Deep Learning for Biomedical Image Reconstruction

Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. The background theory of deep learning is introduced step-by-step, and by incorporating modeling fundamentals this book explains how to implement deep learning in a variety of modalities, including X-ray, CT, MRI and others. Real-world examples demonstrate an interdisciplinary approach to medical image reconstruction processes, featuring numerous imaging applications. Recent clinical studies and innovative research activity in generative models and mathematical theory will inspire the reader towards new frontiers. This book is ideal for graduate students in Electrical or Biomedical Engineering or Medical Physics.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	September 2023
Editors:	Jong Chul Ye • Yonina C. Eldar • Michael Unser
Pages:	400
ISBN-13:	978-1-316-51751-2
Categories:	Books
LSN:	1-316-51751-9
Barcode:	9781316517512

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