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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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Published in: | Stroke (1970) 2002-12, Vol.33 (12), p.2839-2844 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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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 ( |
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ISSN: | 0039-2499 1524-4628 |
DOI: | 10.1161/01.STR.0000043072.76353.7C |