Share Email Print

Proceedings Paper

Efficient optimal surface detection: theory, implementation, and experimental validation
Author(s): Kang Li; Xiaodong Wu; D. Zhixiang Chen; Milan Sonka
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, a novel polynomial-time algorithm is described for solving the optimal net surface detection problem on proper ordered multi-column graphs in N-D space (N ≥ 3). The method is applied to searching for optimal object boundaries with arbitrary smoothness constraints in volumetric medical images. By simple transformations, such optimal surface detection problems can be simplified to a problem of computing the minimum s-t cuts in the transformed graphs. An efficient implementation for the 3-D case that can achieve near real-time performance on moderate-sized datasets is presented. We further examine our technique in experiments by segmenting the cylindrical surfaces of human airways from pulmonary volumetric CT images, and compare the results to those produced by previous methods. By allowing full specifications of the cost-function and smoothness constraints without degrading the performance, the new algorithm is more flexible than traditional methods and guarantees global optimality. The multi-dimensional nature of the algorithm maintains continuity in higher dimensions.

Paper Details

Date Published: 12 May 2004
PDF: 8 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.537048
Show Author Affiliations
Kang Li, Univ. of Iowa (United States)
Xiaodong Wu, Univ. of Texas/Pan American (United States)
D. Zhixiang Chen, Univ. of Notre Dame (United States)
Milan Sonka, Univ. of Iowa (United States)

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

© SPIE. Terms of Use
Back to Top