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Statistical Computing in Nuclear Imaging (Hardcover)
Loot Price: R3,182
Discovery Miles 31 820
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Statistical Computing in Nuclear Imaging (Hardcover)
Series: Series in Medical Physics and Biomedical Engineering
Expected to ship within 12 - 17 working days
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Statistical Computing in Nuclear Imaging introduces aspects of
Bayesian computing in nuclear imaging. The book provides an
introduction to Bayesian statistics and concepts and is highly
focused on the computational aspects of Bayesian data analysis of
photon-limited data acquired in tomographic measurements. Basic
statistical concepts, elements of decision theory, and counting
statistics, including models of photon-limited data and Poisson
approximations, are discussed in the first chapters. Monte Carlo
methods and Markov chains in posterior analysis are discussed next
along with an introduction to nuclear imaging and applications such
as PET and SPECT. The final chapter includes illustrative examples
of statistical computing, based on Poisson-multinomial statistics.
Examples include calculation of Bayes factors and risks as well as
Bayesian decision making and hypothesis testing. Appendices cover
probability distributions, elements of set theory, multinomial
distribution of single-voxel imaging, and derivations of sampling
distribution ratios. C++ code used in the final chapter is also
provided. The text can be used as a textbook that provides an
introduction to Bayesian statistics and advanced computing in
medical imaging for physicists, mathematicians, engineers, and
computer scientists. It is also a valuable resource for a wide
spectrum of practitioners of nuclear imaging data analysis,
including seasoned scientists and researchers who have not been
exposed to Bayesian paradigms.
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