Machine learning for tomographic imaging

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Tác giả: Xuanqin Mou, Ge Wang, Xiaojing Ye, Yi Zhang

Ngôn ngữ: eng

ISBN-13: 978-0750322140

ISBN-13: 978-0750322157

ISBN-13: 978-0750322164

ISBN-13: 978-0750322171

Ký hiệu phân loại: 616.0754 Diseases

Thông tin xuất bản: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, 2020

Mô tả vật lý: 1 online resource (various pagings) : , illustrations (some color).

Bộ sưu tập: Tài liệu truy cập mở

ID: 160943

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 highly 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 as well. An engaging and accessible style makes this book an ideal introduction for those in applied disciplines, as well as those in more theoretical disciplines 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. Part of Series in Physics and Engineering in Medicine and Biology.
Includes bibliographical references.
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