Skip to main content

Deep Network Design for Medical Image Computing

Principles and Applications

  • 1st Edition - August 24, 2022
  • Authors: Haofu Liao, S. Kevin Zhou, Jiebo Luo
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 1 2 - 8 2 4 3 8 3 - 1
  • eBook ISBN:
    9 7 8 - 0 - 1 2 - 8 2 4 4 0 3 - 6

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 approache… Read more

Deep Network Design for Medical Image Computing

Purchase options

Limited Offer

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Institutional subscription on ScienceDirect

Request a sales quote

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.