Paper
12 May 1995 Integrating region growing and edge detection using regularization
Vikram Chalana, Wendy Swan Costa, Yongmin Kim
Author Affiliations +
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vikram Chalana, Wendy Swan Costa, and Yongmin Kim "Integrating region growing and edge detection using regularization", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); https://doi.org/10.1117/12.208697
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CITATIONS
Cited by 11 scholarly publications.
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KEYWORDS
Image segmentation

Data modeling

Sensors

Edge detection

Statistical modeling

Echocardiography

Image processing

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