MBIS: Multivariate Bayesian Image Segmentation tool

MBIS: Multivariate Bayesian Image Segmentation tool

We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an e...

Fully Bayesian Image Segmentation An

Developments in Markov Chain Monte Carlo procedures have made it possible to perform fully Bayesian image seg-mentation. By this we mean that all the parameters are treated identically, be they the segmentation labels, the class parameters or the Markov Random Field prior parameters. We perform the analysis by sampling from the posterior distribution of all the parameters. Sampling from the MRF...

Multivariate Image Analysis and Segmentation in Microanalysis

Instruments for microanalysis are now able to provide several images of the same specimen area. In this paper, two groups of methods are described for handling these multivariate maps. One group concerns dimensionality reduction, i.e., the projection of N-dimensional data sets onto a M-dimensional parameter space (M<N). It is shown that, in addition to linear mapping which can be performed by M...

PMOD Image Segmentation Tool (PSEG)

PMOD Image Segmentation Tool (PSEG)