Format

Send to

Choose Destination
IEEE Trans Med Imaging. 1999 Oct;18(10):897-908.

Automated model-based tissue classification of MR images of the brain.

Author information

1
Medical Image Computing (Radiology-ESAT/PSI), Faculty of Medicine, University Hospital Gasthuisberg, Leuven, Belgium.

Abstract

We describe a fully automated method for model-based tissue classification of magnetic resonance (MR) images of the brain. The method interleaves classification with estimation of the model parameters, improving the classification at each iteration. The algorithm is able to segment single- and multispectral MR images, corrects for MR signal inhomogeneities, and incorporates contextual information by means of Markov random Fields (MRF's). A digital brain atlas containing prior expectations about the spatial location of tissue classes is used to initialize the algorithm. This makes the method fully automated and therefore it provides objective and reproducible segmentations. We have validated the technique on simulated as well as on real MR images of the brain.

PMID:
10628949
DOI:
10.1109/42.811270
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for IEEE Engineering in Medicine and Biology Society
Loading ...
Support Center