Medical Image Reconstruction : : From Analytical and Iterative Methods to Machine Learning / / Gengsheng Lawrence Zeng.

This textbook introduces the essential concepts of tomography in the field of medical imaging. The medical imaging modalities include x-ray CT (computed tomography), PET (positron emission tomography), SPECT (single photon emission tomography) and MRI. In these modalities, the measurements are not i...

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Superior document:Title is part of eBook package: De Gruyter DG Plus DeG Package 2023 Part 1
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Place / Publishing House:Berlin ;, Boston : : De Gruyter, , [2023]
©2023
Year of Publication:2023
Edition:2nd edition
Language:English
Series:De Gruyter Textbook
Online Access:
Physical Description:1 online resource (XIV, 273 p.)
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100 1 |a Zeng, Gengsheng Lawrence,   |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Medical Image Reconstruction :  |b From Analytical and Iterative Methods to Machine Learning /  |c Gengsheng Lawrence Zeng. 
250 |a 2nd edition 
264 1 |a Berlin ;  |a Boston :   |b De Gruyter,   |c [2023] 
264 4 |c ©2023 
300 |a 1 online resource (XIV, 273 p.) 
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490 0 |a De Gruyter Textbook 
505 0 0 |t Frontmatter --   |t Preface --   |t Contents --   |t 1 Basic principles of tomography --   |t 2 Parallel-beam image reconstruction --   |t 3 Fan-beam image reconstruction --   |t 4 Transmission and emission tomography --   |t 5 Three-dimensional image reconstruction --   |t 6 Iterative reconstruction --   |t 7 MRI reconstruction --   |t 8 Using FBP to perform iterative reconstruction --   |t 9 Machine learning --   |t Index 
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520 |a This textbook introduces the essential concepts of tomography in the field of medical imaging. The medical imaging modalities include x-ray CT (computed tomography), PET (positron emission tomography), SPECT (single photon emission tomography) and MRI. In these modalities, the measurements are not in the image domain and the conversion from the measurements to the images is referred to as the image reconstruction. The work covers various image reconstruction methods, ranging from the classic analytical inversion methods to the optimization-based iterative image reconstruction methods. As machine learning methods have lately exhibited astonishing potentials in various areas including medical imaging the author devotes one chapter to applications of machine learning in image reconstruction. Based on college level in mathematics, physics, and engineering the textbook supports students in understanding the concepts. It is an essential reference for graduate students and engineers with electrical engineering and biomedical background due to its didactical structure and the balanced combination of methodologies and applications. 
530 |a Issued also in print. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 06. Mrz 2024) 
650 4 |a Analytische Inversion. 
650 4 |a Iterative Optimierung. 
650 4 |a Klinische Anwendungen tomographischer Methoden. 
650 4 |a Maschinelles Lernen. 
650 4 |a Tomographische Methoden. 
650 7 |a SCIENCE / Physics / Optics & Light.  |2 bisacsh 
653 |a . 
653 |a Analytic Inversion. 
653 |a Clinical Applications of Tomographic Methods. 
653 |a Iterative Optimization. 
653 |a Machine Learning. 
653 |a Tomography Methods. 
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