Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging.

Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging. Research Abstract Details 

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Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging. Abstract Text:

I Bloch,F Preteux,E A Cabanis,M T Iba-Zizen,C Bourgoin,J Tamraz,

An original method of image analysis has been developed, using 'mathematical morphology', in order to detect brain tumors at magnetic resonance imaging of the head following injection of gadolinium-DPTA. The main steps of the analysis are as follows: 1) Spatial reduction by automatic determination of a region of interest, 2) elimination of noise by morphologic filtering (increasing alternate closing-opening sequence), 3) localization of tumor by searching for r-h maxima, and 4) extraction of tumor contours using three-dimensional structuring elements. The preliminary results of this automatic and robust method encourage further studies of the potential of tissue analysis as an aid to tumor diagnosis.

Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging. Publishing Authors By Initials

I Bloch,F Preteux,EA Cabanis,MT Iba-Zizen,C Bourgoin,J Tamraz,

For similar natural sciences: mathematics research abstracts see: natural sciences: mathematics research

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Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Acta radiologica. Supplementum

VOLUME: 369

Page Numbers: 481-2

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ISSN: 0001-6926

DAY: 20

MONTH: 02

YEAR: 1986

Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging. Information

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LANGUAGE: eng

NlmUniqueID: 370370

Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging. Keywords Mesh Terms:

KEYWORDS: Mathematics

MESH TERMS: methods

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Grant and Affiliation Information for Mathematical morphology for automatic detection of brain lesions at magnetic resonance imaging.

AFFILIATION: Centre de Morphologie Mathématique, Ecole Nationale Supérieure des Mines de Paris, France.

Country: SWEDEN

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MEDLINETA: Acta Radiol Suppl

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