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Proceedings Paper

Edge completion from sparse data: a level-set approach
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Paper Abstract

Intensity differences between objects are often used for segmentation. In an ideal situation, these differences permit the computation of edges that form complete contours around objects in the image. However, edges found in real images are usually a set of real and spurious disconnected boundary segments. Even more challenging are those so called apparent or subjective contours whose boundary are not defined by intensity or texture variations. In this paper, we present a novel method to segment and reconstruct images with missing boundaries, including images with large missing edges commonly found in ultrasound imaging. We test our algorithm on classic synthetic images, phantom images and on real ultrasound images of the bladder, heart, and colon.

Paper Details

Date Published: 12 May 2004
PDF: 11 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.533303
Show Author Affiliations
Zhujiang Cao, Vanderbilt Univ. (United States)
Benoit M. Dawant, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)

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