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Proceedings Paper

Evaluation of a level set segmentation method for cardiac ultrasound images
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Paper Abstract

This paper evaluates the quality of segmentation achieved by a level set evolution strategy call Tunneling Descent. Level sets often evolve and become stationary at the nearest local minimum of an energy function. A comparison of the local level set minimum with a global minimum is important for many applications. This is especially true of ultrasound segmentation where ultrasound speckle can introduce many local minima which trap the level set. In this paper, we compare the quality of the level set segmentation with the quality of segmentation achieved by (1) simulated annealing (with three different cooling schedules), and (2) random sampling, and (3) three experts (manual segmentation). Simulated annealing and random sampling offer global minimization. In this paper, the quality of the segmentation is compared for 21 clinically-obtained images. The comparison is carried out using two performance measures: the amount by which the global minimizers can further decrease the level set energy, and the contour distance between the segmentations themselves. The results show that level set segmentation is within one ultrasound resolution cell of the global minimum. The results also show that the level set segmentation is quite close to manual segmentation.

Paper Details

Date Published: 10 March 2008
PDF: 8 pages
Proc. SPIE 6920, Medical Imaging 2008: Ultrasonic Imaging and Signal Processing, 69200E (10 March 2008); doi: 10.1117/12.770392
Show Author Affiliations
Yong Yue, Yale Univ. (United States)
Hemant D. Tagare, Yale Univ. (United States)

Published in SPIE Proceedings Vol. 6920:
Medical Imaging 2008: Ultrasonic Imaging and Signal Processing
Stephen A. McAleavey; Jan D'hooge, Editor(s)

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