Overview
- Clearly explains the concepts with minimum mathematical derivation
- Written in reader-friendly style
- Helps the readers to understand modern image reconstruction algorithms with little background
- Provides more than 140 illustrations
- Presents up-to-date results in analytical and iterative image reconstruction
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About this book
"Medical Image Reconstruction: A Conceptual Tutorial" introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l0-minimization are also included.
This book is written for engineers and researchers in the field of biomedical engineering specializing in medical imaging and image processing with image reconstruction.
Gengsheng Lawrence Zeng is an expert in the development of medical image reconstruction algorithms and is a professor at the Department of Radiology, University of Utah, Salt Lake City, Utah, USA.
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Table of contents (7 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Medical Image Reconstruction
Book Subtitle: A Conceptual Tutorial
Authors: Gengsheng Lawrence Zeng
DOI: https://doi.org/10.1007/978-3-642-05368-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2010
eBook ISBN: 978-3-642-05368-9Published: 28 December 2010
Edition Number: 1
Number of Pages: XIII, 198
Additional Information: Jointly published with Higher Education Press
Topics: Biomedical Engineering and Bioengineering, Imaging / Radiology, Mathematical and Computational Engineering, Signal, Image and Speech Processing