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Proceedings Paper

Development and evaluation of a semiautomatic 3D segmentation technique of the carotid arteries from 3D ultrasound images
Author(s): Jeremy D. Gill; Hanif M. Ladak; David A. Steinman; Aaron Fenster
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Paper Abstract

In this paper, we report on a semi-automatic approach to segmentation of carotid arteries from 3D ultrasound (US) images. Our method uses a deformable model which first is rapidly inflated to approximately find the boundary of the artery, then is further deformed using image-based forces to better localize the boundary. An operator is required to initialize the model by selecting a position in the 3D US image, which is within the carotid vessel. Since the choice of position is user-defined, and therefore arbitrary, there is an inherent variability in the position and shape of the final segmented boundary. We have assessed the performance of our segmentation method by examining the local variability in boundary shape as the initial selected position is varied in a freehand 3D US image of a human carotid bifurcation. Our results indicate that high variability in boundary position occurs in regions where either the segmented boundary is highly curved, or the 3D US image has poorly defined vessel edges.

Paper Details

Date Published: 21 May 1999
PDF: 8 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348576
Show Author Affiliations
Jeremy D. Gill, John P. Robarts Research Institute and Univ. of Western Ontario (Canada)
Hanif M. Ladak, John P. Robarts Research Institute (Canada)
David A. Steinman, John P. Robarts Research Institute and Univ. of Western Ontario (Canada)
Aaron Fenster, John P. Robarts Research Institute and Univ. of Western Ontario (Canada)

Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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