Parameterization-Invariant Shape Comparisons of Anatomical Surfaces

—We consider 3D brain structures as continuous parameterized surfaces and present a metric for their comparisons that is invariant to the way they are parameterized. Past comparisons of such surfaces involve either volume deformations or non-rigid matching under fixed parameterizations of surfaces. We propose a new mathematical representation of surfaces, called q-maps, such that L2 distances between such maps are invariant to re-parameterizations. This property allows for removing the parameterization variability by optimizing over the reparameterization group, resulting in a proper parameterizationinvariant distance between shapes of surfaces. We demonstrate this method in shape analysis of multiple brain structures, for 34 subjects in the Detroit Fetal Alcohol and Drug Exposure Cohort study, which results in a 91% classification rate for ADHD (Attention Deficit Hyperactivity Disorder) cases and controls. This method outperforms some existing techniques such as SPHARM-PDM (spher...

• Type: Journal
• Year: 2011
• Where: TMI
• Authors: Sebastian Kurtek, Eric Klassen, Zhaohua Ding, Sandra Jacobson, Joseph Jacobson, Malcolm Avison, Anuj Srivastava
• Keywords: Iterative Closest Point, Spherical Harmonic Point, Surfaces, TMI 2011