In x-ray tomography, the structure of a three-dimensional body is reconstructed from a
collection of projection images of the body. Medical CT imaging does this using an extensive …

Bayesian inference applied to electrical capacitance tomography, or other inverse problems,
provides a framework for quantified model fitting. Estimation of unknown quantities of …

We present new methodology to extend hidden Markov models to the spatial domain, and
use this class of models to analyze spatial heterogeneity of count data on a rare …

Most statistical analyses of fMRI data assume that the nature, timing and duration of the
psychological processes being studied are known. However, in many areas of psychological …

A statistical approach, based on full range Gaussian Markov random field model, is
proposed for texture analysis such as texture characterization, unique representation …

In this paper, we propose a model for image segmentation based on a finite mixture of
Gaussian distributions. For each pixel of the image, prior probabilities of class memberships …

Purpose We present a probabilistic approach to medical image analysis that requires, and
makes use of, explicit prior information provided by a medical expert. Depending on the …

A vast literature has recently been concerned with the analysis of variation in disease counts
recorded across geographical areas with the aim of detecting clusters of regions with …

Unlike deterministic inversion methods, statistical approaches are capable of taking into
account inherent measurement and model uncertainties into the inverse problem solution in …

Over the last 30 years the use of statistical principles applied to image reconstruction
problems has progressed from its first tentative steps into a rigorous and mature area. This …