title: Conformal metric optimization on surface (CMOS) for deformation and mapping in Laplace-Beltrami embedding space.
abstract: In this paper we develop a novel technique for surface deformation and mapping in the high-dimensional Laplace-Beltrami embedding space. The key idea of our work is to realize surface deformation in the embedding space via optimization of a conformal metric on the surface. Numerical techniques are developed for computing derivatives of the eigenvalues and eigenfunctions with respect to the conformal metric, which is then applied to compute surface maps in the embedding space by minimizing an energy function. In our experiments, we demonstrate the robustness of our method by applying it to map hippocampal atrophy of multiple sclerosis patients with depression on a data set of 109 subjects. Statistically significant results have been obtained that show excellent correlation with clinical variables. A comparison with the popular SPHARM tool has also been performed to demonstrate that our method achieves more significant results.
authors: Lab of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.
authors: Yonggang
authors: Y
authors: Shi
authors: Rongjie
authors: R
authors: Lai
authors: Raja
authors: R
authors: Gill
authors: Daniel
authors: D
authors: Pelletier
authors: David
authors: D
authors: Mohr
authors: Nancy
authors: N
authors: Sicotte
authors: Arthur W
authors: AW
authors: Toga
mesh_terms: D000465:Algorithms; D001284:Atrophy; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003863:Depression / Q000150:complications; D005260:Female; D006624:Hippocampus / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D009103:Multiple Sclerosis / Q000150:complications / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods