Wow! eBook
Machine Learning for Tomographic Imaging
Author(s): Professor Ge Wang (Author), Professor Yi Zhang (Author), Professor Xiaojing Ye (Author)
- Publisher: Institute of Physics Publishing
- Publication Date: 30 Dec. 2019
- Language: English
- Print length: 412 pages
- ISBN-10: 0750322179
- ISBN-13: 9780750322171
Book Description
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.
Editorial Reviews
Review
Machine Learning for Tomographic Imaging, presents a detailed overview of the emerging discipline of deep-learning-based tomographic imaging.
The book begins with an introduction to imaging principles, tomographic reconstruction and artificial neural networks. Parts two and three provide in-depth tutorials on CT and MR image reconstruction and describe a range of recent machine learning techniques. The final part of the book covers other imaging modalities, including PET, SPECT, ultrasound and optical imaging, as well as taking a look at image quality evaluation and quantum computing. The text also includes appendices describing relevant numerical methods and suggesting hands-on projects, with sample codes and working datasets.
Tami Freeman 2020 Physics World IOP Publishing
