Fast 3D brain segmentation using dual-front active contours with optional user-interaction

Hua Li, Anthony Yezzi, Laurent D. Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

Important attributes of 3D brain segmentation algorithms include robustness, accuracy, computational efficiency, and facilitation of user interaction, yet few algorithms incorporate all of these traits. Manual segmentation is highly accurate but tedious and laborious. Most automatic techniques, while less demanding on the user, are much less accurate. It would be useful to employ a fast automatic segmentation procedure to do most of the work but still allow an expert user to interactively guide the segmentation to ensure an accurate final result. We propose a novel 3D brain cortex segmentation procedure utilizing dual-front active contours, which minimize image-based energies in a manner that yields more global minimizers compared to standard active contours. The resulting scheme is not only more robust but much faster and allows the user to guide the final segmentation through simple mouse clicks which add extra seed points. Due to the global nature of the evolution model, single mouse clicks yield corrections to the segmentation that extend far beyond their initial locations, thus minimizing the user effort. Results on 15 simulated and 20 real 3D brain images demonstrate the robustness, accuracy, and speed of our scheme compared with other methods.

Original languageEnglish
Title of host publicationComputer Vision for Biomedical Image Applications - First International Workshop, CVBIA 2005, Proceedings
Pages335-345
Number of pages11
StatePublished - Dec 1 2005
Event1st International Workshop on Computer Vision for Biomedical Image Applications, CVBIA 2005 - Beijing, China
Duration: Oct 21 2005Oct 21 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3765 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Computer Vision for Biomedical Image Applications, CVBIA 2005
CountryChina
CityBeijing
Period10/21/0510/21/05

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    Li, H., Yezzi, A., & Cohen, L. D. (2005). Fast 3D brain segmentation using dual-front active contours with optional user-interaction. In Computer Vision for Biomedical Image Applications - First International Workshop, CVBIA 2005, Proceedings (pp. 335-345). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3765 LNCS).