Statistical Computing in Nuclear Imaging

Statistical Computing in Nuclear Imaging, 1st Edition, is a textbook that focuses on computational aspects of Bayesian data analysis for photon-limited data gathered in tomographic nuclear imaging measurements. The volume is part of the Series in Medical Physics and Biomedical Engineering.

Coverage introduces fundamental Bayesian statistical concepts, decision theory, and counting statistics, including models for photon-limited data and Poisson approximations. It also examines posterior analysis using Monte Carlo methods and Markov chains alongside nuclear imaging applications such as PET and SPECT.

The work is designed for physicists, mathematicians, engineers, and computer scientists studying medical imaging. It also serves practitioners of nuclear imaging data analysis, including researchers and established scientists who are new to Bayesian methods.