Items related to Machine Learning for Tomographic Imaging (IOP ebooks)
Machine Learning for Tomographic Imaging (IOP ebooks) - Hardcover
Book 16 of 36: IPEM-IOP Series in Physics and Engineering in Medicine and Biology
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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Machine Learning for Tomographic Imaging
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Machine Learning for Tomographic Imaging
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Machine Learning for Tomographic Imaging (Programme: IOP Expanding Physics)
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Machine Learning for Tomographic Imaging
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Institute of Physics Publishing, 2020
ISBN 10: 0750322144
ISBN 13: 9780750322140
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Machine Learning for Tomographic Imaging (Programme: IOP Expanding Physics)
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Machine Learning for Tomographic Imaging
Published by
Institute of Physics Publishing, 2020
ISBN 10: 0750322144
ISBN 13: 9780750322140
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Machine Learning for Tomographic Imaging
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IOP Publishing Ltd Mär 2020, 2020
ISBN 10: 0750322144
ISBN 13: 9780750322140
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Buch. Condition: Neu. Neuware - The area of machine learning, especially deep learning, has exploded in recent years, producing advances in everything from speech recognition and gaming to drug discovery. Tomographic imaging is another major area that is being transformed by machine learning, and its potential to revolutionise medical imaging is significant.Written by active 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. X-ray CT and MRI reconstruction methods are covered in detail, and other medical imaging applications are discussed.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. Seller Inventory # 9780750322140