In this paper, a new local Chan–Vese (LCV) model is proposed for image segmentation,
which is built based on the techniques of curve evolution, local statistical function and level …

This paper is dedicated to the statistical analysis of the space of multivariate normal
distributions with an application to the processing of Diffusion Tensor Images (DTI). It relies …

We propose an active contour model using an external force field that is based on
magnetostatics and hypothesized magnetic interactions between the active contour and …

In recent years, diffusion tensor imaging (DTI) has become a popular in vivo diagnostic
imaging technique in Radiological sciences. In order for this imaging technique to be more …

This paper presents a novel level set method for complex image segmentation, where the
local statistical analysis and global similarity measurement are both incorporated into the …

Divergence measures provide a means to measure the pairwise dissimilarity between
“objects,” eg, vectors and probability density functions (pdfs). Kullback-Leibler (KL) …

In this paper, we propose an interactive color natural image segmentation method. The
method integrates color feature with multiscale nonlinear structure tensor texture (MSNST) …

We address the problem of the segmentation of cerebral white matter structures from
diffusion tensor images (DTI). A DTI produces, from a set of diffusion-weighted MR images …

This paper presents a new region-based unified tensor level set model for image
segmentation. This model introduces a three-order tensor to comprehensively depict …

In this article, we review recent mathematical models and computational methods for the
processing of diffusion Magnetic Resonance Images, including state-of-the-art …