Binding: Paperback
Description: 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 2 D/3 D 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.
Title: Deep Network Design For Medical Image Computing Principles And Applications
Author(s): Luo Jiebo (Professor Of Computer Science University Of Rochester Ny Usa)
Publisher: Elsevier Science Publishing Co Inc
Barcode: 9780128243831
Pages: 264 Pages, 75 Illustrations (30 In Full Color); Illustrations, Unspecified
Publication Date: 8/30/2022
Series: The MICCAI Society book Series
Category: Computer Vision