This paper has reviewed, with somewhat variable coverage, the nine MR image
segmentation techniques itemized in Table II. A wide array of approaches have been …

The current literature on MRI segmentation methods is reviewed. Particular emphasis is
placed on the relative merits of single image versus multispectral segmentation, and …

A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data
is described that achieves high performance without requiring a model of the tissue classes …

A statistical model is presented that represents the distributions of major tissue classes in
single-channel magnetic resonance (MR) cerebral images. Using the model, cerebral …

A system that automatically segments and labels glioblastoma-multiforme tumors in
magnetic resonance images (MRIs) of the human brain is presented. The MRIs consist of T1 …

Presents a new approach to the correction of intensity inhomogeneities in magnetic
resonance imaging (MRI) that significantly improves intensity-based tissue segmentation …

Magnetic resonance (MR) brain section images are segmented and then synthetically
colored to give visual representations of the original data with three approaches: the literal …

Tumor segmentation from magnetic resonance (MR) images may aid in tumor treatment by
tracking the progress of tumor growth and/or shrinkage. In this paper we present the first …

This paper presents a review of methods and techniques that have been proposed for the
segmentation of magnetic resonance (MR) images of the brain, with a special emphasis on …

The authors present a new algorithm for identifying the distribution of different material types
in volumetric datasets such as those produced with magnetic resonance imaging (MRI) or …