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Proceedings Paper

Detection and quantification of MS lesions using fuzzy topological principles
Author(s): Jayaram K. Udupa; Luogang Wei; Supun Samarasekera; Yukio Miki; M. A. van Buchem; Robert I. Grossman
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Paper Abstract

Quantification of the severity of the multiple sclerosis (MS) disease through estimation of lesion volume via MR imaging is vital for understanding and monitoring the disease and its treatment. This paper presents a novel methodology and a system that can be routinely used for segmenting and estimating the volume of MS lesions via dual-echo spin-echo MR imagery. An operator indicates a few points in the images by pointing to the white matter, the gray matter, and the CSF. Each of these objects is then detected as a fuzzy connected set. The holes in the union of these objects correspond to potential lesion sites which are utilized to detect each potential lesion as a fuzzy connected object. These 3D objects are presented to the operator who indicates acceptance/rejection through the click of a mouse button. The volume of accepted lesions is then computed and output. Based on several evaluation studies and over 300 3D data sets that were processed, we conclude that the methodology is highly reliable and consistent, with a coefficient of variation (due to subjective operator actions) of less than 1.0% for volume.

Paper Details

Date Published: 16 April 1996
PDF: 11 pages
Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); doi: 10.1117/12.237902
Show Author Affiliations
Jayaram K. Udupa, Univ. of Pennsylvania (United States)
Luogang Wei, Univ. of Pennsylvania (United States)
Supun Samarasekera, Univ. of Pennsylvania (United States)
Yukio Miki, Univ. of Pennsylvania (United States)
M. A. van Buchem, Univ. of Pennsylvania (United States)
Robert I. Grossman, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 2710:
Medical Imaging 1996: Image Processing
Murray H. Loew; Kenneth M. Hanson, Editor(s)

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