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Proceedings Paper

Quantifying white matter lesions with MRI using finite mixture density and 2D clustering estimation
Author(s): William H. Hinson; Howard Donald Gage; Dixon M. Moody; Peter Santago
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Paper Abstract

Research is presented in which white matter lesions are quantified using MRI data on cardiac surgery patients. Various methods of quantification are presented including finite mixture density analysis of various MRI parameters, K-means, and principal components analysis. Pre- and post-operative data sets are studied for each patient to determine the change in lesion load due to surgery. The various methods are compared and the differences are indicated on both registered and unregistered data sets. Agreement among the methods is not good in many instances and at times show an inverse correlation. Images and data showing the gray scale distributions are presented.

Paper Details

Date Published: 11 May 1994
PDF: 7 pages
Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); doi: 10.1117/12.175077
Show Author Affiliations
William H. Hinson, Bowman Gray School of Medicine/Wake Forest Univ. (United States)
Howard Donald Gage, Bowman Gray School of Medicine/Wake Forest Univ. (United States)
Dixon M. Moody, Bowman Gray School of Medicine/Wake Forest Univ. (United States)
Peter Santago, Bowman Gray School of Medicine/Wake Forest Univ. (United States)


Published in SPIE Proceedings Vol. 2167:
Medical Imaging 1994: Image Processing
Murray H. Loew, Editor(s)

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