Download or read book EARLY DETECTION OF MALIGNANCY IN HUMAN BREASTS USING DEEP LEARNING written by Ashok Kumar and published by . This book was released on 2022-10-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is the fitful growth of cells that originate in the breast tissue. Breast cancer is any form of malignancy which develops from breast cells. Cancer is a disease in which malignancy cells in the body grow, change and multiply out of control. It is the most common cancer disease in women worldwide, especially those who are in the age group of 40 to 55 years and one of the leading causes of death from cancer in women. Breast cancer is reported as the second most prevalent cause of the cancerous death in the report of World Health Organization]. Breast cancer is"the second most common cancer worldwide. There were over 2 million new cases reported in 2018. The recent statistics of a study by American Cancer Society gives an alarming message that about 3,30,080 new cases of breast cancer are expected to be diagnosed in women in the U.S. and about 2,550 new cases of invasive breast cancer are expected to be diagnosed in men in 2018. These new cases of breast cancer in women are further classified as 2,66,120 new cases of invasive and 63,960 new cases of non-invasive breast cancer. A man's lifetime risk of breast cancer is about 1 in 1,000 whereas 1 in 8 for women which is about 12.4% chances of having breast cancer over the course of the lifetime . The worldwide cancer statistics report says breast cancer is the third most common cancer in the world in terms of number of new cases . In India, there are around 2.5 million diagnosed with cancer and will lead to 5,56,600 deaths per year. By 2020, India is reported to have over 17.5 lakhs diagnosed patients with breast cancer and near 8.8 lakhs deaths caused by this disease . As reported in literature, most prevailing cancer in India is breast cancer and its explanation is a 27% count in all types of cancer in women. Early detection is an exhausting effort and a nerve center on cancer detection. Imaging modalities and advancements in technology disported a far-reaching role in early detection [4]. Mammography has been extensively recognized as a diagnostic and shielding weapon for an early detection of breast cancer and even up to ten years before detection and diagnosis stage. Mammography can curtail the number of mortality native to breast cancer, particularly among women in an age group of years 40-70. Mammography implies the assimilation of anomalies such as calcifications and masses to detect breast cancer. It makes image analysis as a thrust area of research for an early detection of breast cancer. The enactment of a Computer Aided Diagnosis (CAD) system can revamp the early cancer detection rate and could also share the experts workload [6]. A recent report manifested that the enactment of CAD refined the process of breast cancer detection by 7.62% and this automated or semi-automated gizmo has captivated great considerations [6]. Many Computer Aided Diagnosis systems prospected to assist radiologists to curtail the diagnostic errors effectively by using mammogram and MRI imaging modality of breast mass or calcification [33] [26]. Computer Aided Diagnosis systems substantiated a probably compelling tool for detecting the masses or micro calcifications in recent considerations

Download or read book Breast Imaging written by Christoph I. Lee and published by Oxford University Press. This book was released on 2018 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast Imaging presents a comprehensive review of the subject matter commonly encountered by practicing radiologists and radiology residents in training. This volume includes succinct overviews of breast cancer epidemiology, screening, staging, and treatment; overviews of all imaging modalities including mammography, tomosynthesis, ultrasound, and MRI; step-by-step approaches for image-guided breast interventions; and high-yield chapters organized by specific imaging finding seen on mammography, tomosynthesis, ultrasound, and MRI. Part of the Rotations in Radiology series, this book offers a guided approach to breast imaging interpretation and techniques, highlighting the nuances necessary to arrive at the best diagnosis and management. Each chapter contains a targeted discussion of an imaging finding which reviews the anatomy and physiology, distinguishing features, imaging techniques, differential diagnosis, clinical issues, key points, and further reading. Breast Imaging is a must-read for residents and practicing radiologists seeking a foundation for the essential knowledge base in breast imaging.

Download or read book Artificial Intelligence in Breast Cancer Early Detection and Diagnosis written by Khalid Shaikh and published by Springer Nature. This book was released on 2020-12-04 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods Discusses cancer treatment based on geographical differences and cultural characteristics

Download or read book Developing Technologies for Early Detection of Breast Cancer written by National Research Council and published by National Academies Press. This book was released on 2000-07-06 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: In November 1999, the Institute of Medicine, in consultation with the Commission on Life Sciences, the Commission on Physical Sciences, Mathematics, and Applications, and the Board on Science, Technology and Economic Policy launched a one year study on technologies for early detection of breast cancer. The committee was asked to examine technologies under development for early breast cancer detection, and to scrutinize the process of medical technology development, adoption, and dissemination. The committee is gathering information on these topics for its report in a number of ways, including two public workshops that bring in outside expertise. The first workshop on "Developing Technologies for Early Breast Cancer Detection" was held in Washington DC in February 2000. The content of the presentations at the workshop is summarized here. A second workshop, which will focus on the process of technology development and adoption, will be held in Washington, DC on June 19-20. A formal report on these topics, including conclusions and recommendations, will be prepared by the committee upon completion of the one-year study.

Download or read book Digital Breast Tomosynthesis written by Alberto Tagliafico and published by Springer. This book was released on 2016-05-03 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive description of the screening and clinical applications of digital breast tomosynthesis (DBT) and offers straightforward, clear guidance on use of the technique. Informative clinical cases are presented to illustrate how to take advantage of DBT in clinical practice. The importance of DBT as a diagnostic tool for both screening and diagnosis is increasing rapidly. DBT improves upon mammography by depicting breast tissue on a video clip made of cross‐sectional images reconstructed in correspondence with their mammographic planes of acquisition. DBT results in markedly reduced summation of overlapping breast tissue and offers the potential to improve mammographic breast cancer surveillance and diagnosis. This book will be an excellent practical teaching guide for beginners and a useful reference for more experienced radiologists.

Download or read book Breast Cancer Classification Using Machine Learning An Empirical Study written by Akor Ugwu and published by GRIN Verlag. This book was released on 2021-05-11 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diploma Thesis from the year 2020 in the subject Medicine - Diagnostics, grade: 3.55, , course: Computer Science, language: English, abstract: The study will classify breast cancers into foremost problems: (Benign tumor and Malignant tumor). A benign tumor is a most cancers does now not invade its surrounding tissue or spread around the host. A malignant tumor is another kind of cancers which can invade its surrounding tissue or spread around the frame of the host. Benign cancers on uncommon event can also surely result in someone’s death, but as a fashionable rule they're no longer nearly as horrific because the malignant cancers. The malignant cancers at the contrary are like those killer bees. In this situation, you do not need to be doing something to them or maybe be everywhere near their hive, they will just spread out and attack you emass – they could even kill the individual if they are extreme enough. Manual manner of cancer category into benign and malignant may be very tedious, susceptible to human error and unnecessarily time consuming. The proposed system while constructed can robotically classify the sort of most cancers into the safe (benign) and also the risky (malignant). This machine plays this role through the usage of machine getting to know algorithm. The following is the extensive of this new system: Classification mistakes could be notably removed, early analysis of disorder, removal of possible human mistakes and the device does no longer die. However, the researcher seeks to detect and assess the class of breast using Machine learning.

Download or read book Developing Technologies for Early Detection of Breast Cancer written by National Research Council and published by National Academies Press. This book was released on 2000-08-06 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: In November 1999, the Institute of Medicine, in consultation with the Commission on Life Sciences, the Commission on Physical Sciences, Mathematics, and Applications, and the Board on Science, Technology and Economic Policy launched a one year study on technologies for early detection of breast cancer. The committee was asked to examine technologies under development for early breast cancer detection, and to scrutinize the process of medical technology development, adoption, and dissemination. The committee is gathering information on these topics for its report in a number of ways, including two public workshops that bring in outside expertise. The first workshop on "Developing Technologies for Early Breast Cancer Detection" was held in Washington DC in February 2000. The content of the presentations at the workshop is summarized here. A second workshop, which will focus on the process of technology development and adoption, will be held in Washington, DC on June 19-20. A formal report on these topics, including conclusions and recommendations, will be prepared by the committee upon completion of the one-year study.

Download or read book Early Detection of Breast Cancer written by S. Brünner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: The enormous expansion seen over the last decade in the mammo graphic detection of breast cancer lesions, especially the use of screen ing procedures for the early detection of clinically unsuspected tumors, has made it necessary to summarize the experience made by various centers in the world. The 2nd International Copenhagen Symposium on Detection of Breast Cancer afforded an opportunity of gathering scientists from all over the world to discuss the various problems of early breast cancer detection with special reference to screening procedures. This book forms a synthesis of the information presented by leading scientists from many of the world's mammo graphic centers, particularly those in Sweden and the USA. Hence, the reader will have the opportunity to study the outstanding work carried out by various institutes and centers of breast cancer screening. It is our sincere hope that a study of this volume will encourage other scientists to join in the work on screening procedures. S. Brunner B. Langfeldt P. E. Andersen Contents S. A. Feig: 1 Hypothetical Breast Cancer Risk from Mammography S. A. Feig: Benefits and Risks of Mammography 11 R. L. Egan and M. B. McSweeney: Multicentric Breast Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . 28 M. B. McSweeney and R. L. Egan: Breast Cancer in the Younger Patient: A Preliminary Report 36 M. B. McSweeney and R. L. Egan: Bilateral Breast Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . ' 41 N. Bjurstam: The Radiographic Appearance of Normal and Metastatic Axillary Lymph Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 M. Moskowitz, S. A. Feig, C. Cole-Beuglet, S. H.

Download or read book Early Prediction of Diseases using Deep Learning and Machine Learning Techniques written by Dr. Sasidhar B and published by Archers & Elevators Publishing House. This book was released on with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence in Breast Cancer Early Detection and Diagnosis written by Khalid Shaikh and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods Discusses cancer treatment based on geographical differences and cultural characteristics.

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Download or read book Early Detection of Breast Cancer Through Supervised Machine Learning written by Sandeep Chaurasia and published by . This book was released on 2015-03-19 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning Systems for Automated Lesion Detection Segmentation and Classification in Mammography written by Dina Abdelhafiz and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is the second leading cause of cancer deaths among women in the USA. Mammography is the preferred screening tool for breast cancer and accounts for the greatest contribution to the early detection of breast cancer. The detection of breast masses in mammogram (MG) images using deep learning (DL) systems is a challenging task due to the varying sizes, shapes, and textures of masses. In this thesis, we propose a novel DL network called residual attention UNet (RAU-Net), the network pays attention to small lesions, and shows superior performance compared to the other state-of-the-arts DL models in detecting and segmenting masses, especially for heterogeneously dense and dense MG images. The proposed RAU-Net model achieves a mean dice coefficient index of 0.98 and mean intersection over union of 0.94. We propose a DL residual network for classification of MG images into benign and malignant that achieved accuracy of 0.95, and AUC of 0.98. We also propose a one-shot multi-input Siamese network that learns features from previous and current year MG images of the same patient to give a better assessment for current year MG images. The detection of mass tumors in dense tissues and, more generally, in dense breasts is often considered more challenging due to the similar visual aspects of normal and abnormal dense tissues. In this thesis, we present a training algorithm that we used to train various kinds of U-Net networks such as RCNN-UNet, AU-Net, RAU-Net,and UNet++ to generate density attention masks that automatically pays attention and gives more weight to tumors in dense regions of MG images. To train and test our models, we collected and pre-processed MG images that come with different resolutions from public repositories and MG images from UCONN health center. In conclusion, we proposed DL systems for lesion detection, segmentation, and classification in mammography that can aid radiologists and serve as a second eye for them.

Download or read book Image guided Diagnosis and Treatment of Breast Cancer written by United States. Public Health Service. Office on Women's Health and published by . This book was released on 1998 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning in Cancer Diagnostics written by Mohd Hafiz Arzmi and published by Springer Nature. This book was released on 2023-01-18 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is the leading cause of mortality in most, if not all, countries around the globe. It is worth noting that the World Health Organisation (WHO) in 2019 estimated that cancer is the primary or secondary leading cause of death in 112 of 183 countries for individuals less than 70 years old, which is alarming. In addition, cancer affects socioeconomic development as well. The diagnostics of cancer are often carried out by medical experts through medical imaging; nevertheless, it is not without misdiagnosis owing to a myriad of reasons. With the advancement of technology and computing power, the use of state-of-the-art computational methods for the accurate diagnosis of cancer is no longer far-fetched. In this brief, the diagnosis of four types of common cancers, i.e., breast, lung, oral and skin, are evaluated with different state-of-the-art feature-based transfer learning models. It is expected that the findings in this book are insightful to various stakeholders in the diagnosis of cancer. ​

Download or read book Advanced Machine Learning Approaches in Cancer Prognosis written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2021-05-29 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.

Download or read book Automated breast cancer detection and classification using ultrasound images A survey written by H.D.Cheng and published by Infinite Study. This book was released on with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment, save lives and reduce cost. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast.