Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks (Foundations and Trends(r) in Signal Processing)

McCann, Michael T; Unser, Michael

ISBN 10: 1680836501 / ISBN 13: 9781680836509

Published by Now Publishers, 2019

About this Item

pp. 88.

Seller Inventory # 26376500717

Bibliographic Details

• Title: Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks (Foundations and Trends(r) in Signal Processing)
• Publisher: Now Publishers
• Publication Date: 2019
• Language: English
• ISBN 10: 1680836501
• ISBN 13: 9781680836509
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Biomedical imaging is a vast and diverse field. There are a plethora of imaging devices using light, X-rays, sound waves, magnetic fields, electrons, or protons, to measure structures ranging from nano to macroscale. In many cases, computer software is needed to turn the signals collected by the hardware into a meaningful image. These computer algorithms are similarly diverse and numerous. This survey presents a wide swath of biomedical image reconstruction algorithms under a single framework. It is a coherent, yet brief survey of some six decades of research. The underpinning theory of the techniques are described and practical considerations for designing reconstruction algorithms for use in biomedical systems form the central theme of each chapter. The unifying framework deployed throughout the monograph models imaging modalities as combinations of a small set of building blocks, which identify connections between modalities Thus, the user can quickly port ideas and computer code from one to the next. Furthermore, reconstruction algorithms can treat the imaging model as a black. box, meaning that one algorithm can work for many modalities. This provides a pragmatic approach to designing effective reconstruction algorithms. This monograph is written in a tutorial style that concisely introduces students, researchers and practitioners to the development and design of effective biomedical image reconstruction algorithms.