Generalized surface flows for deformable registration and cortical matching.
Despite being routinely required in medical applications, deformable surface registration is notoriously difficult due to large intersubject variability and complex geometry of most medical datasets. We present a general and flexible deformable matching framework based on generalized surface flows that efficiently tackles these issues through tailored deformation priors and multiresolution computations. The value of our approach over existing methods is demonstrated for automatic and user-guided cortical registration.
Department of Computer Science, University of Southern California, USA.
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I
Eckstein
A A
AA
Joshi
C C J
CC
Kuo
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R
Leahy
M
M
Desbrun
D000465:Algorithms; D002540:Cerebral Cortex / Q000033:anatomy & histology*; D003198:Computer Simulation; 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*; D008954:Models, Biological; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique