Submit Search
Upload
Deep Learning for Leukemia Detection: A MobileNetV2-Based Approach for Accurate and Efficient Diagnosis
•
0 likes
•
6 views
IRJET Journal
Follow
https://www.irjet.net/archives/V10/i10/IRJET-V10I10127.pdf
Read less
Read more
Engineering
Report
Share
Report
Share
1 of 4
Download now
Download to read offline
Recommended
CLASSIFICATION AND SEGMENTATION OF LEUKEMIA USING CONVOLUTION NEURAL NETWORK
CLASSIFICATION AND SEGMENTATION OF LEUKEMIA USING CONVOLUTION NEURAL NETWORK
IRJET Journal
Lung Cancer Detection using Convolutional Neural Network
Lung Cancer Detection using Convolutional Neural Network
IRJET Journal
Investigation of white blood cell biomaker model for acute lymphoblastic leuk...
Investigation of white blood cell biomaker model for acute lymphoblastic leuk...
journalBEEI
REVIEW 1 - PROJECT PPT TEMPLATE (4) (3).pptx
REVIEW 1 - PROJECT PPT TEMPLATE (4) (3).pptx
sathiyasowmi
IRJET- Breast Cancer Detection from Histopathology Images: A Review
IRJET- Breast Cancer Detection from Histopathology Images: A Review
IRJET Journal
Discovering Abnormal Patches and Transformations of Diabetics Retinopathy in ...
Discovering Abnormal Patches and Transformations of Diabetics Retinopathy in ...
cscpconf
DISCOVERING ABNORMAL PATCHES AND TRANSFORMATIONS OF DIABETICS RETINOPATHY IN ...
DISCOVERING ABNORMAL PATCHES AND TRANSFORMATIONS OF DIABETICS RETINOPATHY IN ...
csandit
MALARIAL PARASITES DETECTION IN THE BLOOD CELL USING CONVOLUTIONAL NEURAL NET...
MALARIAL PARASITES DETECTION IN THE BLOOD CELL USING CONVOLUTIONAL NEURAL NET...
IRJET Journal
Recommended
CLASSIFICATION AND SEGMENTATION OF LEUKEMIA USING CONVOLUTION NEURAL NETWORK
CLASSIFICATION AND SEGMENTATION OF LEUKEMIA USING CONVOLUTION NEURAL NETWORK
IRJET Journal
Lung Cancer Detection using Convolutional Neural Network
Lung Cancer Detection using Convolutional Neural Network
IRJET Journal
Investigation of white blood cell biomaker model for acute lymphoblastic leuk...
Investigation of white blood cell biomaker model for acute lymphoblastic leuk...
journalBEEI
REVIEW 1 - PROJECT PPT TEMPLATE (4) (3).pptx
REVIEW 1 - PROJECT PPT TEMPLATE (4) (3).pptx
sathiyasowmi
IRJET- Breast Cancer Detection from Histopathology Images: A Review
IRJET- Breast Cancer Detection from Histopathology Images: A Review
IRJET Journal
Discovering Abnormal Patches and Transformations of Diabetics Retinopathy in ...
Discovering Abnormal Patches and Transformations of Diabetics Retinopathy in ...
cscpconf
DISCOVERING ABNORMAL PATCHES AND TRANSFORMATIONS OF DIABETICS RETINOPATHY IN ...
DISCOVERING ABNORMAL PATCHES AND TRANSFORMATIONS OF DIABETICS RETINOPATHY IN ...
csandit
MALARIAL PARASITES DETECTION IN THE BLOOD CELL USING CONVOLUTIONAL NEURAL NET...
MALARIAL PARASITES DETECTION IN THE BLOOD CELL USING CONVOLUTIONAL NEURAL NET...
IRJET Journal
IRJET- Analysis of Automated Detection of WBC Cancer Diseases in Biomedical P...
IRJET- Analysis of Automated Detection of WBC Cancer Diseases in Biomedical P...
IRJET Journal
Generalized deep learning model for Classification of Gastric, Colon and Rena...
Generalized deep learning model for Classification of Gastric, Colon and Rena...
IRJET Journal
Breast Cancer Detection Using Machine Learning
Breast Cancer Detection Using Machine Learning
IRJET Journal
PPT-Detection of Blood Cancer in Microscopic Images of Human Blood.pptx
PPT-Detection of Blood Cancer in Microscopic Images of Human Blood.pptx
devnamu
Gaussian Multi-Scale Feature Disassociation Screening in Tuberculosise
Gaussian Multi-Scale Feature Disassociation Screening in Tuberculosise
ijceronline
Detection of Skin Diseases based on Skin lesion images
Detection of Skin Diseases based on Skin lesion images
IRJET Journal
Rapid detection of diabetic retinopathy in retinal images: a new approach usi...
Rapid detection of diabetic retinopathy in retinal images: a new approach usi...
IJECEIAES
IRJET - Classification of Cancer Images using Deep Learning
IRJET - Classification of Cancer Images using Deep Learning
IRJET Journal
AI Based Approach for Classification of MultiGrade Tumour in Human Brain
AI Based Approach for Classification of MultiGrade Tumour in Human Brain
IRJET Journal
IRJET - Survey on Analysis of Breast Cancer Prediction
IRJET - Survey on Analysis of Breast Cancer Prediction
IRJET Journal
AnoMalNet: outlier detection based malaria cell image classification method l...
AnoMalNet: outlier detection based malaria cell image classification method l...
International Journal of Reconfigurable and Embedded Systems
Breast cancer histological images nuclei segmentation and optimized classifi...
Breast cancer histological images nuclei segmentation and optimized classifi...
IJECEIAES
deep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumor
Venkat Projects
Analysis of Blood Samples Using Anfis Classification
Analysis of Blood Samples Using Anfis Classification
IRJET Journal
Cervical cancer diagnosis based on cytology pap smear image classification us...
Cervical cancer diagnosis based on cytology pap smear image classification us...
TELKOMNIKA JOURNAL
DETECTION OF LIVER INFECTION USING MACHINE LEARNING TECHNIQUES
DETECTION OF LIVER INFECTION USING MACHINE LEARNING TECHNIQUES
IRJET Journal
Pneumonia Detection Using Convolutional Neural Network Writers
Pneumonia Detection Using Convolutional Neural Network Writers
IRJET Journal
Cervical Cancer Detection: An Enhanced Approach through Transfer Learning and...
Cervical Cancer Detection: An Enhanced Approach through Transfer Learning and...
IRJET Journal
REVIEW OF MACHINE LEARNING APPLICATIONS AND DATASETS IN CLASSIFICATION OF ACU...
REVIEW OF MACHINE LEARNING APPLICATIONS AND DATASETS IN CLASSIFICATION OF ACU...
IJDKP
An Analysis of The Methods Employed for Breast Cancer Diagnosis
An Analysis of The Methods Employed for Breast Cancer Diagnosis
IJORCS
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
IRJET Journal
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
IRJET Journal
More Related Content
Similar to Deep Learning for Leukemia Detection: A MobileNetV2-Based Approach for Accurate and Efficient Diagnosis
IRJET- Analysis of Automated Detection of WBC Cancer Diseases in Biomedical P...
IRJET- Analysis of Automated Detection of WBC Cancer Diseases in Biomedical P...
IRJET Journal
Generalized deep learning model for Classification of Gastric, Colon and Rena...
Generalized deep learning model for Classification of Gastric, Colon and Rena...
IRJET Journal
Breast Cancer Detection Using Machine Learning
Breast Cancer Detection Using Machine Learning
IRJET Journal
PPT-Detection of Blood Cancer in Microscopic Images of Human Blood.pptx
PPT-Detection of Blood Cancer in Microscopic Images of Human Blood.pptx
devnamu
Gaussian Multi-Scale Feature Disassociation Screening in Tuberculosise
Gaussian Multi-Scale Feature Disassociation Screening in Tuberculosise
ijceronline
Detection of Skin Diseases based on Skin lesion images
Detection of Skin Diseases based on Skin lesion images
IRJET Journal
Rapid detection of diabetic retinopathy in retinal images: a new approach usi...
Rapid detection of diabetic retinopathy in retinal images: a new approach usi...
IJECEIAES
IRJET - Classification of Cancer Images using Deep Learning
IRJET - Classification of Cancer Images using Deep Learning
IRJET Journal
AI Based Approach for Classification of MultiGrade Tumour in Human Brain
AI Based Approach for Classification of MultiGrade Tumour in Human Brain
IRJET Journal
IRJET - Survey on Analysis of Breast Cancer Prediction
IRJET - Survey on Analysis of Breast Cancer Prediction
IRJET Journal
AnoMalNet: outlier detection based malaria cell image classification method l...
AnoMalNet: outlier detection based malaria cell image classification method l...
International Journal of Reconfigurable and Embedded Systems
Breast cancer histological images nuclei segmentation and optimized classifi...
Breast cancer histological images nuclei segmentation and optimized classifi...
IJECEIAES
deep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumor
Venkat Projects
Analysis of Blood Samples Using Anfis Classification
Analysis of Blood Samples Using Anfis Classification
IRJET Journal
Cervical cancer diagnosis based on cytology pap smear image classification us...
Cervical cancer diagnosis based on cytology pap smear image classification us...
TELKOMNIKA JOURNAL
DETECTION OF LIVER INFECTION USING MACHINE LEARNING TECHNIQUES
DETECTION OF LIVER INFECTION USING MACHINE LEARNING TECHNIQUES
IRJET Journal
Pneumonia Detection Using Convolutional Neural Network Writers
Pneumonia Detection Using Convolutional Neural Network Writers
IRJET Journal
Cervical Cancer Detection: An Enhanced Approach through Transfer Learning and...
Cervical Cancer Detection: An Enhanced Approach through Transfer Learning and...
IRJET Journal
REVIEW OF MACHINE LEARNING APPLICATIONS AND DATASETS IN CLASSIFICATION OF ACU...
REVIEW OF MACHINE LEARNING APPLICATIONS AND DATASETS IN CLASSIFICATION OF ACU...
IJDKP
An Analysis of The Methods Employed for Breast Cancer Diagnosis
An Analysis of The Methods Employed for Breast Cancer Diagnosis
IJORCS
Similar to Deep Learning for Leukemia Detection: A MobileNetV2-Based Approach for Accurate and Efficient Diagnosis
(20)
IRJET- Analysis of Automated Detection of WBC Cancer Diseases in Biomedical P...
IRJET- Analysis of Automated Detection of WBC Cancer Diseases in Biomedical P...
Generalized deep learning model for Classification of Gastric, Colon and Rena...
Generalized deep learning model for Classification of Gastric, Colon and Rena...
Breast Cancer Detection Using Machine Learning
Breast Cancer Detection Using Machine Learning
PPT-Detection of Blood Cancer in Microscopic Images of Human Blood.pptx
PPT-Detection of Blood Cancer in Microscopic Images of Human Blood.pptx
Gaussian Multi-Scale Feature Disassociation Screening in Tuberculosise
Gaussian Multi-Scale Feature Disassociation Screening in Tuberculosise
Detection of Skin Diseases based on Skin lesion images
Detection of Skin Diseases based on Skin lesion images
Rapid detection of diabetic retinopathy in retinal images: a new approach usi...
Rapid detection of diabetic retinopathy in retinal images: a new approach usi...
IRJET - Classification of Cancer Images using Deep Learning
IRJET - Classification of Cancer Images using Deep Learning
AI Based Approach for Classification of MultiGrade Tumour in Human Brain
AI Based Approach for Classification of MultiGrade Tumour in Human Brain
IRJET - Survey on Analysis of Breast Cancer Prediction
IRJET - Survey on Analysis of Breast Cancer Prediction
AnoMalNet: outlier detection based malaria cell image classification method l...
AnoMalNet: outlier detection based malaria cell image classification method l...
Breast cancer histological images nuclei segmentation and optimized classifi...
Breast cancer histological images nuclei segmentation and optimized classifi...
deep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumor
Analysis of Blood Samples Using Anfis Classification
Analysis of Blood Samples Using Anfis Classification
Cervical cancer diagnosis based on cytology pap smear image classification us...
Cervical cancer diagnosis based on cytology pap smear image classification us...
DETECTION OF LIVER INFECTION USING MACHINE LEARNING TECHNIQUES
DETECTION OF LIVER INFECTION USING MACHINE LEARNING TECHNIQUES
Pneumonia Detection Using Convolutional Neural Network Writers
Pneumonia Detection Using Convolutional Neural Network Writers
Cervical Cancer Detection: An Enhanced Approach through Transfer Learning and...
Cervical Cancer Detection: An Enhanced Approach through Transfer Learning and...
REVIEW OF MACHINE LEARNING APPLICATIONS AND DATASETS IN CLASSIFICATION OF ACU...
REVIEW OF MACHINE LEARNING APPLICATIONS AND DATASETS IN CLASSIFICATION OF ACU...
An Analysis of The Methods Employed for Breast Cancer Diagnosis
An Analysis of The Methods Employed for Breast Cancer Diagnosis
More from IRJET Journal
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
IRJET Journal
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
IRJET Journal
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
IRJET Journal
Effect of Camber and Angles of Attack on Airfoil Characteristics
Effect of Camber and Angles of Attack on Airfoil Characteristics
IRJET Journal
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
IRJET Journal
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
IRJET Journal
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
IRJET Journal
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
IRJET Journal
A REVIEW ON MACHINE LEARNING IN ADAS
A REVIEW ON MACHINE LEARNING IN ADAS
IRJET Journal
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
IRJET Journal
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
IRJET Journal
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
IRJET Journal
Survey Paper on Cloud-Based Secured Healthcare System
Survey Paper on Cloud-Based Secured Healthcare System
IRJET Journal
Review on studies and research on widening of existing concrete bridges
Review on studies and research on widening of existing concrete bridges
IRJET Journal
React based fullstack edtech web application
React based fullstack edtech web application
IRJET Journal
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
IRJET Journal
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
IRJET Journal
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
IRJET Journal
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
IRJET Journal
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
IRJET Journal
More from IRJET Journal
(20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
Effect of Camber and Angles of Attack on Airfoil Characteristics
Effect of Camber and Angles of Attack on Airfoil Characteristics
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
A REVIEW ON MACHINE LEARNING IN ADAS
A REVIEW ON MACHINE LEARNING IN ADAS
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
Survey Paper on Cloud-Based Secured Healthcare System
Survey Paper on Cloud-Based Secured Healthcare System
Review on studies and research on widening of existing concrete bridges
Review on studies and research on widening of existing concrete bridges
React based fullstack edtech web application
React based fullstack edtech web application
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
Recently uploaded
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
ranjana rawat
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZTE
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
null - The Open Security Community
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Dr.Costas Sachpazis
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptx
upamatechverse
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
Call Girls in Nagpur High Profile
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile service
rehmti665
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
ranjana rawat
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
Soham Mondal
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
purnimasatapathy1234
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
Tsuyoshi Horigome
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCL
DeelipZope
Biology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptx
DeepakSakkari2
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
ranjana rawat
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
9953056974 Low Rate Call Girls In Saket, Delhi NCR
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
Call Girls in Nagpur High Profile
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
ranjana rawat
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
Suhani Kapoor
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Low Rate Call Girls In Saket, Delhi NCR
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
João Esperancinha
Recently uploaded
(20)
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptx
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile service
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCL
Biology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptx
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Deep Learning for Leukemia Detection: A MobileNetV2-Based Approach for Accurate and Efficient Diagnosis
1.
© 2023, IRJET
| Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 876 Deep Learning for Leukemia Detection: A MobileNetV2-Based Approach for Accurate and Efficient Diagnosis Lagisetty Naga Pavithra1 1Student, Dept of Computer Science, Bangalore Institute of Technology, Bengaluru, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract – Acute lymphoblastic leukemia (ALL) is a type of cancer of blood and bone marrow, which is not only fatal but also very expensive to treat. Leukemia detection atearlystage would can save lives and money. It is very common in children. Most leukemia in childrenistreated. Researchstudiesreported that leukemia brings changes in white blood cells count. Currently for initial ALL diagnosis evaluation is done manually. This is time consuming and prone to errors. The proposed model is based on data collected from Kaggle dataset. The MobileNetV2 model is a lightweight model through which I have achieved an accuracy of 98.88% on training data and accuracy of 98.58% on testing data, with precision of 0.986, recall of 0.9858 and F1 score of 0.9857. Experiments were conducted on dataset containing 3256 images from 89 patients suspected of ALL, including 25 healthy individuals. Currently the dataset contains three stages which are Early Pre-B, Pre-B and Pro-B ALL. Key Words: Acute lymphoblastic leukemia (ALL), MobileNetV2, blood cancer, bone marrow, deep learning, leukemia 1.INTRODUCTION Leukemia is cancerof blood orbone marrowwhichproduces blood cells. It usually involves white blood cells.Whiteblood cells are infection fighters, where they divide in orderly way to fight as your body needs them. But when it comes to people with leukemia there is abnormal amount of white blood cells. Treatment is very complicated and varies based on the type of leukemia tat the person is facing and involves various other factors. There are many types of leukemia but few of them are very common in children which is ALL. It occurs in children of age 2 to 4. Acutemyelogenousleukemia (AML) is second most common in children. ALL can affect different types of lymphocytescalledB-cellsorT-cells.Blood stem cells originate in the bone marrow, mainly in flatbones in adults (hip, sternum, skull, ribs, vertebrae, scapulae, to name a few.), and can follow two developmental lines. Cells of the myeloid lineage give rise to white blood cells, especially neutrophil monocytes, platelets, and red blood cells; Cells of the lymphoid lining produce white blood cells, also called lymphocytes [1]. Leukemia occurs when there is damage in DNA of developing blood cells, mainlywhitebloodcellswhichcauses the blood cells to divide and grow uncontrollable. Researchers say that leukemia might be genetic and run in the family. Few of the symptoms of leukemia include fatigue, weakness, pale skin, fever, and chills. It also causes headaches, nausea, vomiting, confusion, seizures. Leukemia can cause petechiae, a rash like collection of pinpoint red spots on the skin. Currently leukemia is not curable. In few cases it is treatable with chemotherapy, radiation therapy, stem cell transplantation, CART-cell therapy,targettherapyandother methods. A risk factor is anything that may increase your chance of having a disease. Some of the risk factors include smoking, exposure to certain chemicals, radiation exposure and blood disorders. There are several methods that can be used to detect leukemia like CNN, EfficientNet,ResNet,DenseNetandmany more. The proposed model is based on MobileNetV2. MobileNetV2 excels due to its efficiency, lightweight design, and fast inference, making it suitable for resource- constrained environments and real-time applications. It offers strong generalization through pre-trained weights, robust feature extraction, scalability, and competitive performance, backed by open-source accessibility and community support. The rest of the paper is organized as follows: Section II Literature review, Section III presents the proposed architecture, and IV and V explain the experimental settings, results, and conclusion. Finally, Section VI discusses the future work. 2. LITERATURE REVIEW N. Jiwani et al. [1] introduced a pioneering approach using Pattern Recognition and Computational Deep Learning to enhance acute lymphoblastic leukemia (ALL) diagnosis and management. The ALLDM model achieved impressive accuracy rates, such as 87.92% in chemotherapy management and 94.31% in stem cell transplantation management. This technology holds promise for improving ALL treatment outcomes, especially in children. A. Batool et al. [2] proposed a comprehensive solution to address the diagnostic complexities of acute lymphoblastic leukemia (ALL). Their work introduces a state-of-the-art DL model based on EfficientNet-B3, achieving remarkable accuracy in leukemia cell classification. This model outperforms existing DL classifiers, offering a robust and reliable tool to enhance clinical leukemia detection and improve patient outcomes. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 10 | Oct 2023 www.irjet.net p-ISSN: 2395-0072
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 10 | Oct 2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 877 M. A. Hossain et al. [3] proposed a cost-effective solution to detect early-stage leukemia based on symptoms. Their explainable supervised machine learning model, using decision trees and the Apriori algorithm,outperformedother algorithms with a 97.45% accuracy rate. Sharing the dataset and code enhances resources for future leukemia research. N. Akram et al. [4] introduced a pioneering solution for leukemia diagnosis, focusing on WBC segmentation. Their multi-scale information fusion network (MIF-Net), with its internal and external spatial informationfusionmechanisms, excelled in the accurate segmentation of challenging WBC images. Across four datasets, MIF-Net achieved state-of-the- art segmentation performance, boasting remarkable accuracy, and it maintains computational efficiency with just 2.67 million trainable parameters. Atteia, G et al. [5] introduced a Bayesian-optimized convolutional neural network (CNN) foracutelymphoblastic leukemia(ALL)detectioninbloodsmearimages.Themodel's hyperparameters were tailored usingBayesianoptimization, resulting in enhanced classification performance. This innovative approach yielded superior accuracy, outperforming other optimized deep learning models, promising improved ALL detection. Chen et al. [6] introduced aResnet101-9 ensemble model for acute lymphoblasticleukemia(ALL)detectioninmicroscopic images, combining nine trained Resnet-101 models with majority voting. Algorithm hyperparameterswereoptimized through the Taguchi method. The model achieved an accuracy of 85.11% and an F1-score of 88.94, surpassing individual models and excelling in precision, recall, and specificity. Houssein EH et al. [7] introduced an end-to-end computer- aided diagnosis (CAD) system for leukocyte classification using deep learning. They combined DenseNet-161 with cyclical learning rateand the one-cycletechniquetooptimize hyperparameters. The model achieved remarkableaccuracy, with 100% on the training set and 99.8% on the testing set, promising significant improvements in white blood cell classification. Kruse A et al. [8] proposed an advanced model for Minimal Residual Disease (MRD) detection, crucial for predicting leukemiarelapse.Theyleveragednext-generationsequencing (NGS) to enhance MRD diagnostics' sensitivity. The model employed phenotypic markers and differentialgenepatterns analysed through various techniques like flow cytometry (FCM), PCR, RQ-PCR, RT-PCR, or NGS. Bibi N et al. [9] presented an IoMT-based framework for quick and safe leukemia identification, aiming to address the shortcomings of existing methods. Leveraging cloud computing, this system facilitates real-time coordination for diagnosisandtreatment.UsingDenseNet-121andResNet-34, the study outperformed other algorithms in identifying leukemia subtypes. Loey et al. [10] proposed two automated leukemia classification models using transfer learning for early detection. The first model preprocesses images and employs a pre-traineddeepconvolutionalneuralnetwork,AlexNet,for feature extraction and classification. In the second model, AlexNet is fine-tuned for improved performance. Experiments on 2820 images demonstrated that the second model achieved a remarkable 100% classification accuracy, surpassing the first model. 3. PROPOSED SYSTEM Model is designed to automate leukemia classification using microscopic images. This system leverages deep learning and transfer learning techniques to enhance accuracy and efficiency. 3.1 DATASET COLLECTION The implementation of the proposed model begins by loading the dataset. The dataset used for this model is available publicly on Kaggle. The dataset contains 3256 images classified as healthy, Early Pre-B, Pre-B and Pro-B. There are 504 healthy, 985 Early Pre-B, 963 Pre-B and 804 Pro-B. It is split into training validation and testing in the ratio 80:10:10. 3.2 DATA PREPROCESSING The preprocessing techniques used in the code involve resizing and rescaling images to a target size of 256x256 pixels and normalizing their pixel values to a range between 0 and 1. Additionally, data augmentation methods such as random flips and rotations are applied to increase the diversity of the training dataset. Cachingandprefetching are utilized to improve data loading efficiency during training, ensuring optimal performance of the deep learning model. 3.3 TRANSFER LEARNING Model utilizes MobileNetV2, a pre-trained deep convolutional neural network, as the feature extractor. This model, trained on a large and diverse dataset, offers a valuable starting point for leukemia classification. By extracting high-level features from images, MobileNetV2 provides valuable insights into image content. 3.4 MODEL ARCHITECTURE The system builds on MobileNetV2 withadditional layersfor classification. These layers include a Global Average Pooling 2D layer to reduce dimensionality, a Dropout layer to prevent overfitting, and fully connected Dense layers. The final Dense layer has a softmax activation function to output class probabilities.
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 10 | Oct 2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 878 3.5 TRAINING AND EVALUATION Model is trained using the preprocessed training dataset with a batch size of 32 for 30 epochs. The training process is monitored for accuracyandloss.Themodel'sperformanceis evaluated using a separate test dataset. 3.6 METRICS AND VISUALIZATION: The system provides insights into the model's performance by calculating metrics such as accuracy and loss. These metrics offer a quantitative measure of the model's classification capabilities. Additionally,thesystemgenerates visualizations, including accuracy and loss curves over the training epochs. 4. RESULTS AND ANALYSIS Chart -1: Training and Validation accuracyandloss It was observed that the proposed neural network model achieved an accuracy of98.87%ontrainingdata and98.58% on testing data. The loss reduced from 0.1874 to0.0443.The highest value of accuracy was achieved at 18th epoch. Table -1: Output for proposed model w.r.t intermediate epochs Epoch Loss Accuracy% 1 0.1874 93.18 15 0.0645 97.73 30 0.0443 98.58 Fig -1: Actual vs Predicted Figure 1 shows predictions of few of the randomly selected images from dataset. 5. CONCLUSION In this study, a deep learning model based on MobileNetV2 demonstrated impressive accuracy (98.58%) in classifying acute lymphoblastic leukemia (ALL) from microscopic images. It boasted high precision and recall (both above 98%) and a strong F1 score (0.986). The model was trained on a diverse dataset of 3256 images, encompassingdifferent ALL stages and healthy samples. The utilization of transfer learning with MobileNetV2 enhanced its classification capabilities. This research offers significant potential for early ALL detection, providing a valuable tool for medical professionals and the possibility of improving patient outcomes, while further refinements could advance its clinical utility. 6. FUTURE WORK In the future, the dataset canbeextendedbyaddingnew samples and utilizing new augmentation techniques. A variety of deep learning models can be applied to improve accuracy. Various feature extraction techniques could be used. REFERENCES [1] N. Jiwani, K. Gupta, G. Pau and M. Alibakhshikenari, "Pattern Recognition of Acute Lymphoblastic Leukemia (ALL) Using Computational Deep Learning," in IEEE
4.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 10 | Oct 2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 879 Access, vol. 11, pp. 29541-29553, 2023, doi: 10.1109/ACCESS.2023.3260065. [2] A. Batool and Y. -C. Byun, "Lightweight EfficientNetB3 Model Based on Depthwise Separable Convolutions for Enhancing Classification of Leukemia White Blood Cell Images," in IEEE Access, vol. 11, pp.37203-37215,2023, doi: 10.1109/ACCESS.2023.3266511. [3] M. A. Hossain, A. K. M. M. Islam, S. Islam, S. Shatabda and A. Ahmed, "Symptom Based Explainable Artificial Intelligence Model for Leukemia Detection," in IEEE Access, vol. 10, pp. 57283-57298, 2022, doi: 10.1109/ACCESS.2022.3176274. [4] N. Akram et al., "Exploiting the Multiscale Information Fusion Capabilities for Aiding the Leukemia Diagnosis Through White Blood Cells Segmentation," in IEEE Access, vol. 10, pp. 48747-48760, 2022, doi: 10.1109/ACCESS.2022.3171916. [5] Atteia, G.; Alhussan, A.A.; Samee, N.A. BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images. Sensors 2022, 22, 5520. https://doi.org/10.3390/s22155520. [6] Chen, YM., Chou, FI., Ho, WH. et al. Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method. BMC Bioinformatics 22 (Suppl 5), 615 (2021). https://doi.org/10.1186/s12859-022-04558-5 [7] Houssein EH, Mohamed O, Abdel Samee N, Mahmoud NF, Talaat R, Al-Hejri AM, Al-Tam RM. Using deep DenseNet with cyclical learning rate to classify leukocytes for leukemia identification. Front Oncol. 2023 Sep 12;13:1230434. doi: 10.3389/fonc.2023.1230434.PMID:37771437;PMCID: PMC10523295. [8] Kruse A, Abdel-Azim N, Kim HN, Ruan Y, Phan V, Ogana H, Wang W, Lee R, Gang EJ, Khazal S, Kim YM. Minimal Residual Disease Detection in Acute Lymphoblastic Leukemia. Int J Mol Sci. 2020 Feb 5;21(3):1054. doi: 10.3390/ijms21031054. PMID: 32033444; PMCID: PMC7037356. [9] Bibi N, Sikandar M, Ud Din I, Almogren A, Ali S. IoMT- Based Automated Detection and Classification of Leukemia Using Deep Learning. J Healthc Eng. 2020 Dec 3;2020:6648574. doi: 10.1155/2020/6648574. PMID: 33343851; PMCID: PMC7732373. [10] Loey, M.; Naman, M.; Zayed, H. Deep Transfer Learning in Diagnosing Leukemia in Blood Cells. Computers 2020, 9, 29. https://doi.org/10.3390/computers9020029 BIOGRAPHIES Lagisetty Naga Pavithra is a student at Bangalore Institute of Technology, Bengaluru,Karnataka, India pursuing Computer Science and Engineering.
Download now