Description

Book Synopsis

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.



Machine Learning for Tomographic Imaging

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A Hardback by Professor Ge Wang, Professor Yi Zhang, Professor Xiaojing Ye

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    Publisher: Institute of Physics Publishing
    Publication Date: 12/30/2019 12:00:00 AM
    ISBN13: 9780750322140, 978-0750322140
    ISBN10: 0750322144
    Also in:
    Medical imaging

    Description

    Book Synopsis

    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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