Statistical Computing in Nuclear Imaging – eBook

Description

The ebook Statistical Computing in Nuclear Imaging (PDF) serves as a comprehensive guide to the intricacies of Bayesian computing specifically tailored for applications in nuclear imaging. This authoritative textbook delves into the foundational principles of Bayesian statistics, highlighting not only the theoretical aspects but also the essential computational techniques required for effective data analysis of photon-limited datasets encountered in tomographic measurements.

Beginning with fundamental statistical concepts, the initial chapters introduce key ideas in decision theory and counting statistics, emphasizing models relevant to photon-limited data and the application of Poisson approximations. Following this foundational discourse, the text explores advanced computational techniques such as Monte Carlo methods and Markov chain Monte Carlo (MCMC) approaches for posterior analysis, providing a robust framework for understanding nuclear imaging modalities, including Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET).

The concluding chapter is rich with illustrative case studies of statistical computing, utilizing Poisson-multinomial statistics. It includes practical examples that demonstrate the calculation of Bayes factors, assessment of risks, and methodologies for Bayesian decision-making and hypothesis testing. In addition, the appendices offer invaluable resources such as probability distribution tables, key elements of set theory, analysis of multinomial distributions in single-voxel imaging, and detailed derivations of sampling distribution ratios. For added utility, C++ code snippets featured in the final chapter enhance hands-on understanding and practical application.

This ebook is designed to serve not only as a textbook for students and researchers seeking a firm grounding in Bayesian statistics and its application to medical imaging but also as a definitive reference for a diverse audience. Mathematicians, physicists, engineers, and computer scientists will find it an indispensable resource. Moreover, seasoned scientists and researchers in the field of nuclear imaging data analysis will benefit significantly, particularly those unfamiliar with Bayesian frameworks.

In summary, Statistical Computing in Nuclear Imaging (PDF) is an essential read for anyone looking to enhance their knowledge and skills at the intersection of statistical computing and nuclear imaging technologies.

ISBN: 978-3-16-148410-0, 978-1-234-56789-7