Topology correction in brain cortex segmentation using a multiscale, graph-based algorithm.
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.
Han
Xiao
X
Center for Imaging Science, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Xu
Chenyang
C
Braga-Neto
Ulisses
U
Prince
Jerry L
JL
D000465:Algorithms; D002540:Cerebral Cortex / Q000033:anatomy & histology; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008959:Models, Neurological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity