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Proceedings Paper

Affinity-based constraint optimization for nearly-automatic vessel segmentation
Author(s): O. Cooper; M. Freiman; L. Joskowicz; D. Lischinski
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Paper Abstract

We present an affinity-based optimization method for nearly-automatic vessels segmentation in CTA scans. The desired segmentation is modeled as a function that minimizes a quadratic affinity-based functional. The functional incorporates intensity and geometrical vessel shape information and a smoothing constraint. Given a few user-defined seeds, the minimum of the functional is obtained by solving a single set of linear equations. The binary segmentation is then obtained by applying a user-selected threshold. The advantages of our method are that it requires fewer initialization seeds, is robust, and yields better results than existing graph-based interactive segmentation methods. Experimental results on 20 vessel segments including the carotid arteries bifurcation and noisy parts of the carotid yield a mean symmetric surface error of 0.54mm (std=0.28).

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76230O (12 March 2010); doi: 10.1117/12.841245
Show Author Affiliations
O. Cooper, The Hebrew Univ. of Jerusalem (Israel)
M. Freiman, The Hebrew Univ. of Jerusalem (Israel)
L. Joskowicz, The Hebrew Univ. of Jerusalem (Israel)
D. Lischinski, The Hebrew Univ. of Jerusalem (Israel)

Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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