title: Brain image registration using cortically constrained harmonic mappings.
abstract: Volumetric registration of brains is required for inter-subject studies of functional and anatomical data. Intensity-driven registration typically results in some degree of misalignment of cortical and gyral folds. Increased statistical power in group studies may be achieved through improved alignment of cortical areas by using sulcal landmarks. In this paper we describe a new volumetric registration method in which cortical surfaces and sulcal landmarks are accurately aligned. We first compute a one-to-one map between the two cortical surfaces constrained by a set of user identified sulcal curves. We then extrapolate this mapping from the cortical surface to the entire brain volume using a harmonic mapping procedure. Finally, this volumetric mapping is refined using an intensity driven linear elastic registration. The resulting maps retain the one-to-one correspondence between cortical surfaces while also aligning volumetric features via the intensity-driven registration. We evaluate performance of this method in comparison to other volumetric registration methods.
authors.affiliation: Signal and Image Processing Institute, University of Southern California, Los Angeles 90089, USA. ajoshi@sipi.usc.edu
authors.forename: Anand
authors.initials: A
authors.lastname: Joshi
authors.forename: David
authors.initials: D
authors.lastname: Shattuck
authors.forename: Paul
authors.initials: P
authors.lastname: Thompson
authors.forename: Richard
authors.initials: R
authors.lastname: Leahy
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique