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Proceedings Paper

Brain tissue classification from MRI data by means of texture analysis
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Paper Abstract

The new magnetic resonance imaging systems (MRI) are able to perform a brain scan with fairly good three-dimensional resolution. In order to allow the physician, and especially the neuroanatomist, to deal with the prime information borne by the images, the prevalent data have to be enhanced with regards to the medical objective. The aim of the work presented in this paper is to recognize and to label the head structures from MR images. This is done by computing probabilities for a pixel to belong to pre-specified head structures (i.e., skin, bone, CSF, ventricular system, grey and white matter, and brain). Several ways are presented and discussed in this paper, including the computation of statistical properties like `Markov parameters' and `fractal dimension.' From these statistical parameters, computed from a single MR image or a 3-D isotropic MR database, clustering and classification processes are used to issue fuzzy membership coefficients representing the probabilities for a pixel to belong to a particular structure. Improvements are proposed with regard to the expressed choices and examples are presented.

Paper Details

Date Published: 1 June 1992
PDF: 12 pages
Proc. SPIE 1652, Medical Imaging VI: Image Processing, (1 June 1992); doi: 10.1117/12.59413
Show Author Affiliations
Frederic Lachmann, Pontchaillou Hospital (France)
Christian Barillot, Pontchaillou Hospital (France)

Published in SPIE Proceedings Vol. 1652:
Medical Imaging VI: Image Processing
Murray H. Loew, Editor(s)

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