Topology correction in brain cortex segmentation using a multiscale, graph-based algorithm

Xiao Han; Chenyang Xu; Ulisses Braga-Neto; Jerry L Prince

doi:10.1109/42.993130

Topology correction in brain cortex segmentation using a multiscale, graph-based algorithm

IEEE Trans Med Imaging. 2002 Feb;21(2):109-21. doi: 10.1109/42.993130.

Authors

Xiao Han¹, Chenyang Xu, Ulisses Braga-Neto, Jerry L Prince

Affiliation

¹ Center for Imaging Science, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

PMID: 11929099
DOI: 10.1109/42.993130

Abstract

Reconstructing an accurate and topologically correct representation of the cortical surface of the brain is an important objective in various neuroscience applications. Most cortical surface reconstruction methods either ignore topology or correct it using manual editing or methods that lead to inaccurate reconstructions. Shattuck and Leahy recently reported a fully automatic method that yields a topologically correct representation with little distortion of the underlying segmentation. We provide an alternate approach that has several advantages over their approach, including the use of arbitrary digital connectivities, a flexible morphology-based multiscale approach, and the option of foreground-only or background-only correction. A detailed analysis of the method's performance on 15 magnetic resonance brain images is provided.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.
Research Support, U.S. Gov't, P.H.S.

MeSH terms

Algorithms*
Cerebral Cortex / anatomy & histology
Computer Simulation
Humans
Image Processing, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging / methods
Models, Neurological*
Models, Statistical*
Pattern Recognition, Automated
Reproducibility of Results
Sensitivity and Specificity

Grants and funding

R01NS37747/NS/NINDS NIH HHS/United States