Abstract：
:Flat mapping based cortical surface registration constrained by manually traced sulcal curves has been widely used for inter subject comparisons of neuroanatomical data. Even for an experienced neuroanatomist, manual sulcal tracing can be quite time consuming, with the cost increasing with the number of sulcal curves used for registration. We present a method for estimation of an optimal subset of size N(C) from N possible candidate sulcal curves that minimizes a mean squared error metric over all combinations of N(C) curves. The resulting procedure allows us to estimate a subset with a reduced number of curves to be traced as part of the registration procedure leading to optimal use of manual labeling effort for registration. To minimize the error metric we analyze the correlation structure of the errors in the sulcal curves by modeling them as a multivariate Gaussian distribution. For a given subset of sulci used as constraints in surface registration, the proposed model estimates registration error based on the correlation structure of the sulcal errors. The optimal subset of constraint curves consists of the N(C) sulci that jointly minimize the estimated error variance for the subset of unconstrained curves conditioned on the N(C) constraint curves. The optimal subsets of sulci are presented and the estimated and actual registration errors for these subsets are computed.
journal_name
Neuroimagejournal_title
NeuroImageauthors
Joshi AA,Pantazis D,Li Q,Damasio H,Shattuck DW,Toga AW,Leahy RMdoi
10.1016/j.neuroimage.2009.12.064subject
Has Abstractpub_date
2010-04-15 00:00:00pages
950-9issue
3eissn
1053-8119issn
1095-9572pii
S1053-8119(09)01353-6journal_volume
50pub_type
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