1st Edition

Statistical Computing in Nuclear Imaging

By Arkadiusz Sitek Copyright 2015
275 Pages
by CRC Press

275 Pages 76 B/W Illustrations
by CRC Press

275 Pages
by CRC Press

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... Read more

Basic Statistical Concepts. Elements of Decision Theory. Counting Statistics. Monte Carlo Methods in Posterior Analysis. Basics of Nuclear Imaging. Statistical Computing. Appendix A Probability Distributions. Appendix B Elements of Set Theory. Appendix C Multinomial Distribution of Single-Voxel Imaging. Appendix D Derivations of Sampling Distribution Ratios. Appendix E Equation (6.11). Appendix F C++ Code of the OE Algorithm for STS. References.

Biography

Arkadiusz Sitek is an associate physicist at Massachusetts General Hospital in Boston and an assistant professor at Harvard Medical School. He received his doctorate from the University of British Columbia in Canada and since 2001 has worked as a nuclear imaging scientist in the Lawrence Berkeley National Laboratory, Beth Israel Medical Center, and Brigham and Women’s Hospital before joining Massachusetts General Hospital. He has authored more than 100 scientific journal and proceedings papers, book chapters, and patents, and served as a principal investigator on nuclear imaging research projects. Dr. Sitek is a practitioner of the Bayesian school of thought and a member of the International Society for Bayesian Analysis.