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Multiparametric MRI ISODATA ischemic lesion Analysis: Correlation with the clinical neurological deficit and single-parameter MRI techniques

The purpose of this study was to show that the computer segmentation algorithm Iterative Self-Organizing Data Analysis Technique (ISODATA), which integrates multiple MRI parameters (diffusion-weighted imaging [DWI], T2-weighted imaging [T2WI], and T1-weighted imaging [T1WI]) into a single composite...

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Bibliographic Details
Published in:Stroke (1970) 2002-12, Vol.33 (12), p.2839-2844
Main Authors: MITSIAS, Panayiotis D, JACOBS, Michael A, HAMMOUD, Rabih, PASNOOR, Mamatha, SANTHAKUMAR, Sunitha, PAPAMITSAKIS, Nikolaos I. H, SOLTANIAN-ZADEH, Hamid, MEI LU, CHOPP, Michael, PATEL, Suresh C
Format: Article
Language:English
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Summary:The purpose of this study was to show that the computer segmentation algorithm Iterative Self-Organizing Data Analysis Technique (ISODATA), which integrates multiple MRI parameters (diffusion-weighted imaging [DWI], T2-weighted imaging [T2WI], and T1-weighted imaging [T1WI]) into a single composite image, is capable of defining the ischemic lesion in a time-independent manner equally as well as the MRI techniques considered the best for each phase after stroke onset (ie, perfusion weighted imaging [PWI] and DWI for the acute phase and T2WI for the outcome phase). We measured MRI parameters of PWI, DWI, T2WI, and T1WI from patients at the acute phase (
ISSN:0039-2499
1524-4628
DOI:10.1161/01.STR.0000043072.76353.7C