Automated segmentation of multiple sclerosis lesions by model outlier detection.

Automated segmentation of multiple sclerosis lesions by model outlier detection.

This paper presents a fully automated algorithm for segmentation of multiple sclerosis (MS) lesions from multispectral magnetic resonance (MR) images. The method performs intensity-based tissue classification using a stochastic model for normal brain images and simultaneously detects MS lesions as o...

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Pubblicato in:IEEE Transactions on medical imaging 20, 8 (2001).
Autore principale: Van Leemput, K.
Natura: Articolo
Lingua:English
Soggetti:
MR field inhomogeneities correction.
Markov random field.
Automatic measurements.
Digital brain atlas.
Expert measurements.
Fully automated algorithm.
Intensity-based tissue classification.
Lesion load correlation.
Medical diagnostic imaging.
Multispectral magnetic resonance images.
Normal brain images.
Stochastic model.
Tissue-specific intensity models.