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Proceedings Paper

Method for quantitative assessment of atherosclerotic lesion burden on the basis of high-resolution black-blood MRI
Author(s): Jeffrey Duda; Hee Kwon Song; Ronald Wolf; Alex Wright; James C. Gee; Felix W. Wehrli
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Paper Abstract

The aim of this work was to develop a reliable semi-automatic method for quantifying carotid atherosclerotic lesion burden using black-blood high-resolution MR images. Vessel wall volume was quantified by measuring its cross-sectional area in adjacent slices. Two methods for obtaining this measure are presented. The first method approximates the outer boundary of the vessel on a slice-by-slice basis by fitting an ellipse to user-identified points and automatically identifying the lumen through examination of the histogram obtained from a local region of interest (ROI). The second, method identifies the lumen and wall throughout the entire volume based upon user-selected points in a single slice. Radially directed intensity profiles are examined in order to automatically locate points on the outer boundary, and the same histogram-based method is used for lumen delineation. The measure of wall area provided by the manual outer boundary selection has an intra-class correlation coefficient (ICC) of 0.83 for test-retest comparisons, but the ICC values for the inter-observer comparisons (0.84, 0.65) suggest that user bias remains a potential source of error. A susceptibility to low image signal-to-noise ratio (SNR) may present a limitation on the usefulness of the automated outer boundary selection method for use on whole image volumes.

Paper Details

Date Published: 9 May 2002
PDF: 9 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467154
Show Author Affiliations
Jeffrey Duda, Univ. of Pennsylvania (United States)
Hee Kwon Song, Univ. of Pennsylvania (United States)
Ronald Wolf, Univ. of Pennsylvania (United States)
Alex Wright, Univ. of Pennsylvania (United States)
James C. Gee, Univ. of Pennsylvania (United States)
Felix W. Wehrli, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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