A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom.
Cortical surface reconstruction is important for functional brain mapping and morphometric analysis of the brain cortex. Several methods have been developed for the faithful reconstruction of surface models which represent the true cortical surface in both geometry and topology. However, there has been no explicit comparison study among those methods because each method has its own procedures, file formats, coordinate systems, and use of the reconstructed surface. There has also been no explicit evaluation method except visual inspection to validate the whole-cortical surface models quantitatively. In this study, we presented a novel phantom-based validation method of the cortical surface reconstruction algorithm and quantitatively cross-validated the three most prominent cortical surface reconstruction algorithms which are used in Freesurfer, BrainVISA, and CLASP, respectively. The validation included geometrical accuracy and mesh characteristics such as Euler number, fractal dimension (FD), total surface area, and local density of points. CLASP showed the best geometric/topologic accuracy and mesh characteristics such as FD and total surface area compared to Freesurfer and BrainVISA. In the validation of local density of points, Freesurfer and BrainVISA showed more even distribution of points on the cortical surface compared to CLASP.
Lee
Jun Ki
JK
Department of Biomedical Engineering, Hanyang University, 17 Haengdang-dong Sungdong-gu P.O. Box 55, Seoul 133-791, Republic of Korea.
Lee
Jong-Min
JM
Kim
June Sic
JS
Kim
In Young
IY
Evans
Alan C
AC
Kim
Sun I
SI
D000465:Algorithms; D002540:Cerebral Cortex / Q000033:anatomy & histology*; D007839:Functional Laterality; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D010841:Pia Mater / Q000033:anatomy & histology; D015203:Reproducibility of Results