Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause
(s) of breast cancer still remains unknown. Early detection, precise identification of women at …

This paper describes an algorithm to segment mammo-graphic images into regions
corresponding to different densities. The breast parenchymal segmentation uses information …

Random walk is a popular and efficient algorithm for image segmentation, especially for
extracting regions of interest (ROIs). One difficulty with the random walk algorithm is the …

Several studies have showed that increased mammographic density is an important risk
factor for breast cancer. Dense tissue often appears as textured regions in mammograms, so …

Probability theory and statistics are two main tools in signal and image processing. Bayesian
inference has a privileged place in developing methods for inverse problems arising in …

Segmentation of video sequences requires the segmentations of consecutive frames to be
consistent with each other. We propose to use a three dimensional Conditional Random …

A background subtraction video segmentation algorithm that works by modelling the
different appearances of a pixel in a set of independent layers is proposed. The main …

We describe a new fully unsupervised image segmentation method based on a Bayesian
approach and a Potts-Markov random field (PMRF) model that are performed in the wavelet …

In this paper we apply multi-vector Hidden Markov Random Fields to tissue segmentation of
Magnetic Resonance (MR) breast images. Our proposed method performs segmentation …

Many image processing problems can be presented as inverse problems by modeling the
relation of the observed image to the unknown desired features explicitly. Some of these …