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In Computed Tomography: Algorithms, Insight, and Just Enough
Theory, readers will learn about the fundamental computational
methods used for image reconstruction in computed tomography (CT).
Unique in its emphasis on the interplay of modeling, computing, and
algorithm development, the book presents underlying mathematical
models for motivating and deriving the basic principles of CT
reconstruction methods, along with insight into their advantages,
limitations, and computational aspects. Computed Tomography:
Algorithms, Insight, and Just Enough Theory: Develops the
mathematical and computational aspects of three main classes of
reconstruction methods. Emphasizes the link between CT and
numerical methods, which is rarely found in current literature.
Describes the effects of incomplete data using both microlocal
analysis and the singular value decomposition (SVD). Contains
computer exercises using MATLAB that allow readers to experiment
with the algorithms and make the book suitable for teaching and
self-study. This book is aimed at students, researchers, and
practitioners. As a textbook, it is appropriate for the following
courses: Advanced Numerical Analysis, Special Topics on Numerical
Analysis, Topics on Data Science, Topics on Numerical Optimization,
and Topics on Approximation Theory.
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