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Machine Learning for Tomographic Imaging
Hardcover
Series: Programme: Iop Expanding Physics
ISBN13: 9780750322140
Publisher: Institute of Physics Publishing
Published: Mar 15 2020
Pages: 250
Weight: 2.10
Height: 1.10 Width: 7.10 Depth: 10.10
Language: English
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.
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