Deep Network Design for Medical Image Computing: Principles and Applications * covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine.* These include skin disease classification, vertebrae identification and localization, cardiac ultrasoun...

Deep Network Design for Medical Image Computing: Principles and Applications * covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine.* These include skin disease classification, vertebrae identification and localization, cardiac ultrasound image segmentation, 2D/3D medical image registration for intervention, metal artifact reduction, sparse-view artifact reduction, etc. For each topic, the book provides a deep learning-based solution that takes into account the medical or biological aspect of the problem and how the solution addresses a variety of important questions surrounding architecture, the design of deep learning techniques, when to introduce adversarial learning, and more.

This book will help graduate students and researchers develop a better understanding of the deep learning design principles for MIC and to apply them to their medical problems.