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Machine Learning for Tomographic Imaging

By: (Author) Professor Ge Wang , (Author) Professor Xiaojing Ye , (Author) Professor Xuanqin Mou , (Author) Professor Yi Zhang

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Ksh 13,800.00

Format: Hardback or Cased Book

ISBN-10: 0750322144

ISBN-13: 9780750322140

Series: IPEM-IOP Series in Physics and Engineering in Medicine and Biology

Publisher: Institute of Physics Publishing

Imprint: Institute of Physics Publishing

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Dec 30th, 2019

Print length: 411 Pages

Weight: 930 grams

Dimensions (height x width x thickness): 25.40 x 17.80 x 2.40 cms

Product Classification: Medical imaging

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Written by leading researchers in the field, Machine Learning for Tomographic Imaging presents a unified overview of deep-learning-based tomographic imaging. Key concepts, including classic reconstruction ideas and human vision inspired insights, are introduced as a foundation for a thorough examination of artificial neural networks and deep tomographic reconstruction. An engaging and accessible style makes this book an ideal introduction for those in applied disciplines, as well as those in more theoretical fields who wish to learn about application contexts. Hands-on projects are also suggested, and links to open source software, working datasets, and network models are included.




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