Quantifying white matter lesions with MRI using finite mixture density and 2D clustering estimation

William H. Hinson; Howard Donald Gage; Dixon M. Moody; Peter Santago II

doi:10.1117/12.175077

11 May 1994 Quantifying white matter lesions with MRI using finite mixture density and 2D clustering estimation

William H. Hinson, Howard Donald Gage, Dixon M. Moody, Peter Santago II

Proceedings Volume 2167, Medical Imaging 1994: Image Processing; (1994) https://doi.org/10.1117/12.175077
Event: Medical Imaging 1994, 1994, Newport Beach, CA, United States

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.

Citation Download Citation

William H. Hinson, Howard Donald Gage, Dixon M. Moody, and Peter Santago II "Quantifying white matter lesions with MRI using finite mixture density and 2D clustering estimation", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175077

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