This document discusses techniques for early detection of breast cancer through image processing of mammograms. It begins by introducing breast cancer and the importance of early detection. It then discusses current mammography screening approaches, including the two standard views and BI-RADS assessment system. The key abnormalities that may indicate breast cancer are described: masses with characteristics like shape, margin, density; calcifications described by size, shape and clustering; architectural distortion; and asymmetries. Current challenges are noted around detecting calcifications and masses in dense breast tissue. The paper aims to review techniques used in image processing for early breast cancer detection, including preprocessing, segmentation, and decomposition steps typically used.
A Review of Segmentation of Mammographic Images Based on Breast DensityIJERA Editor
1) The document reviews approaches for segmenting breast regions in mammograms according to breast density. Breast density is an important risk factor for breast cancer.
2) Segmentation of mammographic images can identify glandular and fibroglandular tissues, which appear bright on mammograms. This segmentation is the first step in computer-aided detection and diagnosis of breast cancer.
3) Several approaches have been used for segmentation, including statistical methods based on Gaussian mixture modeling, thresholding techniques, and classification of breast density into categories like the BI-RADS system. Segmentation of specific breast regions like the pectoral muscle have also been studied.
This document compares calcification specificity in digital mammography using soft-copy display versus screen-film mammography. Breast cancer is the most common cancer in women. Digital mammography offers advantages over screen-film mammography like enhanced resolution and contrast. The study aims to compare the specificity of detecting microcalcifications, which can indicate early breast cancer, between the two imaging methods. Sixty female patients undergoing mammography were divided into groups for either screen-film or soft-copy digital mammography. Patient data and mammogram images were analyzed using statistical and imaging software to compare detection of microcalcifications between the methods.
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...breastcancerupdatecongress
This document discusses the use of breast MRI in evaluating response to neoadjuvant chemotherapy. MRI can provide both morphological and functional information about tumors. Studies show DCE-MRI and DWI-MRI may help assess response after 1-2 cycles of chemotherapy, with changes in tumor size, kinetic parameters and ADC values predicting pathological complete or near-complete response. Larger prospective trials are still needed to standardize MRI methods and thresholds to determine if changes on MRI could guide modifications to chemotherapy regimens for non-responders. Overall, MRI shows potential as a predictive marker and non-invasive method for monitoring early response to neoadjuvant breast cancer treatment.
Shared Decision Making, Decision Support and Breast Conservation TherapyMatthew Katz
Shared Decision Making, Decision Support and Breast Conservation Therapy explores how breast cancer patients interpret decisions around making decisions about mastectomy vs. lumpectomy.
Spindle cell lesions of the breast diagnostic issues 2019 (1)Alejandro Palacio
This document discusses diagnostic issues with spindle cell lesions of the breast. It proposes a two-step approach for classification and diagnosis. The first step is to determine if the lesion contains both spindle and epithelial components (biphasic) or only spindle cells (monophasic). Biphasic lesions are then graded based on the appearance of the spindle cells. Common biphasic lesions with bland spindle cells include fibroadenoma, benign phyllodes tumor, and pseudoangiomatous stromal hyperplasia (PASH). Accurate diagnosis is important as treatment and prognosis varies between entities. Immunohistochemistry and molecular analysis can aid in distinguishing between lesions.
This summarizes a study that investigated using bilateral asymmetry analysis of breast MR images to detect breast diseases. The study used directional statistics of breast parenchymal edges and texture analysis to characterize differences between left and right breast images. On a dataset of 40 MR scans (20 normal, 20 malignant), the method achieved an average classification accuracy of 70% at detecting cancer, with sensitivity of 75% and specificity of 65%. The results support that bilateral asymmetry analysis of MR images can provide additional information for breast disease detection.
Primary osteosarcoma of the breast a case reportpharmaindexing
1. A 45-year-old woman presented with a lump in her right breast that was diagnosed as carcinoma based on clinical examination. Histological examination of an excisional biopsy found the mass to be an osteogenic sarcoma comprising osteoblastic and chondroblastic stromal cells, changing the diagnosis.
2. Further lumpectomy confirmed the diagnosis of primary osteosarcoma of the breast. Osteosarcomas of the breast are very rare, representing less than 1% of breast cancers.
3. This case report describes a rare instance of primary osteosarcoma arising within the breast tissue itself, rather than from underlying bone structures, based on surgical and pathological findings that excluded
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...CSCJournals
Breast cancer patients with the same diagnostic and clinical prognostic profile can have markedly different clinical outcome. This difference is possibly caused by the limitation of current breast cancer prognostic indices, which group molecularly distinct patients into similar clinical classes based mainly on morphological of disease. Traditional clinical based prognosis models were discovered contain some restriction to address the heterogeneity of breast cancer. The invention of microarray technology and its ability to simultaneously interrogate thousands genes has changed the paradigm of molecular classification of human cancers as well as it shifted clinical prognosis model to broader prospect. Numerous studies have revealed the potential value of gene expression signatures in examining the risk of disease recurrence. However, currently most of these studies attempted to implement genetic marker based prognostic models to replace the traditional clinical markers, yet neglecting the rich information contain in clinical information. Therefore, this research took an effort to integrate both clinical and microarray data in order to obtain accurate breast cancer prognosis, by taking into account that these data complements each other. This article presents a review of the development of breast cancer prognosis models, concentrating precisely on clinical and gene expression profiles. The literature is reviewed in an explicit machine learning framework, which include the elements of feature selection and classification techniques.
A Review of Segmentation of Mammographic Images Based on Breast DensityIJERA Editor
1) The document reviews approaches for segmenting breast regions in mammograms according to breast density. Breast density is an important risk factor for breast cancer.
2) Segmentation of mammographic images can identify glandular and fibroglandular tissues, which appear bright on mammograms. This segmentation is the first step in computer-aided detection and diagnosis of breast cancer.
3) Several approaches have been used for segmentation, including statistical methods based on Gaussian mixture modeling, thresholding techniques, and classification of breast density into categories like the BI-RADS system. Segmentation of specific breast regions like the pectoral muscle have also been studied.
This document compares calcification specificity in digital mammography using soft-copy display versus screen-film mammography. Breast cancer is the most common cancer in women. Digital mammography offers advantages over screen-film mammography like enhanced resolution and contrast. The study aims to compare the specificity of detecting microcalcifications, which can indicate early breast cancer, between the two imaging methods. Sixty female patients undergoing mammography were divided into groups for either screen-film or soft-copy digital mammography. Patient data and mammogram images were analyzed using statistical and imaging software to compare detection of microcalcifications between the methods.
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...breastcancerupdatecongress
This document discusses the use of breast MRI in evaluating response to neoadjuvant chemotherapy. MRI can provide both morphological and functional information about tumors. Studies show DCE-MRI and DWI-MRI may help assess response after 1-2 cycles of chemotherapy, with changes in tumor size, kinetic parameters and ADC values predicting pathological complete or near-complete response. Larger prospective trials are still needed to standardize MRI methods and thresholds to determine if changes on MRI could guide modifications to chemotherapy regimens for non-responders. Overall, MRI shows potential as a predictive marker and non-invasive method for monitoring early response to neoadjuvant breast cancer treatment.
Shared Decision Making, Decision Support and Breast Conservation TherapyMatthew Katz
Shared Decision Making, Decision Support and Breast Conservation Therapy explores how breast cancer patients interpret decisions around making decisions about mastectomy vs. lumpectomy.
Spindle cell lesions of the breast diagnostic issues 2019 (1)Alejandro Palacio
This document discusses diagnostic issues with spindle cell lesions of the breast. It proposes a two-step approach for classification and diagnosis. The first step is to determine if the lesion contains both spindle and epithelial components (biphasic) or only spindle cells (monophasic). Biphasic lesions are then graded based on the appearance of the spindle cells. Common biphasic lesions with bland spindle cells include fibroadenoma, benign phyllodes tumor, and pseudoangiomatous stromal hyperplasia (PASH). Accurate diagnosis is important as treatment and prognosis varies between entities. Immunohistochemistry and molecular analysis can aid in distinguishing between lesions.
This summarizes a study that investigated using bilateral asymmetry analysis of breast MR images to detect breast diseases. The study used directional statistics of breast parenchymal edges and texture analysis to characterize differences between left and right breast images. On a dataset of 40 MR scans (20 normal, 20 malignant), the method achieved an average classification accuracy of 70% at detecting cancer, with sensitivity of 75% and specificity of 65%. The results support that bilateral asymmetry analysis of MR images can provide additional information for breast disease detection.
Primary osteosarcoma of the breast a case reportpharmaindexing
1. A 45-year-old woman presented with a lump in her right breast that was diagnosed as carcinoma based on clinical examination. Histological examination of an excisional biopsy found the mass to be an osteogenic sarcoma comprising osteoblastic and chondroblastic stromal cells, changing the diagnosis.
2. Further lumpectomy confirmed the diagnosis of primary osteosarcoma of the breast. Osteosarcomas of the breast are very rare, representing less than 1% of breast cancers.
3. This case report describes a rare instance of primary osteosarcoma arising within the breast tissue itself, rather than from underlying bone structures, based on surgical and pathological findings that excluded
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...CSCJournals
Breast cancer patients with the same diagnostic and clinical prognostic profile can have markedly different clinical outcome. This difference is possibly caused by the limitation of current breast cancer prognostic indices, which group molecularly distinct patients into similar clinical classes based mainly on morphological of disease. Traditional clinical based prognosis models were discovered contain some restriction to address the heterogeneity of breast cancer. The invention of microarray technology and its ability to simultaneously interrogate thousands genes has changed the paradigm of molecular classification of human cancers as well as it shifted clinical prognosis model to broader prospect. Numerous studies have revealed the potential value of gene expression signatures in examining the risk of disease recurrence. However, currently most of these studies attempted to implement genetic marker based prognostic models to replace the traditional clinical markers, yet neglecting the rich information contain in clinical information. Therefore, this research took an effort to integrate both clinical and microarray data in order to obtain accurate breast cancer prognosis, by taking into account that these data complements each other. This article presents a review of the development of breast cancer prognosis models, concentrating precisely on clinical and gene expression profiles. The literature is reviewed in an explicit machine learning framework, which include the elements of feature selection and classification techniques.
Comparison between mammogram and mri in detecting breast cancernordin1808
MRI mammography is more accurate than mammography in detecting breast diseases. A study compared MRI and mammography on 15 patients and found MRI detected 12 cases of ductal carcinoma in situ (DCIS) in the right breast that mammography missed, as well as 10 cases of DCIS in the left breast. MRI mammography had a sensitivity of 100% while mammography's sensitivity was only 18% for detecting breast cancer. MRI is better able to detect cancers obscured by dense breast tissue and can provide additional information on tumor extent.
This study evaluated the sensitivity of breast MRI for detecting breast cancers. Of 222 cancers, MRI correctly identified 213 but missed 9 cancers (sensitivity of 96.8%). The 7 true false-negatives included 4 DCIS lesions and 3 invasive cancers. False-negative lesions were often small or obscured by surrounding enhancing breast tissue. While MRI is highly sensitive for breast cancer, a small percentage of cancers can be missed, particularly DCIS and cancers in a background of diffuse parenchymal enhancement.
Caren Stalburg, MD, MA presented to the 2016 annual Snow meeting of the Michigan Section of the American Congress of Obstetricians and Gynecologists (ACOG) about her program to train Michigan providers about the new Breast Density Notification Law (http://www.midensebreasts.org/).
Dr. Stalburg is Division Chief and Clinical Assistant Professor in the Division of Professional Education in the Department of Learning Health Sciences and Assistant Professor of Obstetrics and Gynecology in the University of Michigan Medical School.
This document discusses breast imaging recommendations and tools. It recommends annual mammography screening starting at age 40 for average risk women, while high risk women may benefit from additional screening with MRI. Digital mammography is the gold standard but has limitations depending on breast density. New tools like tomosynthesis and ultrasound can help address these limitations and provide additional information. The document reviews various breast imaging tools and their uses, as well as risk factors, screening guidelines, and case examples.
MRI can detect breast lesions with high sensitivity but has variable specificity in differentiating benign from malignant lesions. MR spectroscopy provides additional metabolic information that can improve specificity by detecting elevated choline levels associated with malignant tumors. Response to chemotherapy can also be assessed non-invasively with MR spectroscopy by monitoring changes in choline levels within 24 hours of treatment. Limitations include difficulty with small lesions, dense breasts, and lactating breasts.
1) Breast MRI is useful for screening and surveillance in women with high genetic risk of breast cancer, such as those with BRCA1/BRCA2 mutations. MRI can identify cancers earlier than mammography due to certain features of hereditary breast cancers.
2) For lesions found on MRI, further workup with targeted ultrasound and biopsy is recommended. If no lesion is found on ultrasound, short-term MRI follow up or MRI-guided biopsy may be needed given the increased risk in this patient population.
3) Annual breast MRI, ultrasound and mammography (when applicable) is important for surveillance in high risk women due to the possibility of interval cancers developing between screenings. Following standardized imaging protocols and recommendations
This document provides information on breast cancer screening and prevention. It discusses screening principles and guidelines for mammography, MRI, ultrasound and other screening techniques. It outlines high-risk factors for breast cancer and recommends annual screening starting at age 30-40 for high-risk individuals, including those with BRCA gene mutations or family history. Screening mammography every 1-2 years is recommended for average risk women starting at age 40. Chemoprevention with tamoxifen or raloxifene can lower breast cancer risk in high risk postmenopausal women. Genetic testing guidelines are also provided.
Breast cancer is a common and serious form of cancer that affects millions of women globally each year. It starts in the breast tissue and can spread to other parts of the body if not detected early. Some key risk factors include gender, age, family history and lifestyle factors. Symptoms may include a breast lump, skin changes, nipple discharge or inversion. Diagnosis involves examinations, mammography, ultrasound and biopsy. Cancer is staged according to tumor size and spread. Treatment options include surgery to remove all or part of the breast, chemotherapy, radiation therapy, hormone therapy and targeted drug therapies. The goal is cure, remission or palliation depending on the stage and type of cancer.
- Kettering General Hospital Breast Unit went digital between 2010-2012 and implemented tomosynthesis and contrast-enhanced spectral mammography (CESM) to improve cancer detection for women with dense breasts.
- A review of 50 patients who received tomosynthesis found it aided diagnosis in 36 patients (69%), providing extra information in 22 patients and more detailed information in 7 patients.
- A prospective study of 117 CESM exams found it to be as sensitive as MRI in detecting cancer and impacted management for 30% of cancer patients. CESM provided accurate sizing for invasive cancers but was less accurate for lobular cancers and cancers with ductal carcinoma in situ.
This document discusses the evolution of breast cancer surgery from radical mastectomy to breast-conserving surgery (BCS). It provides an overview of the key factors to consider when determining eligibility for BCS, including tumor characteristics, family history, genetic factors, and patient age/health status. Multiple studies have shown that BCS followed by radiation therapy provides equivalent survival outcomes to mastectomy for appropriately selected early-stage patients. Surgical challenges include achieving negative margins, maintaining cosmesis, and detecting local recurrence after BCS. Patient selection factors and techniques to help guide BCS are discussed.
This document summarizes the role of MRI in diagnosing various types of uterine sarcomas. It discusses the main subtypes of uterine sarcoma - carcinosarcoma, endometrial stromal sarcoma, and leiomyosarcoma. It provides details on the characteristics, risk factors, MRI appearance and diagnostic criteria for each subtype. Carcinosarcomas account for about 50% of uterine sarcomas and have heterogeneous enhancement. Endometrial stromal sarcomas appear as polypoid masses on MRI. Leiomyosarcomas usually have an irregular, ill-defined appearance on MRI and can cause uterine enlargement.
Thermal Imaging: Opportunities and Challenges for Breast Cancer DetectionTarek Gaber
Thermal Imaging: Opportunities and Challenges for Breast Cancer Detection
Abstract:
Breast cancer is the most common cancer among women in the world. It is estimated that one in eight women, all over the wide, would develop breast cancer during her life. Breast cancer is considered one of the first-leading causes of cancer deaths among women. The early detection of breast cancer could save many women's life. Mammogram is one of the most imaging technology used for diagnosing breast cancer. Although mammogram has recorded a high detection and classification accuracy, it is difficult in imaging dense breast tissues, its performance is poor in younger women, it is harmful, and it couldn’t detect breast tumor that less than 2 mm. To overcome these limitations, it was found that there is a relation between the temperature and the presence of breast cancer. Utilizing this fact, infrared thermography could be a good source of breast images to study and detect cancer at the early stages which is crucial for cancer patients for increasing the rate of breast cancer survival.
This talk aims to give an overview of the thermal imaging technology, its possible applications in the medical field, focusing on its opportunities and challenges for the early detection of breast cancer and highlighting the state-of-the-art of this point.
This document summarizes updates made to the BI-RADS MRI lexicon in its third edition. It describes new features for characterizing breast lesions on MRI, including background parenchymal enhancement categories, mass shape and margin descriptions, and distributions for non-mass enhancements. Kinetic enhancement curves are also discussed. The importance of the revised lexicon is to standardize MRI reporting and improve assessment of lesions, with certain characteristics like irregular masses or clustered ring non-mass enhancements having a higher positive predictive value for malignancy.
Breast MRI has poor specificity but can provide useful information when used appropriately according to evidence-based guidelines. It has high sensitivity for detecting breast cancer but many benign lesions also enhance, leading to false positives. MRI is best used to further evaluate lesions already detected by other imaging when biopsy is not possible, to screen high-risk patients, and assess response to neoadjuvant chemotherapy or detect recurrence. Strict technical protocols and reporting standards help optimize MRI's clinical utility while minimizing unnecessary additional procedures due to false positives.
Mammography is an x-ray test used to aid in the early detection and diagnosis of breast diseases in women. It uses low-dose radiation to produce images of the breast tissue. Screening mammograms are used to look for signs of breast cancer in women without symptoms, while diagnostic mammograms are used when abnormalities are detected or a woman has breast symptoms. Mammograms produce images of the breast tissue and can detect abnormalities such as masses, calcifications, architectural distortions, and asymmetries that may indicate breast cancer. The images are analyzed according to the Breast Imaging Reporting and Data System (BI-RADS) to determine if follow-up is needed. Digital mammography provides enhanced image quality compared to traditional film
This case report describes a rare case of a 63-year-old woman who presented with a breast lump 30 months after surgery for rectal adenocarcinoma. Tests revealed the breast lump was a metastasis from the original rectal cancer. Immunohistochemical staining of the breast tissue was positive for cytokeratin 20 and CEA, matching the staining pattern of the original rectal tumor. The patient had disseminated metastatic disease and was treated with palliative chemotherapy, unfortunately deteriorating and dying 4 months later. Rectal cancer metastasizing to the breast is very rare and usually indicates widespread metastases with a poor prognosis.
1) The document discusses the use of computer-aided detection (CAD) systems in mammography to help radiologists detect breast cancer.
2) An observer study found that radiologists' cancer detection performance improved when they interactively reviewed CAD marks compared to unaided reading.
3) Non-radiologists saw more benefit from interactive CAD than experienced radiologists. The study suggests CAD could help less experienced mammogram readers.
This document analyzes and compares maintainability metrics for aspect-oriented software (AOS) and object-oriented software (OOS) using five projects. It discusses metrics like number of children, depth of inheritance tree, lack of cohesion of methods, weighted methods per class, and lines of code. The results show that for most metrics like NOC, DIT, LCOM, and WMC, the mean values are higher for OOS compared to AOS, indicating that AOS is generally more maintainable based on these metrics. LOC is also lower on average for AOS. The study concludes that an AOP version is more maintainable than an OOP version according to the chosen metrics.
Comparison between mammogram and mri in detecting breast cancernordin1808
MRI mammography is more accurate than mammography in detecting breast diseases. A study compared MRI and mammography on 15 patients and found MRI detected 12 cases of ductal carcinoma in situ (DCIS) in the right breast that mammography missed, as well as 10 cases of DCIS in the left breast. MRI mammography had a sensitivity of 100% while mammography's sensitivity was only 18% for detecting breast cancer. MRI is better able to detect cancers obscured by dense breast tissue and can provide additional information on tumor extent.
This study evaluated the sensitivity of breast MRI for detecting breast cancers. Of 222 cancers, MRI correctly identified 213 but missed 9 cancers (sensitivity of 96.8%). The 7 true false-negatives included 4 DCIS lesions and 3 invasive cancers. False-negative lesions were often small or obscured by surrounding enhancing breast tissue. While MRI is highly sensitive for breast cancer, a small percentage of cancers can be missed, particularly DCIS and cancers in a background of diffuse parenchymal enhancement.
Caren Stalburg, MD, MA presented to the 2016 annual Snow meeting of the Michigan Section of the American Congress of Obstetricians and Gynecologists (ACOG) about her program to train Michigan providers about the new Breast Density Notification Law (http://www.midensebreasts.org/).
Dr. Stalburg is Division Chief and Clinical Assistant Professor in the Division of Professional Education in the Department of Learning Health Sciences and Assistant Professor of Obstetrics and Gynecology in the University of Michigan Medical School.
This document discusses breast imaging recommendations and tools. It recommends annual mammography screening starting at age 40 for average risk women, while high risk women may benefit from additional screening with MRI. Digital mammography is the gold standard but has limitations depending on breast density. New tools like tomosynthesis and ultrasound can help address these limitations and provide additional information. The document reviews various breast imaging tools and their uses, as well as risk factors, screening guidelines, and case examples.
MRI can detect breast lesions with high sensitivity but has variable specificity in differentiating benign from malignant lesions. MR spectroscopy provides additional metabolic information that can improve specificity by detecting elevated choline levels associated with malignant tumors. Response to chemotherapy can also be assessed non-invasively with MR spectroscopy by monitoring changes in choline levels within 24 hours of treatment. Limitations include difficulty with small lesions, dense breasts, and lactating breasts.
1) Breast MRI is useful for screening and surveillance in women with high genetic risk of breast cancer, such as those with BRCA1/BRCA2 mutations. MRI can identify cancers earlier than mammography due to certain features of hereditary breast cancers.
2) For lesions found on MRI, further workup with targeted ultrasound and biopsy is recommended. If no lesion is found on ultrasound, short-term MRI follow up or MRI-guided biopsy may be needed given the increased risk in this patient population.
3) Annual breast MRI, ultrasound and mammography (when applicable) is important for surveillance in high risk women due to the possibility of interval cancers developing between screenings. Following standardized imaging protocols and recommendations
This document provides information on breast cancer screening and prevention. It discusses screening principles and guidelines for mammography, MRI, ultrasound and other screening techniques. It outlines high-risk factors for breast cancer and recommends annual screening starting at age 30-40 for high-risk individuals, including those with BRCA gene mutations or family history. Screening mammography every 1-2 years is recommended for average risk women starting at age 40. Chemoprevention with tamoxifen or raloxifene can lower breast cancer risk in high risk postmenopausal women. Genetic testing guidelines are also provided.
Breast cancer is a common and serious form of cancer that affects millions of women globally each year. It starts in the breast tissue and can spread to other parts of the body if not detected early. Some key risk factors include gender, age, family history and lifestyle factors. Symptoms may include a breast lump, skin changes, nipple discharge or inversion. Diagnosis involves examinations, mammography, ultrasound and biopsy. Cancer is staged according to tumor size and spread. Treatment options include surgery to remove all or part of the breast, chemotherapy, radiation therapy, hormone therapy and targeted drug therapies. The goal is cure, remission or palliation depending on the stage and type of cancer.
- Kettering General Hospital Breast Unit went digital between 2010-2012 and implemented tomosynthesis and contrast-enhanced spectral mammography (CESM) to improve cancer detection for women with dense breasts.
- A review of 50 patients who received tomosynthesis found it aided diagnosis in 36 patients (69%), providing extra information in 22 patients and more detailed information in 7 patients.
- A prospective study of 117 CESM exams found it to be as sensitive as MRI in detecting cancer and impacted management for 30% of cancer patients. CESM provided accurate sizing for invasive cancers but was less accurate for lobular cancers and cancers with ductal carcinoma in situ.
This document discusses the evolution of breast cancer surgery from radical mastectomy to breast-conserving surgery (BCS). It provides an overview of the key factors to consider when determining eligibility for BCS, including tumor characteristics, family history, genetic factors, and patient age/health status. Multiple studies have shown that BCS followed by radiation therapy provides equivalent survival outcomes to mastectomy for appropriately selected early-stage patients. Surgical challenges include achieving negative margins, maintaining cosmesis, and detecting local recurrence after BCS. Patient selection factors and techniques to help guide BCS are discussed.
This document summarizes the role of MRI in diagnosing various types of uterine sarcomas. It discusses the main subtypes of uterine sarcoma - carcinosarcoma, endometrial stromal sarcoma, and leiomyosarcoma. It provides details on the characteristics, risk factors, MRI appearance and diagnostic criteria for each subtype. Carcinosarcomas account for about 50% of uterine sarcomas and have heterogeneous enhancement. Endometrial stromal sarcomas appear as polypoid masses on MRI. Leiomyosarcomas usually have an irregular, ill-defined appearance on MRI and can cause uterine enlargement.
Thermal Imaging: Opportunities and Challenges for Breast Cancer DetectionTarek Gaber
Thermal Imaging: Opportunities and Challenges for Breast Cancer Detection
Abstract:
Breast cancer is the most common cancer among women in the world. It is estimated that one in eight women, all over the wide, would develop breast cancer during her life. Breast cancer is considered one of the first-leading causes of cancer deaths among women. The early detection of breast cancer could save many women's life. Mammogram is one of the most imaging technology used for diagnosing breast cancer. Although mammogram has recorded a high detection and classification accuracy, it is difficult in imaging dense breast tissues, its performance is poor in younger women, it is harmful, and it couldn’t detect breast tumor that less than 2 mm. To overcome these limitations, it was found that there is a relation between the temperature and the presence of breast cancer. Utilizing this fact, infrared thermography could be a good source of breast images to study and detect cancer at the early stages which is crucial for cancer patients for increasing the rate of breast cancer survival.
This talk aims to give an overview of the thermal imaging technology, its possible applications in the medical field, focusing on its opportunities and challenges for the early detection of breast cancer and highlighting the state-of-the-art of this point.
This document summarizes updates made to the BI-RADS MRI lexicon in its third edition. It describes new features for characterizing breast lesions on MRI, including background parenchymal enhancement categories, mass shape and margin descriptions, and distributions for non-mass enhancements. Kinetic enhancement curves are also discussed. The importance of the revised lexicon is to standardize MRI reporting and improve assessment of lesions, with certain characteristics like irregular masses or clustered ring non-mass enhancements having a higher positive predictive value for malignancy.
Breast MRI has poor specificity but can provide useful information when used appropriately according to evidence-based guidelines. It has high sensitivity for detecting breast cancer but many benign lesions also enhance, leading to false positives. MRI is best used to further evaluate lesions already detected by other imaging when biopsy is not possible, to screen high-risk patients, and assess response to neoadjuvant chemotherapy or detect recurrence. Strict technical protocols and reporting standards help optimize MRI's clinical utility while minimizing unnecessary additional procedures due to false positives.
Mammography is an x-ray test used to aid in the early detection and diagnosis of breast diseases in women. It uses low-dose radiation to produce images of the breast tissue. Screening mammograms are used to look for signs of breast cancer in women without symptoms, while diagnostic mammograms are used when abnormalities are detected or a woman has breast symptoms. Mammograms produce images of the breast tissue and can detect abnormalities such as masses, calcifications, architectural distortions, and asymmetries that may indicate breast cancer. The images are analyzed according to the Breast Imaging Reporting and Data System (BI-RADS) to determine if follow-up is needed. Digital mammography provides enhanced image quality compared to traditional film
This case report describes a rare case of a 63-year-old woman who presented with a breast lump 30 months after surgery for rectal adenocarcinoma. Tests revealed the breast lump was a metastasis from the original rectal cancer. Immunohistochemical staining of the breast tissue was positive for cytokeratin 20 and CEA, matching the staining pattern of the original rectal tumor. The patient had disseminated metastatic disease and was treated with palliative chemotherapy, unfortunately deteriorating and dying 4 months later. Rectal cancer metastasizing to the breast is very rare and usually indicates widespread metastases with a poor prognosis.
1) The document discusses the use of computer-aided detection (CAD) systems in mammography to help radiologists detect breast cancer.
2) An observer study found that radiologists' cancer detection performance improved when they interactively reviewed CAD marks compared to unaided reading.
3) Non-radiologists saw more benefit from interactive CAD than experienced radiologists. The study suggests CAD could help less experienced mammogram readers.
This document analyzes and compares maintainability metrics for aspect-oriented software (AOS) and object-oriented software (OOS) using five projects. It discusses metrics like number of children, depth of inheritance tree, lack of cohesion of methods, weighted methods per class, and lines of code. The results show that for most metrics like NOC, DIT, LCOM, and WMC, the mean values are higher for OOS compared to AOS, indicating that AOS is generally more maintainable based on these metrics. LOC is also lower on average for AOS. The study concludes that an AOP version is more maintainable than an OOP version according to the chosen metrics.
This case study examines quality improvement efforts at Caparo Maruti Ltd through the application of Six Sigma methodology. The company manufactures sheet metal automobile parts, including cross members. Data was collected on inspections of 187525 cross member parts over 5 months, finding 67 defects. Major defects included welding failures causing nut misplacement or damage. Pareto and line charts identified the primary defect as M8 nut failure during projection welding. Root cause analysis using a fishbone diagram indicated issues with the welding process, including variation in weld gun position, nut placement, and material quality. Recommendations were made to improve the welding process and reduce defects.
This document discusses the basic tasks involved in natural language processing (NLP). It describes the different phases of NLP including phonetics, lexical analysis, syntactic analysis, semantic analysis, discourse analysis, and pragmatic analysis. It then explains some basic NLP activities like tokenization, sentence splitting, and part-of-speech tagging. The goal of NLP is to enable computers to understand and process human languages through computational modeling.
This document presents three mixed quadrature rules of precision seven and three mixed quadrature rules of precision nine for numerically evaluating definite integrals. The rules are formulated by combining Gauss-Legendre, Gauss-Labatto, and Weddle's quadrature rules. Analytical expressions for the asymptotic error bounds of the seven degree rules are derived. It is shown that the errors converge to zero faster than any power of the independent variable as it approaches the boundary of the domain. The mixed rules are found to achieve higher precision than the basic rules and compound forms for numerical integration of test functions.
This document discusses a study of the vegetative trichomes of Petrea volubilis L., a perennial liana. It finds that trichomes on vegetative parts come in two types - non-glandular and glandular. Non-glandular trichomes vary from unicellular to multicellular and differ in details between plant parts. Glandular trichomes are capitate and stalked. Trichomes provide useful taxonomic information and suggest functional roles like transpiration control and protection. The epidermal surface is papillate across organs. Trichomes are diagnostic for P. volubilis and their study provides insights into structure, development and classification of trichomes.
- The document examines the awareness level and investment behavior of salaried individuals towards financial products in India.
- It finds that respondents have high awareness of traditional financial products like bank deposits and life insurance, but low awareness of newer products like mutual funds, stocks, and forex markets.
- In terms of investment behavior, the majority of respondents invest their money in traditional and safe options like bank deposits and life insurance. Few invest in riskier assets like stocks or commodities.
This document discusses techniques for classifying sentiments and mining opinions from text data. It begins with defining key terminology in opinion mining like opinion feature, sentiment, polarity, holder and time. It then discusses various data sources for opinion mining like blogs, reviews sites, datasets, microblogs and other text. It describes the granularity of opinion mining tasks at the document level, sentence level and feature level. Finally, it outlines approaches to opinion mining including supervised learning techniques like Naive Bayes, SVM and unsupervised learning techniques that use lexical resources without prior training. Evaluation metrics for sentiment classification systems like accuracy, precision, recall and F1 measure are also discussed.
Applying Deep Learning to Transform Breast Cancer DiagnosisCognizant
Deep convolutional neural networks can assist pathologists in breast cancer diagnosis by automatically filtering benign tissue biopsies, identifying malignant regions and labeling important cellular features like nuclei for further analysis. Automatic detection of diagnostically relevant regions-of-interest and nuclei segmentation reduces the pathologist’s workload, while ensuring that no critical region is overlooked, rendering breast cancer diagnosis more reliable, efficient and cost-effective.
Image processing and machine learning techniques used in computer-aided dete...IJECEIAES
This paper aims to review the previously developed Computer-aided detection (CAD) systems for mammogram screening because increasing death rate in women due to breast cancer is a global medical issue and it can be controlled only by early detection with regular screening. Till now mammography is the widely used breast imaging modality. CAD systems have been adopted by the radiologists to increase the accuracy of the breast cancer diagnosis by avoiding human errors and experience related issues. This study reveals that in spite of the higher accuracy obtained by the earlier proposed CAD systems for breast cancer diagnosis, they are not fully automated. Moreover, the false-positive mammogram screening cases are high in number and over-diagnosis of breast cancer exposes a patient towards harmful overtreatment for which a huge amount of money is being wasted. In addition, it is also reported that the mammogram screening result with and without CAD systems does not have noticeable difference, whereas the undetected cancer cases by CAD system are increasing. Thus, future research is required to improve the performance of CAD system for mammogram screening and make it completely automated.
A Review on Data Mining Techniques for Prediction of Breast Cancer RecurrenceDr. Amarjeet Singh
The most common type of cancer in women
worldwide is the Breast Cancer. Breast cancer may be
detected early using Mammograms, probably before it's
spread. Recurrent breast cancer could occur months or years
after initial treatment. The cancer could return within the
same place because the original cancer (local recurrence), or it
may spread to different areas of your body (distant
recurrence). Early stage treatment is done not only to cure
breast cancer however additionally facilitate in preventing its
repetition/recurrence. Data mining algorithms provide
assistance in predicting the early-stage breast cancer that
continually has been difficult analysis drawback. The
projected analysis can establish the most effective algorithm
that predicts the recurrence of the breast cancer and improve
the accuracy the algorithms. Large information like Clump,
Classification, Association Rules, Prediction and Neural
Networks, Decision Trees can be analyzed using data mining
applications and techniques.
IRJET - Classifying Breast Cancer Tumour Type using Convolution Neural Netwo...IRJET Journal
This document presents a study that uses a convolutional neural network (CNN) deep learning model to classify breast cancer tumors as benign or malignant based on ultrasonic images. The researchers trained a CNN model using a dataset of ultrasonic breast images labeled as benign or malignant. The trained model can then analyze new ultrasonic images and determine the tumor type, which could help doctors diagnose and treat breast cancer more accurately. The document provides background on breast cancer and existing diagnosis methods, describes the proposed CNN classification system, and reviews related work applying machine learning to breast cancer analysis.
This document discusses radioimmunoscintigraphy and radioimmunotherapy for breast cancer diagnosis and treatment. It begins by introducing breast cancer as a major public health problem, and discusses various conventional imaging modalities for diagnosis like mammography and their limitations. It then highlights nuclear medicine techniques like radioimmunoscintigraphy which can help overcome these limitations by exploiting differences in tumor biology. The document also reviews current treatment methods for breast cancer including surgery, radiation therapy, chemotherapy and immunotherapy. It concludes by introducing radioimmunotherapy as a targeted molecular therapy method being researched to more efficiently treat cancer cells.
Performance Evaluation using Supervised Learning Algorithms for Breast Cancer...IRJET Journal
The document discusses using supervised machine learning algorithms to evaluate the performance of breast cancer diagnosis. It evaluates algorithms like perceptron, cascade-forward backpropagation, and feed-forward backpropagation on a breast cancer dataset from the Wisconsin Breast Cancer Diagnosis database. The algorithms are used to develop a process for diagnosis and prediction of breast cancer that could help physicians diagnose the disease more accurately.
Breast cancer screening guidelines recommend biennial mammography for women aged 50-74 in well-resourced settings, as it can reduce breast cancer mortality by around 16% compared to no screening. For limited-resource settings, the guidelines conditionally recommend clinical breast examination as a low-cost alternative. Screening intervals of less than 24 months show no added benefit over longer intervals. Shared decision making around risks of false positives and overdiagnosis is important. Early diagnosis through awareness and symptom screening is prioritized where most women present at late stages due to weak health systems.
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUESIAEME Publication
Women who have improved from breast cancer (BC) constantly panic about setback. The way that they have persevered through the meticulous treatment makes repeat their biggest fear. However, with current spreads in technology, early repeat prediction can enable patients to get treatment prior. The accessibility of broad information and propelled techniques make precise and fast prediction possible. This examination expects to think about the exactness of a couple of existing information mining calculations in predicting BC repeat. It inserts a particle swarm optimization as highlight choice into ANN classifier. An objective of increasing the accuracy level of the prediction model.
This document discusses various imaging modalities used for breast cancer screening and diagnosis, including mammography, ultrasound, MRI, CT, and PET scans. It provides details on mammography techniques for screening and diagnostic purposes. Key findings from studies on screening mammography for different age groups are summarized. Guidelines on screening from organizations like ACS, NCCN, and NCI are also outlined. The use of ultrasound and MRI as supplemental tools for diagnosis is discussed.
A Review Of Breast Cancer Classification And Detection TechniquesLori Moore
This document reviews techniques for classifying and detecting breast cancer. It discusses how breast cancer occurs when cells grow abnormally and can spread to other parts of the body. Early detection is important for treatment. The document examines various techniques that have been used for automated detection of breast cancer in medical images, including convolutional neural networks, support vector machines, and fuzzy clustering. It provides an overview of the types and stages of breast cancer and discusses challenges in screening and the need for more accurate and efficient detection methods.
Comparative analysis on bayesian classification for breast cancer problemjournalBEEI
The problem of imbalanced class distribution or small datasets is quite frequent in certain fields especially in medical domain. However, the classical Naive Bayes approach in dealing with uncertainties within medical datasets face with the difficulties in selecting prior distributions, whereby parameter estimation such as the maximum likelihood estimation (MLE) and maximum a posteriori (MAP) often hurt the accuracy of predictions. This paper presents the full Bayesian approach to assess the predictive distribution of all classes using three classifiers; naïve bayes (NB), bayesian networks (BN), and tree augmented naïve bayes (TAN) with three datasets; Breast cancer, breast cancer wisconsin, and breast tissue dataset. Next, the prediction accuracies of bayesian approaches are also compared with three standard machine learning algorithms from the literature; K-nearest neighbor (K-NN), support vector machine (SVM), and decision tree (DT). The results showed that the best performance was the bayesian networks (BN) algorithm with accuracy of 97.281%. The results are hoped to provide as base comparison for further research on breast cancer detection. All experiments are conducted in WEKA data mining tool.
IRJET- Comparison of Breast Cancer Detection using Probabilistic Neural Netwo...IRJET Journal
1) The document compares two machine learning algorithms, probabilistic neural network (PNN) and support vector machine (SVM), for detecting breast cancer in mammogram images.
2) It evaluates the performance of PNN and SVM on a dataset of 322 mammogram images containing both benign and malignant tumors.
3) The proposed methodology applies techniques like image enhancement, segmentation, and feature extraction before classifying the images using PNN and SVM to detect tumors and determine if they are benign or malignant.
PREDICTION OF BREAST CANCER,COMPARATIVE REVIEW OF MACHINE LEARNING TECHNIQUES...IRJET Journal
This document presents a comparative review of machine learning techniques for breast cancer prediction. It analyzes several algorithms applied to the Wisconsin Breast Cancer Diagnosis (WBCD) dataset, including SVM, KNN, Random Forest, AdaBoost, and XGBoost. XGBoost achieved the highest accuracy of 98.24% with 0% false negatives. The study demonstrates that machine learning can effectively predict breast cancer and increase early detection accuracy.
Breast Cancer Detection through Deep Learning: A ReviewIRJET Journal
Three sentences:
Convolutional neural networks show promise for automating breast cancer detection from medical images to address increasing caseloads. Previous research has developed CNN approaches for segmenting breast tissue and detecting cancer from mammograms and ultrasound images with strong accuracy. This literature review evaluates past works applying deep learning to breast cancer detection and segmentation tasks to inform the development of a new CNN-based approach detailed in future work.
PRIMARY SQUAMOUS CELL CANCER OF BREAST: A CASE REPORTKETAN VAGHOLKAR
Primary squamous cell cancer (SqCC) of the breast is a rather rare disease. These tumors are known to be
quite aggressive in nature and are usually found to be treatment-resistant. Currently, there is no standard treatment
guideline for the management of primary SqCC of the breast. In this case report, we present a case of primary SqCC of
the breast in 60-year old postmenopausal women presenting as pigmented lesion over the right breast (no lump). Initial
skin biopsy (core) done by dermatologist revealed squamous cell cancer in situ (Bowen’s disease); however surgical
resection of the lesion and subsequent histopathological examination revealed primary SqCC (no secondary sites were
found elsewhere in the body).
Logistic Regression Model for Predicting the Malignancy of Breast CancerIRJET Journal
1. The document describes using a logistic regression machine learning model to predict whether breast cancer is benign or malignant based on characteristics of breast cell samples.
2. The model was trained on a dataset of 569 samples described by 33 characteristics and achieved 94.94% accuracy on the training data and 92.10% accuracy on the test data.
3. The model provides a way to efficiently diagnose breast cancer and determine the appropriate treatment needed based on whether the cancer is predicted as benign or malignant.
This document provides information on diagnosing and treating breast cancer. It discusses evaluating a patient's history and performing a physical exam. Investigation may involve fine needle aspiration biopsy or core needle biopsy to obtain samples. Breast imaging with mammography, ultrasound or MRI can further evaluate abnormalities. Staging helps determine how far cancer has spread. Surgical options include breast-conserving surgery by removing the tumor with radiation, or mastectomy by removing the entire breast. The goal is to completely remove the cancer while maximizing cosmetic results.
Mammography is an important tool for early detection of breast cancer. It uses low-dose x-rays of the breast to find cancers too small to be felt. For women over 50, annual mammograms are recommended by leading health groups. Mammography works best with modern equipment that takes specialized images of the compressed breast from different angles. While no test is perfect, mammograms can find 85-90% of cancers when they are still micro in size. Early detection improves survival rates significantly. Men can also develop breast cancer, though it is much rarer, occurring in about 0.22% of cancer cases among males.
This document discusses various techniques for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It describes common PAPR reduction techniques such as partial transmit sequence (PTS), selective mapping (SLM), tone injection, peak cancellation, and peak windowing. It analyzes these techniques based on parameters like distortion, power increase, data rate loss, and bit error rate improvement. The document concludes that while SLM is better for PAPR reduction as it does not cause out-of-band radiation or degrade bit error rate performance, it has the drawback of increased complexity with larger number of subcarriers or phase sequences.
This document summarizes the performance enhancement and characterization of a junctionless vertical slit field effect transistor (JLVeSFET). Key findings from simulations include:
1) The JLVeSFET shows an optimized subthreshold slope of 65mV/decade and OFF current of ~10-18A/μm for a 50nm radius device with a high-k dielectric.
2) Using a high-k dielectric (Si3N4) instead of SiO2 increases the Ion/Ioff ratio to ~1011 and reduces the subthreshold slope to 63mV/decade.
3) Increasing the gate doping concentration reduces the subthreshold slope slightly while increasing the Ion/
This document summarizes research that analyzed the effect of temperature on the parameters of silicon solar cells. It was found that the open circuit voltage (Voc) of the solar cells decreases linearly as temperature increases from 20°C to 80°C. In contrast, the short circuit current (Isc) was found to increase only slightly with higher temperatures. The maximum efficiency of 18.5% was obtained at 20°C when Voc was 667.3mV and Isc was 37.56mA. Overall, the study demonstrated that higher temperatures negatively impact the Voc, fill factor, and efficiency of silicon solar cells.
The document presents a new bridgeless single-phase AC-DC converter based on a single-ended primary inductance converter (SEPIC) topology. The proposed rectifier utilizes a bidirectional switch and two fast diodes. It has less conduction losses compared to existing power factor correction rectifiers due to fewer components conducting during each switching cycle. Experimental results show the converter can achieve a high power factor under universal input voltage conditions and provide regulated output voltage for resistive and incandescent lamp loads. Future work may include further optimizing the design for applications requiring high power quality input power.
The document presents a new ontology matching system based on a multi-agent architecture. The system takes ontologies described in XML, RDF Schema, and OWL as input. It uses multiple matchers and filtering to generate mappings between ontology entities. The mappings are then validated. The system is implemented as a multi-agent system with different agent types responsible for resources, matching, generating mappings, and filtering/validating mappings. The architecture allows for robust, flexible, and scalable ontology matching.
This document discusses techniques to reduce leakage current and power consumption in static random-access memory (SRAM) cells implemented using independent gate fin field-effect transistors (FinFETs). It first describes the independent gate FinFET SRAM cell design and its advantages over other designs. It then examines two circuit-level leakage reduction techniques: 1) using multi-threshold voltages by connecting high-threshold transistors to reduce leakage when in standby mode, and 2) adding a gated power supply transistor to reduce leakage through stacking effects. Simulation results show that both techniques can reduce leakage current and power in the independent gate FinFET SRAM cell, with multi-threshold voltages providing better leakage control.
This document summarizes a survey on string similarity matching search techniques. It discusses how string similarity matching is used to find relevant information in text collections. The document reviews different algorithms for string matching, including edit distance, NR-grep, n-grams, and approaches based on hashing and locality-sensitive hashing. It analyzes techniques like pattern matching, threshold-based joins, and vector representations. The goal is to present an overview of the field and compare algorithm performance for similarity searches.
The document reviews various methods for enhancing the bandwidth of microstrip patch antennas. It discusses how modifying the patch shape, using multilayer configurations, planar/stacked multi-resonator structures, and different feeding techniques can increase the antenna's bandwidth. Modified patch shapes, multilayer structures, and proximity coupled feeding provide the greatest bandwidth enhancements, with multilayer designs potentially achieving over 70% bandwidth. The review concludes that slot loading and multilayer techniques are most effective for enhancing bandwidth while maintaining a small antenna size.
This document presents a new method for interpolation called weighted average interpolation (WAI). WAI uses the concepts of positive and negative effect to determine the influence of neighboring data points. Correction factors are derived from Pascal's triangle to match the results of WAI to Lagrange interpolation. The method is extended to extrapolation and unevenly spaced data using similar concepts. WAI aims to reduce the number of operations compared to Lagrange interpolation while maintaining accuracy.
This document presents a theorem about the almost Norlund summability of conjugate Fourier series. It generalizes previous results by Pati (1961) and Singh and Singh (1993). The main theorem states that if the conjugate partial sums of a Fourier series satisfy certain conditions, including being bounded by a function that approaches 0 as n approaches infinity, then the conjugate Fourier series is almost Norlund summable to the integral of the function at every point where the integral exists. The proof utilizes lemmas about the behavior of the conjugate partial sums and applies mean value theorems to show the necessary conditions are met. References to previous related works are also provided.
The document discusses the determination of diffusion constants in boronated powder metallurgy samples of the iron-carbon-copper system. Experiments were conducted on powdered samples with 0.1% carbon and 1-3% copper. The thickness of the boride layers formed after boronation at temperatures of 920-980°C were measured. The data was used to calculate the activation energy (Q) and pre-exponential factor (Do) based on parabolic growth curves. The results show that Q increases with sample density from 5.8 to 7 g/cm3. Adding up to 2% copper reduces Q values, but higher copper concentrations increase Q similar to pure iron samples.
This document compares various biometric methods for identification and verification. It discusses fingerprint recognition, face recognition, voice recognition, and iris recognition as some of the main biometric techniques. For each method, it describes how the biometric data is captured and analyzed, the advantages and disadvantages, and examples of applications where the technique can be used. The document provides an overview of the history of biometrics and the typical modules involved in a biometric system, such as sensors, feature extraction, matching, and template databases.
This document describes the design of a digital phase locked loop (PLL) with a divide by 4/5 prescaler. The digital PLL uses a digital phase frequency detector, time to digital converter, thermometric decoder, and digitally controlled oscillator. The proposed PLL design uses an accumulator type DCO and ring oscillator type TDC to achieve fast lock time and reduced jitter. The final system incorporates all the components to function as a digital PLL that locks when the reference and feedback frequencies match.
The document discusses energy efficient routing protocols for clustered wireless sensor networks. It provides an overview of wireless sensor networks and discusses how clustering is commonly used to improve energy efficiency and scalability. The document reviews several existing clustering-based routing protocols and analyzes their approaches for prolonging network lifetime by minimizing energy consumption in wireless sensor networks.
The document discusses bit error rate (BER) performance analysis of M-ary quadrature amplitude modulation (M-QAM) for implementation of orthogonal frequency-division multiplexing (OFDM). It analyzes the theoretical BER of M-QAM under different modulation orders and signal-to-noise ratios (SNR). The analysis shows that higher order M-QAM has higher BER than lower order M-QAM for the same SNR due to decreased symbol distances as the modulation order increases. It also discusses the use of M-QAM modulation in OFDM systems and outlines challenges in implementing higher order M-QAM for OFDM.
This document analyzes the groundwater quality of South Karaikal and Nagapattinam districts in Tamil Nadu, India. 14 groundwater samples were collected and analyzed for physicochemical parameters including major ions. Spatial variation maps were generated for parameters like calcium, chloride, sodium, and bicarbonate which showed high and low concentration regions. Piper and Durov plots indicated mixed temporary and permanent water hardness. Sodium absorption ratio values identified areas of excellent, good and fair water quality for irrigation. Overall, comparison to standards showed groundwater was not suitable for drinking in most areas.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.