In emission tomography statistically based iterative methods can improve image quality
relative to analytic image reconstruction through more accurate physical and statistical …

Monte Carlo techniques have become popular in different areas of medical physics with
advantage of powerful computing systems. In particular, they have been extensively applied …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

The concept of prior probability for signals plays a key role in the successful solution of many
inverse problems. Much of the literature on this topic can be divided between analysis …

The problem of forming cross-sectional or tomographic images of the attenuation
characteristics of objects arises in a variety of contexts, including medical X-ray computed …

Positron emission tomography is a medical imaging modality for producing 3D images of the
spatial distribution of biochemical tracers within the human body. The images are …

Batteries are promising sources of green and sustainable energy that have been widely
used in various applications. Battery modelling as the basis of battery management system …

▪ Abstract Digital image reconstruction is a robust means by which the underlying images
hidden in blurry and noisy data can be revealed. The main challenge is sensitivity to …

We propose a new approach for image segmentation based on a hierarchical and spatially
variant mixture model. According to this model, the pixel labels are random variables and a …

Markov random fields (MRFs) have been widely used to model images in Bayesian
frameworks for image reconstruction and restoration. Typically, these MRF models have …