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Proceedings Paper

Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1000 studies
Author(s): Jayaram K. Udupa; Laszlo G. Nyul; Yulin Ge; Robert I. Grossman
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Paper Abstract

Multiple Sclerosis (MS) is an acquired disease of the central nervous system. Subjective cognitive and ambulatory test scores on a scale called EDSS are currently utilized to assess the disease severity. Various MRI protocols are being investigated to study the disease based on how it manifests itself in the images. In an attempt to eventually replace EDSS by an objective measure to assess the natural course of the disease and its response to therapy, we have developed image segmentation methods based on fuzzy connectedness to quantify various objects in multiprotocol MRI. These include the macroscopic objects such as lesions, the gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and brain parenchyma as well as the microscopic aspects of the diseased WM. Over 1000 studies have been processed to date. By far the strongest correlations with the clinical measures were demonstrated by the Magnetization Transfer Ratio (MTR) histogram parameters obtained for the various segmented tissue regions emphasizing the importance of considering the microscopic/diffused nature of the disease in the individual tissue regions. Brain parenchymal volume also demonstrated a strong correlation with the clinical measures indicating that brain atrophy is an important indicator of the disease. Fuzzy connectedness is a viable segmentation method for studying MS.

Paper Details

Date Published: 6 June 2000
PDF: 11 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387606
Show Author Affiliations
Jayaram K. Udupa, Univ. of Pennsylvania (United States)
Laszlo G. Nyul, Univ. of Pennsylvania (Hungary)
Yulin Ge, Univ. of Pennsylvania (United States)
Robert I. Grossman, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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