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This proposed book aims to discuss the recent trends and progress happening in hospitals and research laboratories to detect and diagnose breast cancer. It also aims to support researchers working in medical image analysis fields to explore the methodologies supported by various case studies on breast cancer with a range of medical imaging modalities.
It also provides essential information regarding breast cancer including, (1) the cause for breast cancer, (2) screening protocols for breast cancer, and (3) image assisted diagnosis with (a) Segmentation, (b) Machine-Learning and (c) Deep-learning techniques, and (d) Treatment planning and execution.
Chapter 1: Introduction to anatomy and physiology of the breast
Chapter 2: Causes for breast abnormalities
Chapter 3: Breast abnormality screening
Chapter 4: Computer aided detection methods
Chapter 5: Implementation of machine-learning scheme
Chapter 6: Implementation of deep-learning system
Chapter 7: Hybrid detection methods
Chapter 8: Evaluation of clinically collected breast thermal images
Chapter 9: Other case studies and future scope