Arkadiusz Sitek

Statistical Computing in Nuclear Imaging

• Broschiertes Buch

Produktbeschreibung

This book is highly focused on computational aspects of Bayesian data analysis of photon-limited data acquired in tomographic measurements in nuclear imaging. Basic Bayesian statistical concepts, elements of Bayesian decision theory, and counting statistics are discussed in the first chapters. Monte Carlo methods and Markov chains in posterior a

Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 275
• Erscheinungstermin: 31. März 2021
• Englisch
• Abmessung: 234mm x 156mm x 15mm
• Gewicht: 390g
• ISBN-13: 9780367783631
• ISBN-10: 0367783630
• Artikelnr.: 61210994

Autorenporträt

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.

Inhaltsangabe

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.