Abstract：
:Analysis of cortical patterns requires accurate cortical surface registration. Many researchers map the cortical surface onto a unit sphere and perform registration of two images defined on the unit sphere. Here we have developed a novel registration framework for the cortical surface based on spherical thin-plate splines. Small-scale composition of spherical thin-plate splines was used as the geometric interpolant to avoid folding in the geometric transform. Using an automatic algorithm based on anisotropic skeletons, we extracted seven sulcal lines, which we then incorporated as landmark information. Mean curvature was chosen as an additional feature for matching between spherical maps. We employed a two-term cost function to encourage matching of both sulcal lines and the mean curvature between the spherical maps. Application of our registration framework to fifty pairwise registrations of T1-weighted MRI scans resulted in improved registration accuracy, which was computed from sulcal lines. Our registration approach was tested as an additional procedure to improve an existing surface registration algorithm. Our registration framework maintained an accurate registration over the sulcal lines while significantly increasing the cross-correlation of mean curvature between the spherical maps being registered.
journal_name
J Neurosci Methodsjournal_title
Journal of neuroscience methodsauthors
Park H,Park JS,Seong JK,Na DL,Lee JMdoi
10.1016/j.jneumeth.2012.02.010subject
Has Abstractpub_date
2012-04-30 00:00:00pages
46-53issue
1eissn
0165-0270issn
1872-678Xpii
S0165-0270(12)00054-4journal_volume
206pub_type
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