the input medical image is a critical step to offer highly precise and reliable diagnosis of clinical condition in human. The importance of such assurance becomes more while dealing with important organ like brain. Magnetic Resonance Imaging (MRI) is one of the most trusted mediums to investigate brain. Looking into the existing trends of investigating brain MRI, it was observed that researchers are more prone to investigate advanced problems e.g. segmentation, localization, classification, etc considering image dataset. There is less work carried out towards image preprocessing that potential affects the later stage of diagnosing. Therefore, this paper introduces a novel model of integrated image enhancement algorithm that is capable of solving different and discrete problems of performing image pre-processing for offering highly improved and enhanced brain MRI. The comparative outcomes exhibit the advantage of its simplistic implemetation strategy.
Image Segmentation and Identification of Brain Tumor using FFT Techniques of ...IDES Editor
The image processing tools are extensively used on
the development of new algorithms and mathematical tools
for the advanced processing of medical and biological images.
Given an MRI scan, first segment the tumor region in the
MRI brain image and study the pixel intensity values. A
detailed procedure using Matlab script is written to extract
tumor region in CT scan Brain Image and MRI Scan Brain
Image. MRI Scan has higher resolution and easier
identification compare to CT scan Brain image. Fast Fourier
Transform is used here to study the tumor region of MRI
Brain Image in terms of its pixel intensity. Types of FFT like
Zero padded FFT, Windowed FFT are used to study the signal
converted from the MRI Brain Image. It is found that lesser
spectral leakage for Zero Padded Windowed FFT than other
Types of FFT and hence the tumor cell identification is easier
than other methods. Finally higher pixel intensity values of
the cells gives identification of presence and activeness of
tumor cells.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Brain Tumor Detection using MRI ImagesYogeshIJTSRD
Brain tumor segmentation is a very important task in medical image processing. Early diagnosis of brain tumors plays a crucial role in improving treatment possibilities and increases the survival rate of the patients. For the study of tumor detection and segmentation, MRI Images are very useful in recent years. One of the foremost crucial tasks in any brain tumor detection system is that the detachment of abnormal tissues from normal brain tissues. Because of MRI Images, we will detect the brain tumor. Detection of unusual growth of tissues and blocks of blood within the system is seen in an MRI Imaging. Brain tumor detection using MRI images may be a challenging task due to the brains complex structure.In this paper, we propose an image segmentation method to detect tumors from MRI images using an interface of GUI in MATLAB. The method of distinguishing brain tumors through MRI images is often sorted into four sections of image processing as pre processing, feature extraction, image segmentation, and image classification. During this paper, weve used various algorithms for the partial fulfillment of the necessities to hit the simplest results that may help us to detect brain tumors within the early stage. Deepa Dangwal | Aditya Nautiyal | Dakshita Adhikari | Kapil Joshi "Brain Tumor Detection using MRI Images" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Advances in Engineering, Science and Technology - 2021 , May 2021, URL: https://www.ijtsrd.com/papers/ijtsrd42456.pdf Paper URL : https://www.ijtsrd.com/engineering/computer-engineering/42456/brain-tumor-detection-using-mri-images/deepa-dangwal
A novel framework for efficient identification of brain cancer region from br...IJECEIAES
Diagnosis of brain cancer using existing imaging techniques, e.g., Magnetic Resonance Imaging (MRI) is shrouded with various degrees of challenges. At present, there are very few significant research models focusing on introducing some novel and unique solutions towards such problems of detection. Moreover, existing techniques are found to have lesser accuracy as compared to other detection schemes. Therefore, the proposed paper presents a framework that introduces a series of simple and computationally cost-effective techniques that have assisted in leveraging the accuracy level to a very higher degree. The proposed framework takes the input image and subjects it to non-conventional segmentation mechanism followed by optimizing the performance using directed acyclic graph, Bayesian Network, and neural network. The study outcome of the proposed system shows the significantly higher degree of accuracy in detection performance as compared to frequently existing approaches.
This paper primarily focuses on to employ a novel approach to classify the brain tumor and its area. The Tumor is an uncontrolled enlargement of tissues in any portion of the human body. Tumors are of several types and have some different characteristics. According to their characteristics some of them are avoidable and some are unavoidable. Brain tumor is serious and life threatening issues now days, because of today’s hectic lifestyle. Medical imaging play important role to diagnose brain tumor .In this study an automated system has been proposed to detect and calculate the area of tumor. For proposed system the experiment carried out with 150 T1 weighted MRI images. The edge based segmentation, watershed segmentation has applied for tumor, and watershed segmentation has used to extract abnormal cells from the normal cells to get the tumor identification of involved and noninvolved areas so that the radiologist differentiate the affected area. The experiment result shows tumor extraction and area of tumor find the weather it is benign and malignant.
Glioblastomas brain tumour segmentation based on convolutional neural network...IJECEIAES
Brain tumour segmentation can improve diagnostics efficiency, rise the prediction rate and treatment planning. This will help the doctors and experts in their work. Where many types of brain tumour may be classified easily, the gliomas tumour is challenging to be segmented because of the diffusion between the tumour and the surrounding edema. Another important challenge with this type of brain tumour is that the tumour may grow anywhere in the brain with different shape and size. Brain cancer presents one of the most famous diseases over the world, which encourage the researchers to find a high-throughput system for tumour detection and classification. Several approaches have been proposed to design automatic detection and classification systems. This paper presents an integrated framework to segment the gliomas brain tumour automatically using pixel clustering for the MRI images foreground and background and classify its type based on deep learning mechanism, which is the convolutional neural network. In this work, a novel segmentation and classification system is proposed to detect the tumour cells and classify the brain image if it is healthy or not. After collecting data for healthy and non-healthy brain images, satisfactory results are found and registered using computer vision approaches. This approach can be used as a part of a bigger diagnosis system for breast tumour detection and manipulation.
MRI Image Segmentation by Using DWT for Detection of Brain Tumorijtsrd
Brain tumor segmentation is one of the critical tasks in the medical image processing. Some early diagnosis of brain tumor helps in improving the treatment and also increases the survival rate of the patients. The manual segmentation for cancer diagnosis of brain tumor and generation of MRI images in clinical routine is difficult and time consuming. The aim of this research paper is to review of MRI based brain tumor segmentation methods for the treatment of cancer like diseases. The magnetic resonance imaging used for detection of tumor and diagnosis of tissue abnormalities. The computerized medical image segmentation helps the doctors in treatment in a simple way with fast decision making. The brain tumor segmentation assessed by computer based surgery, tumor growth, developing tumor growth models and treatment responses. This research focuses on the causes of brain tumor, brain tumor segmentation and its classification, MRI scanning process and different segmentation methodologies. Ishu Rana | Gargi Kalia | Preeti Sondhi ""MRI Image Segmentation by Using DWT for Detection of Brain Tumor"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25116.pdf
Paper URL: https://www.ijtsrd.com/computer-science/bioinformatics/25116/mri-image-segmentation-by-using-dwt-for-detection-of-brain-tumor/ishu-rana
Enhanced 3D Brain Tumor Segmentation Using Assorted Precision TrainingBIJIAM Journal
A brain tumor is a medical disorder faced by individuals of all demographics. Medically, it is described as the spread of nonessential cells close to or throughout the brain. Symptoms of this ailment include headaches, seizures, and sensory changes. This research explores two main categories of brain tumors: benign and malignant. Benign spreads steadily, and malignant express growth makes it dangerous. Early identification of brain tumors is a crucial factor for the survival of patients. This research provides a state-of-the-art approach to the early identification of tumors within the brain. We implemented the SegResNet architecture, a widely adopted architecture for threedimensional segmentation, and trained it using the automatic multi-precision method. We incorporated the dice loss function and dice metric for evaluating the model. We got a dice score of 0.84. For the tumor core, we got a dice score of 0.84; for the whole tumor, 0.90; and for the enhanced tumor, we got a score of 0.79.
A review on detecting brain tumors using deep learning and magnetic resonanc...IJECEIAES
Early detection and treatment in the medical field offer a critical opportunity to survive people. However, the brain has a significant role in human life as it handles most human body activities. Accurate diagnosis of brain tumors dramatically helps speed up the patient's recovery and the cost of treatment. Magnetic resonance imaging (MRI) is a commonly used technique due to the massive progress of artificial intelligence in medicine, machine learning, and recently, deep learning has shown significant results in detecting brain tumors. This review paper is a comprehensive article suitable as a starting point for researchers to demonstrate essential aspects of using deep learning in diagnosing brain tumors. More specifically, it has been restricted to only detecting brain tumors (binary classification as normal or tumor) using MRI datasets in 2020 and 2021. In addition, the paper presents the frequently used datasets, convolutional neural network architectures (standard and designed), and transfer learning techniques. The crucial limitations of applying the deep learning approach, including a lack of datasets, overfitting, and vanishing gradient problems, are also discussed. Finally, alternative solutions for these limitations are obtained.
A Survey on Segmentation Techniques Used For Brain Tumor DetectionEditor IJMTER
In recent years Brain tumor is one of the most commonly found causes for death among
children and adults. Early detection of tumor is a must in order to reduce the death rate. For tumor
detection various image techniques can be used. In this paper we mainly concentrate on the images
obtained from MRI scans. In MRI images, the tumor may appear clearly, but for further treatment
the physician need to be a qualified and well experienced person. In order to help the radiologist in
detection computer-aided diagnosis was developed. The generation of a CAD system consists of
several processes and among them segmentation is considered to the most important process. Image
Segmentation is a process of partitioning an image into multiple segments. The main objective of
segmentation is to represent the image into a simplified form so as to increase the efficiency and
accuracy of the system. Therefore the segmentation of brain tumor can be considered as an important
role in the medical image process. Hence in this paper we concentrate on the recently used
segmentation techniques for the detection of tumor using MRI images.
Efficient Brain Tumor Detection Using Wavelet TransformIJERA Editor
Brain tumor detection is a challenging task and its very important to analyze the structure of the tumor correctly so a automatic method is used now a days for the detection of the tumor. This method saves time as well as it reduces the error which occurs in the method of manual detection. In this paper the tumor is detected using wavelet transform. MRI is an important tool used in many fields of medicine and is capable of generating a detailed image of any part of the human body. The tumor is segmented from the MRI images, features are extracted and then the area of the tumor is determined. PNN can successfully handle the process of brain tumor classification
Description of Different Phases of Brain Tumor Classificationasclepiuspdfs
The proposed approach makes contributions in various stages in the development of a computer-aided diagnosis (CAD) system of brain diseases, namely image preprocessing, intermediate processing, detection, segmentation, feature extraction, and classification. Literature study incorporates many important ideas for abnormalities detection and analysis with their advantages and disadvantages. Literature studies have pointed out the needs of dividing task and appropriate ways for accurate abnormality characterization to provide a proper clinical diagnosis.
Automatic brain tumor detection using adaptive region growing with thresholdi...IAESIJAI
Brain cancer affects many people around the world. It's not just limited to the elderly; it is also recognized in children. With the development of image processing, early detection of mental development is possible. Some designers suggest deformable models, histogram averaging, or manual division. Due to constant manual intervention, these cycles can be uncomfortable and tiring. This research introduces a high-level system for the removal of malignant tumors from attractive reverberation images, based on a programmed and rapid distribution strategy for surface extraction and recreation for clinicians. To test the proposed system, acquired tomography images from the Cancer Imaging Archive were used. The results of the study strongly demonstrate that the intended structure is viable in brain tumor detection.
‘Six Sigma Technique’ A Journey Through its Implementationijtsrd
The manufacturing industries all over the world are facing tough challenges for growth, development and sustainability in today’s competitive environment. They have to achieve apex position by adapting with the global competitive environment by delivering goods and services at low cost, prime quality and better price to increase wealth and consumer satisfaction. Cost Management ensures profit, growth and sustainability of the business with implementation of Continuous Improvement Technique like Six Sigma. This leads to optimize Business performance. The method drives for customer satisfaction, low variation, reduction in waste and cycle time resulting into a competitive advantage over other industries which did not implement it. The main objective of this paper ‘Six Sigma Technique A Journey Through Its Implementation’ is to conceptualize the effectiveness of Six Sigma Technique through the journey of its implementation. Aditi Sunilkumar Ghosalkar "‘Six Sigma Technique’: A Journey Through its Implementation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64546.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64546/‘six-sigma-technique’-a-journey-through-its-implementation/aditi-sunilkumar-ghosalkar
Edge Computing in Space Enhancing Data Processing and Communication for Space...ijtsrd
Edge computing, a paradigm that involves processing data closer to its source, has gained significant attention for its potential to revolutionize data processing and communication in space missions. With the increasing complexity and data volume generated by modern space missions, traditional centralized computing approaches face challenges related to latency, bandwidth, and security. Edge computing in space, involving on board processing and analysis of data, offers promising solutions to these challenges. This paper explores the concept of edge computing in space, its benefits, applications, and future prospects in enhancing space missions. Manish Verma "Edge Computing in Space: Enhancing Data Processing and Communication for Space Missions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64541.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/64541/edge-computing-in-space-enhancing-data-processing-and-communication-for-space-missions/manish-verma
Dynamics of Communal Politics in 21st Century India Challenges and Prospectsijtsrd
Communal politics in India has evolved through centuries, weaving a complex tapestry shaped by historical legacies, colonial influences, and contemporary socio political transformations. This research comprehensively examines the dynamics of communal politics in 21st century India, emphasizing its historical roots, socio political dynamics, economic implications, challenges, and prospects for mitigation. The historical perspective unravels the intricate interplay of religious identities and power dynamics from ancient civilizations to the impact of colonial rule, providing insights into the evolution of communalism. The socio political dynamics section delves into the contemporary manifestations, exploring the roles of identity politics, socio economic disparities, and globalization. The economic implications section highlights how communal politics intersects with economic issues, perpetuating disparities and influencing resource allocation. Challenges posed by communal politics are scrutinized, revealing multifaceted issues ranging from social fragmentation to threats against democratic values. The prospects for mitigation present a multifaceted approach, incorporating policy interventions, community engagement, and educational initiatives. The paper conducts a comparative analysis with international examples, identifying common patterns such as identity politics and economic disparities. It also examines unique challenges, emphasizing Indias diverse religious landscape, historical legacy, and secular framework. Lessons for effective strategies are drawn from international experiences, offering insights into inclusive policies, interfaith dialogue, media regulation, and global cooperation. By scrutinizing historical epochs, contemporary dynamics, economic implications, and international comparisons, this research provides a comprehensive understanding of communal politics in India. The proposed strategies for mitigation underscore the importance of a holistic approach to foster social harmony, inclusivity, and democratic values. Rose Hossain "Dynamics of Communal Politics in 21st Century India: Challenges and Prospects" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64528.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/history/64528/dynamics-of-communal-politics-in-21st-century-india-challenges-and-prospects/rose-hossain
Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in...ijtsrd
Background and Objective Telehealth has become a well known tool for the delivery of health care in Saudi Arabia, and the perspective and knowledge of healthcare providers are influential in the implementation, adoption and advancement of the method. This systematic review was conducted to examine the current literature base regarding telehealth and the related healthcare professional perspective and knowledge in the Kingdom of Saudi Arabia. Materials and Methods This systematic review was conducted by searching 7 databases including, MEDLINE, CINHAL, Web of Science, Scopus, PubMed, PsycINFO, and ProQuest Central. Studies on healthcare practitioners telehealth knowledge and perspectives published in English in Saudi Arabia from 2000 to 2023 were included. Boland directed this comprehensive review. The researchers examined each connected study using the AXIS tool, which evaluates cross sectional systematic reviews. Narrative synthesis was used to summarise and convey the data. Results Out of 1840 search results, 10 studies were included. Positive outlook and limited knowledge among providers were seen across trials. Healthcare professionals like telehealth for its ability to improve quality, access, and delivery, save time and money, and be successful. Age, gender, occupation, and work experience also affect health workers knowledge. In Saudi Arabia, healthcare professionals face inadequate expert assistance, patient privacy, internet connection concerns, lack of training courses, lack of telehealth understanding, and high costs while performing telemedicine. Conclusions Healthcare practitioners telehealth perceptions and knowledge were examined in this systematic study. Its collection of concerned experts different personal attitudes and expertise would help enhance telehealths implementation in Saudi Arabia, develop its healthcare delivery alternative, and eliminate frequent problems. Badriah Mousa I Mulayhi | Dr. Jomin George | Judy Jenkins "Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in Saudi Arabia: A Systematic Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64535.pdf Paper Url: https://www.ijtsrd.com/medicine/other/64535/assess-perspective-and-knowledge-of-healthcare-providers-towards-elehealth-in-saudi-arabia-a-systematic-review/badriah-mousa-i-mulayhi
The Impact of Digital Media on the Decentralization of Power and the Erosion ...ijtsrd
The impact of digital media on the distribution of power and the weakening of traditional gatekeepers has gained considerable attention in recent years. The adoption of digital technologies and the internet has resulted in declining influence and power for traditional gatekeepers such as publishing houses and news organizations. Simultaneously, digital media has facilitated the emergence of new voices and players in the media industry. Digital medias impact on power decentralization and gatekeeper erosion is visible in several ways. One significant aspect is the democratization of information, which enables anyone with an internet connection to publish and share content globally, leading to citizen journalism and bypassing traditional gatekeepers. Another aspect is the disruption of conventional media industry business models, as traditional organizations struggle to adjust to the decrease in advertising revenue and the rise of digital platforms. Alternative business models, such as subscription models and crowdfunding, have become more prevalent, leading to the emergence of new players. Overall, the impact of digital media on the distribution of power and the weakening of traditional gatekeepers has brought about significant changes in the media landscape and the way information is shared. Further research is required to fully comprehend the implications of these changes and their impact on society. Dr. Kusum Lata "The Impact of Digital Media on the Decentralization of Power and the Erosion of Traditional Gatekeepers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64544.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64544/the-impact-of-digital-media-on-the-decentralization-of-power-and-the-erosion-of-traditional-gatekeepers/dr-kusum-lata
Online Voices, Offline Impact Ambedkars Ideals and Socio Political Inclusion ...ijtsrd
This research investigates the nexus between online discussions on Dr. B.R. Ambedkars ideals and their impact on social inclusion among college students in Gurugram, Haryana. Surveying 240 students from 12 government colleges, findings indicate that 65 actively engage in online discussions, with 80 demonstrating moderate to high awareness of Ambedkars ideals. Statistically significant correlations reveal that higher online engagement correlates with increased awareness p 0.05 and perceived social inclusion. Variations across colleges and a notable effect of college type on perceived social inclusion highlight the influence of contextual factors. Furthermore, the intersectional analysis underscores nuanced differences based on gender, caste, and socio economic status. Dr. Kusum Lata "Online Voices, Offline Impact: Ambedkar's Ideals and Socio-Political Inclusion - A Study of Gurugram District" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64543.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64543/online-voices-offline-impact-ambedkars-ideals-and-sociopolitical-inclusion--a-study-of-gurugram-district/dr-kusum-lata
Problems and Challenges of Agro Entreprenurship A Studyijtsrd
Noting calls for contextualizing Agro entrepreneurs problems and challenges of the agro entrepreneurs and for greater attention to the Role of entrepreneurs in agro entrepreneurship research, we conduct a systematic literature review of extent research in agriculture entrepreneurship to overcome the study objectives of complications of agro entrepreneurs through various factors, Development of agriculture products is a key factor for the overall economic growth of agro entrepreneurs Agro Entrepreneurs produces firsthand large scale employment, utilizes the labor and natural resources, This research outlines the problems of Weather and Soil Erosions, Market price fluctuation, stimulates labor cost problems, reduces concentration of Price volatility, Dependency on Intermediaries, induces Limited Bargaining Power, and Storage and Transportation Costs. This paper mainly devoted to highlight Problems and challenges faced for the sustainable of Agro Entrepreneurs in India. Vinay Prasad B "Problems and Challenges of Agro Entreprenurship - A Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64540.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64540/problems-and-challenges-of-agro-entreprenurship--a-study/vinay-prasad-b
Comparative Analysis of Total Corporate Disclosure of Selected IT Companies o...ijtsrd
Disclosure is a process through which a business enterprise communicates with external parties. A corporate disclosure is communication of financial and non financial information of the activities of a business enterprise to the interested entities. Corporate disclosure is done through publishing annual reports. So corporate disclosure through annual reports plays a vital role in the life of all the companies and provides valuable information to investors. The basic objectives of corporate disclosure is to give a true and fair view of companies to the parties related either directly or indirectly like owner, government, creditors, shareholders etc. in the companies act, provisions have been made about mandatory and voluntary disclosure. The IT sector in India is rapidly growing, the trend to invest in the IT sector is rising and employment opportunities in IT sectors are also increasing. Therefore the IT sector is expected to have fair, full and adequate disclosure of all information. Unfair and incomplete disclosure may adversely affect the entire economy. A research study on disclosure practices of IT companies could play an important role in this regard. Hence, the present research study has been done to study and review comparative analysis of total corporate disclosure of selected IT companies of India and to put forward overall findings and suggestions with a view to increase disclosure score of these companies. The researcher hopes that the present research study will be helpful to all selected Companies for improving level of corporate disclosure through annual reports as well as the government, creditors, investors, all business organizations and upcoming researcher for comparative analyses of level of corporate disclosure with special reference to selected IT companies. Dr. Vaibhavi D. Thaker "Comparative Analysis of Total Corporate Disclosure of Selected IT Companies of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64539.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64539/comparative-analysis-of-total-corporate-disclosure-of-selected-it-companies-of-india/dr-vaibhavi-d-thaker
The Impact of Educational Background and Professional Training on Human Right...ijtsrd
This study investigated the impact of educational background and professional training on human rights awareness among secondary school teachers in the Marathwada region of Maharashtra, India. The key findings reveal that higher levels of education, particularly a master’s degree, and fields of study related to education, humanities, or social sciences are associated with greater human rights awareness among teachers. Additionally, both pre service teacher training and in service professional development programs focused on human rights education significantly enhance teacher’s knowledge, skills, and competencies in promoting human rights principles in their classrooms. Baig Ameer Bee Mirza Abdul Aziz | Dr. Syed Azaz Ali Amjad Ali "The Impact of Educational Background and Professional Training on Human Rights Awareness among Secondary School Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64529.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64529/the-impact-of-educational-background-and-professional-training-on-human-rights-awareness-among-secondary-school-teachers/baig-ameer-bee-mirza-abdul-aziz
A Study on the Effective Teaching Learning Process in English Curriculum at t...ijtsrd
“One Language sets you in a corridor for life. Two languages open every door along the way” Frank Smith English as a foreign language or as a second language has been ruling in India since the period of Lord Macaulay. But the question is how much we teach or learn English properly in our culture. Is there any scope to use English as a language rather than a subject How much we learn or teach English without any interference of mother language specially in the classroom teaching learning scenario in West Bengal By considering all these issues the researcher has attempted in this article to focus on the effective teaching learning process comparing to other traditional strategies in the field of English curriculum at the secondary level to investigate whether they fulfill the present teaching learning requirements or not by examining the validity of the present curriculum of English. The purpose of this study is to focus on the effectiveness of the systematic, scientific, sequential and logical transaction of the course between the teachers and the learners in the perspective of the 5Es programme that is engage, explore, explain, extend and evaluate. Sanchali Mondal | Santinath Sarkar "A Study on the Effective Teaching Learning Process in English Curriculum at the Secondary Level of West Bengal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd62412.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/62412/a-study-on-the-effective-teaching-learning-process-in-english-curriculum-at-the-secondary-level-of-west-bengal/sanchali-mondal
The Role of Mentoring and Its Influence on the Effectiveness of the Teaching ...ijtsrd
This paper reports on a study which was conducted to investigate the role of mentoring and its influence on the effectiveness of the teaching of Physics in secondary schools in the South West Region of Cameroon. The study adopted the convergent parallel mixed methods design, focusing on respondents in secondary schools in the South West Region of Cameroon. Both quantitative and qualitative data were collected, analysed separately, and the results were compared to see if the findings confirm or disconfirm each other. The quantitative analysis found that majority of the respondents 72 of Physics teachers affirmed that they had more experienced colleagues as mentors to help build their confidence, improve their teaching, and help them improve their effectiveness and efficiency in guiding learners’ achievements. Only 28 of the respondents disagreed with these statements. With majority respondents 72 agreeing with the statements, it implies that in most secondary schools, experienced Physics teachers act as mentors to build teachers’ confidence in teaching and improving students’ learning. The interview qualitative data analysis summarized how secondary school Principals use meetings with mentors and mentees to promote mentorship in the school milieu. This has helped strengthen teachers’ classroom practices in secondary schools in the South West Region of Cameroon. With the results confirming each other, the study recommends that mentoring should focus on helping teachers employ social interactions and instructional practices feedback and clarity in teaching that have direct measurable impact on students’ learning achievements. Andrew Ngeim Sumba | Frederick Ebot Ashu | Peter Agborbechem Tambi "The Role of Mentoring and Its Influence on the Effectiveness of the Teaching of Physics in Secondary Schools in the South West Region of Cameroon" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64524.pdf Paper Url: https://www.ijtsrd.com/management/management-development/64524/the-role-of-mentoring-and-its-influence-on-the-effectiveness-of-the-teaching-of-physics-in-secondary-schools-in-the-south-west-region-of-cameroon/andrew-ngeim-sumba
Design Simulation and Hardware Construction of an Arduino Microcontroller Bas...ijtsrd
This study primarily focuses on the design of a high side buck converter using an Arduino microcontroller. The converter is specifically intended for use in DC DC applications, particularly in standalone solar PV systems where the PV output voltage exceeds the load or battery voltage. To evaluate the performance of the converter, simulation experiments are conducted using Proteus Software. These simulations provide insights into the input and output voltages, currents, powers, and efficiency under different state of charge SoC conditions of a 12V,70Ah rechargeable lead acid battery. Additionally, the hardware design of the converter is implemented, and practical data is collected through operation, monitoring, and recording. By comparing the simulation results with the practical results, the efficiency and performance of the designed converter are assessed. The findings indicate that while the buck converter is suitable for practical use in standalone PV systems, its efficiency is compromised due to a lower output current. Chan Myae Aung | Dr. Ei Mon "Design Simulation and Hardware Construction of an Arduino-Microcontroller Based DC-DC High-Side Buck Converter for Standalone PV System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64518.pdf Paper Url: https://www.ijtsrd.com/engineering/mechanical-engineering/64518/design-simulation-and-hardware-construction-of-an-arduinomicrocontroller-based-dcdc-highside-buck-converter-for-standalone-pv-system/chan-myae-aung
Sustainable Energy by Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadikuijtsrd
Energy becomes sustainable if it meets the needs of the present without compromising the ability of future generations to meet their own needs. Some of the definitions of sustainable energy include the considerations of environmental aspects such as greenhouse gas emissions, social, and economic aspects such as energy poverty. Generally far more sustainable than fossil fuel are renewable energy sources such as wind, hydroelectric power, solar, and geothermal energy sources. Worthy of note is that some renewable energy projects, like the clearing of forests to produce biofuels, can cause severe environmental damage. The sustainability of nuclear power which is a low carbon source is highly debated because of concerns about radioactive waste, nuclear proliferation, and accidents. The switching from coal to natural gas has environmental benefits, including a lower climate impact, but could lead to delay in switching to more sustainable options. “Carbon capture and storage” can be built into power plants to remove the carbon dioxide CO2 emissions, but this technology is expensive and has rarely been implemented. Leading non renewable energy sources around the world is fossil fuels, coal, petroleum, and natural gas. Nuclear energy is usually considered another non renewable energy source, although nuclear energy itself is a renewable energy source, but the material used in nuclear power plants is not. The paper addresses the issue of sustainable energy, its attendant benefits to the future generation, and humanity in general. Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadiku "Sustainable Energy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64534.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/64534/sustainable-energy/paul-a-adekunte
Concepts for Sudan Survey Act Implementations Executive Regulations and Stand...ijtsrd
This paper aims to outline the executive regulations, survey standards, and specifications required for the implementation of the Sudan Survey Act, and for regulating and organizing all surveying work activities in Sudan. The act has been discussed for more than 5 years. The Land Survey Act was initiated by the Sudan Survey Authority and all official legislations were headed by the Sudan Ministry of Justice till it was issued in 2022. The paper presents conceptual guidelines to be used for the Survey Act implementation and to regulate the survey work practice, standardizing the field surveys, processing, quality control, procedures, and the processes related to survey work carried out by the stakeholders and relevant authorities in Sudan. The conceptual guidelines are meant to improve the quality and harmonization of geospatial data and to aid decision making processes as well as geospatial information systems. The established comprehensive executive regulations will govern and regulate the implementation of the Sudan Survey Geomatics Act in all surveying and mapping practices undertaken by the Sudan Survey Authority SSA and state local survey departments for public or private sector organizations. The targeted standards and specifications include the reference frame, projection, coordinate systems, and the guidelines and specifications that must be followed in the field of survey work, processes, and mapping products. In the last few decades, there has been a growing awareness of the importance of geomatics activities and measurements on the Earths surface in space and time, together with observing and mapping the changes. In such cases, data must be captured promptly, standardized, and obtained with more accuracy and specified in much detail. The paper will also highlight the current situation in Sudan, the degree to which survey standards are used, the problems encountered, and the errors that arise from not using the standards and survey specifications. Kamal A. A. Sami "Concepts for Sudan Survey Act Implementations - Executive Regulations and Standards" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63484.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63484/concepts-for-sudan-survey-act-implementations--executive-regulations-and-standards/kamal-a-a-sami
Towards the Implementation of the Sudan Interpolated Geoid Model Khartoum Sta...ijtsrd
The discussions between ellipsoid and geoid have invoked many researchers during the recent decades, especially during the GNSS technology era, which had witnessed a great deal of development but still geoid undulation requires more investigations. To figure out a solution for Sudans local geoid, this research has tried to intake the possibility of determining the geoid model by following two approaches, gravimetric and geometrical geoid model determination, by making use of GNSS leveling benchmarks at Khartoum state. The Benchmarks are well distributed in the study area, in which, the horizontal coordinates and the height above the ellipsoid have been observed by GNSS while orthometric heights were carried out using precise leveling. The Global Geopotential Model GGM represented in EGM2008 has been exploited to figure out the geoid undulation at the benchmarks in the study area. This is followed by a fitting process, that has been done to suit the geoid undulation data which has been computed using GNSS leveling data and geoid undulation inspired by the EGM2008. Two geoid surfaces were created after the fitting process to ensure that they are identical and both of them could be counted for getting the same geoid undulation with an acceptable accuracy. In this respect, statistical operation played an important role in ensuring the consistency and integrity of the model by applying cross validation techniques splitting the data into training and testing datasets for building the geoid model and testing its eligibility. The geometrical solution for geoid undulation computation has been utilized by applying straightforward equations that facilitate the calculation of the geoid undulation directly through applying statistical techniques for the GNSS leveling data of the study area to get the common equation parameters values that could be utilized to calculate geoid undulation of any position in the study area within the claimed accuracy. Both systems were checked and proved eligible to be used within the study area with acceptable accuracy which may contribute to solving the geoid undulation problem in the Khartoum area, and be further generalized to determine the geoid model over the entire country, and this could be considered in the future, for regional and continental geoid model. Ahmed M. A. Mohammed. | Kamal A. A. Sami "Towards the Implementation of the Sudan Interpolated Geoid Model (Khartoum State Case Study)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63483.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63483/towards-the-implementation-of-the-sudan-interpolated-geoid-model-khartoum-state-case-study/ahmed-m-a-mohammed
Activating Geospatial Information for Sudans Sustainable Investment Mapijtsrd
Sudan is witnessing an acceleration in the processes of development and transformation in the performance of government institutions to raise the productivity and investment efficiency of the government sector. The development plans and investment opportunities have focused on achieving national goals in various sectors. This paper aims to illuminate the path to the future and provide geospatial data and information to develop the investment climate and environment for all sized businesses, and to bridge the development gap between the Sudan states. The Sudan Survey Authority SSA is the main advisor to the Sudan Government in conducting surveying, mappings, designing, and developing systems related to geospatial data and information. In recent years, SSA made a strategic partnership with the Ministry of Investment to activate Geospatial Information for Sudans Sustainable Investment and in particular, for the preparation and implementation of the Sudan investment map, based on the directives and objectives of the Ministry of Investment MI in Sudan. This paper comes within the framework of activating the efforts of the Ministry of Investment to develop technical investment services by applying techniques adopted by the Ministry and its strategic partners for advancing investment processes in the country. Kamal A. A. Sami "Activating Geospatial Information for Sudan's Sustainable Investment Map" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63482.pdf Paper Url: https://www.ijtsrd.com/engineering/information-technology/63482/activating-geospatial-information-for-sudans-sustainable-investment-map/kamal-a-a-sami
Educational Unity Embracing Diversity for a Stronger Societyijtsrd
In a rapidly changing global landscape, the importance of education as a unifying force cannot be overstated. This paper explores the crucial role of educational unity in fostering a stronger and more inclusive society through the embrace of diversity. By examining the benefits of diverse learning environments, the paper aims to highlight the positive impact on societal strength. The discussion encompasses various dimensions, from curriculum design to classroom dynamics, and emphasizes the need for educational institutions to become catalysts for unity in diversity. It highlights the need for a paradigm shift in educational policies, curricula, and pedagogical approaches to ensure that they are reflective of the diverse fabric of society. This paper also addresses the challenges associated with implementing inclusive educational practices and offers practical strategies for overcoming barriers. It advocates for collaborative efforts between educational institutions, policymakers, and communities to create a supportive ecosystem that promotes diversity and unity. Mr. Amit Adhikari | Madhumita Teli | Gopal Adhikari "Educational Unity: Embracing Diversity for a Stronger Society" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64525.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64525/educational-unity-embracing-diversity-for-a-stronger-society/mr-amit-adhikari
Integration of Indian Indigenous Knowledge System in Management Prospects and...ijtsrd
The diversity of indigenous knowledge systems in India is vast and can vary significantly between different communities and regions. Preserving and respecting these knowledge systems is crucial for maintaining cultural heritage, promoting sustainable practices, and fostering cross cultural understanding. In this paper, an overview of the prospects and challenges associated with incorporating Indian indigenous knowledge into management is explored. It is found that IIKS helps in management in many areas like sustainable development, tourism, food security, natural resource management, cultural preservation and innovation, etc. However, IIKS integration with management faces some challenges in the form of a lack of documentation, cultural sensitivity, language barriers legal framework, etc. Savita Lathwal "Integration of Indian Indigenous Knowledge System in Management: Prospects and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63500.pdf Paper Url: https://www.ijtsrd.com/management/accounting-and-finance/63500/integration-of-indian-indigenous-knowledge-system-in-management-prospects-and-challenges/savita-lathwal
DeepMask Transforming Face Mask Identification for Better Pandemic Control in...ijtsrd
The COVID 19 pandemic has highlighted the crucial need of preventive measures, with widespread use of face masks being a key method for slowing the viruss spread. This research investigates face mask identification using deep learning as a technological solution to be reducing the risk of coronavirus transmission. The proposed method uses state of the art convolutional neural networks CNNs and transfer learning to automatically recognize persons who are not wearing masks in a variety of circumstances. We discuss how this strategy improves public health and safety by providing an efficient manner of enforcing mask wearing standards. The report also discusses the obstacles, ethical concerns, and prospective applications of face mask detection systems in the ongoing fight against the pandemic. Dilip Kumar Sharma | Aaditya Yadav "DeepMask: Transforming Face Mask Identification for Better Pandemic Control in the COVID-19 Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64522.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/64522/deepmask-transforming-face-mask-identification-for-better-pandemic-control-in-the-covid19-era/dilip-kumar-sharma
Streamlining Data Collection eCRF Design and Machine Learningijtsrd
Efficient and accurate data collection is paramount in clinical trials, and the design of Electronic Case Report Forms eCRFs plays a pivotal role in streamlining this process. This paper explores the integration of machine learning techniques in the design and implementation of eCRFs to enhance data collection efficiency. We delve into the synergies between eCRF design principles and machine learning algorithms, aiming to optimize data quality, reduce errors, and expedite the overall data collection process. The application of machine learning in eCRF design brings forth innovative approaches to data validation, anomaly detection, and real time adaptability. This paper discusses the benefits, challenges, and future prospects of leveraging machine learning in eCRF design for streamlined and advanced data collection in clinical trials. Dhanalakshmi D | Vijaya Lakshmi Kannareddy "Streamlining Data Collection: eCRF Design and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63515.pdf Paper Url: https://www.ijtsrd.com/biological-science/biotechnology/63515/streamlining-data-collection-ecrf-design-and-machine-learning/dhanalakshmi-d
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD30192 | Volume – 4 | Issue – 2 | January-February 2020 Page 1011
brain tumors, but also improve clinical doctors to study the
mechanism of brain tumors at the aim of better treatment.
Clinical doctors play an important role in brain tumor
assessment and therapy. This information is very important
and critical in deciding between the different forms of
therapy such as surgery, radiation, and chemotherapy.
Therefore, the evaluation of brain tumors with imaging
modalities is now one of the key issues of radiology
departments.
II. PROPOSED SYSTEM
In this project we discuss about the brain tumors disease
detection by using a method at MRI images.Nowadays many
peoples are affected at more Brain cell tumor disease. So
using that situation many doctors and hospitals are easily
theft more money from patients. The common peoples are
mostly affected by this problem. We propose the method is
used to predict the disease accurately. Then it detect all the
Brain tumor disease easily. That is used to detect all the
brain cell related diseases and its provide more accuracy.
Then the detection of brain tumor disease at less
computation time. Our proposed method is used to predict
all the brain cell related diseases like that Tumors. They are
easily detected and its used accurately identify the diseases
in less processing time.
Fig1. Block Diagram
III. SOFTWARE IMPLEMENTATION
A. DATA ACQUISITION
The disease affected image or not affected images are
captured from camera or to upload the images. It is used to
upload the pair of input images. However, it differs from
conventional methods by using thermal images as input.
Fig2. Data acquisition
B. PRE PROCESSING
The pair of images is preprocessed it by the alignment
process. The main process of the preprocessing is used to
separate the meaningful features. The academic community
has achieved fruitful breakthroughs in the field of brain
image in the past few decades. Processingchainisde-noising
medical thresholding techniques in noise presence for
various wavelet families. We applied Haar, Symlet, Morlet,
and Daubechies in de-noising MRI brain images.
Performance estimationand analysisareaccomplishedusing
Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio
(PSNR) and Mean Square Error (MSE). We are using
wavelets to de-noise images. In medical images, edges are
places where the image brightness changesfast.Maintaining
edges while de-noising an image is severely important for
initiative quality. Traditional low pass filtering removes
noise, it often smoothensedgesandinfluencesimagequality.
Wavelets are able to remove noise while maintaining
important features. From the obtained results it can be
confirmed that the wavelets with higher level tend to give
good result. Since the SNR value correspondingtothehigher
level. The same goes for Symlet wavelets. While the best
result are obtained using the Haar wavelets, with highest
SNR value, least MSE and least entropy. It can be conclude
from above results that the wavelet that are higher level
show better results.
Fig3. Preprocessing
C. IMAGE SEGMENTATION
The segmentation method is described using its free
parametric character and unsupervised nature of threshold
choice and has the following benefits like the process is very
easy but only the zeroth and first ordercumulativemoments
of the Greylevel histogram are used. Wecanapplythesimple
extension to multi thresholding problems that is possible by
the criteria on which the method is based, we can
automatically selecting an optimal threshold or set of
threshold, that are not based on the diffraction (i.e. a local
property such as valley) but on the integration (i.e. global
property) of the histogram.
We can also analyze other aspects for example evaluation of
class separabality, estimation of class mean levels, etc. We
are able to underline the generality of themethod,itcoversa
large unsupervised decision procedure. That is used to
automatically perform clustering- basedimagethresholding
or reduction of grey-level image to a binary image in
computer vision and image processing. The algorithm
presumes that the image contains two classes of pixels
following bimodal histogram, it then calculatestheoptimum
threshold separating the two classes so that their mixed
expansion is minimal, or uniformly so that their inter class
variance is maximal.
3. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD30192 | Volume – 4 | Issue – 2 | January-February 2020 Page 1012
Fig4. Image Segmentation
D. IMAGE CLASSIFICATION
The classification method is used to classify the object easily
so we are detecting the object accurately. Then this method
is used to classify the disease accurately and refining a
background objects accurately. Our data hasspecificallytwo
classes we can use a support vector machine (SVM). We are
using a set of new MRI brain images. Finding the best hyper
plane that detaches all data points of one class those of the
other class means correct data classification using SVM
methods. Establishing the best hyper plane for an SVM
means the one with the largest margin between the two
classes.
The maximal width of the plate parallel to the hyper plane
that has no interior data points determine the margin.
Complicated binary classification problems do not have a
simple hyper plane as a useful separating criterion. There is
a variant of the mathematical approach that retains nearly
all the simplicity of an SVM separating hyper plane for those
problems.
Fig4. Image Classification
E. FEATURE EXTRACTION
This method is used to predict disease accurately. This
system identify from the MRI image at the brain is normal or
affected. Then the useful disease prediction from the brain
images then it provides the range of disease level. We
remove the average pooling layers from the pre-trained
model and add auxiliary convolution layers to detect large
sizes of objects. It will not be surprising for getting a better
result after adding a top-down structure inFGstage,butthat
is beyond the scope of this paper.
Fig5. Feature Extraction
IV. CONCLUSION
The brain tumor detection and classification system is
implemented using CWT, DWT and SVMs. The result shows
that SVMs having the proper sets of training data are able to
distinguish between abnormal and normal tumor regions
and classify them correctly as a benign tumor, malign tumor
or healthy brain. In practice, SVMs have significant
computational advantages Five times improvement in
computation speed (22 vs. 110 ms) for our proposed
method.
This classification is very important for the physician in
establishing a precise diagnostic and recommending a
correct further treatment. If we are interested in de-noising,
compression, restoration, then DWT is often more
appropriate. A hybrid approach is recommended in solving
properly the detection and classification problems in brain
tumors. Our method is used to predict the diseases
accurately. Then these methods are used to predict the
disease is affected or not affected by using a comparison
method. These methodology are validated by a
comprehensive set of comparisons against competing and
well-established image registration methods, by using real
medical datasets and classic measurestypicallyemployedas
a benchmark by the medical imaging community our
proposed method is mostly used in medical field.itisused to
easily detect the diseases.
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