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Proceedings Paper

Integrating region growing and edge detection using regularization
Author(s): Vikram Chalana; Wendy Swan Costa; Yongmin Kim
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Paper Abstract

We propose a segmentation approach which integrates region growing and edge detection in a regularization framework. Our method is a modified active contour model and uses region statistics in addition to gradient information. We formulate the active contour model using a Bayesian approach. We have implemented this integrated approach and characterized its performance on synthetic images and on 36 short-axis cardiac ultrasound images. The resulting boundaries are compared to true boundaries in the case of the synthetic images and to manually outlined boundaries in the case of ultrasound images. The results are also compared with those obtained using the balloon force to expand the active contour model. We found that our integrated algorithm detects boundaries more accurately than the active contour method using a balloon force. Furthermore, the integrated algorithm is less sensitive to the placement of the initial contour inside the LV cavity than the active contour algorithm using a balloon force.

Paper Details

Date Published: 12 May 1995
PDF: 10 pages
Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); doi: 10.1117/12.208697
Show Author Affiliations
Vikram Chalana, Univ. of Washington (United States)
Wendy Swan Costa, Univ. of Washington (United States)
Yongmin Kim, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 2434:
Medical Imaging 1995: Image Processing
Murray H. Loew, Editor(s)

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