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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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    £67.50

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    RRP £75.00 – you save £7.50 (10%)

    Order before 4pm today for delivery by Wed 17 Jun 2026.

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

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      View other formats and editions of Machine Learning for Tomographic Imaging by Professor Ge Wang

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

      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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