Laplace-Beltrami eigenfunction expansion of cortical manifolds

We represent a shape representation technique using the eigenfunctions of Laplace-Beltrami operator and compare the performance with the conventional spherical harmonic (SPHARM) representation. Cortical manifolds are represented as a linear combination of the Laplace-Beltrami eigenfunctions, which form orthonormal basis. Since the LaplaceBeltrami eigenfunctions reflect the intrinsic geometry of the manifolds, the new representation is supposed to more compactly represent the manifolds and outperform SPHARM representation. However, this is not demonstrated yet in brain imaging data. We demonstrate the superior reconstruction capability of the Laplace-Beltrami eigenfunction representation using cortical and amygdala surfaces as examples.

• Type: Journal
• Year: 2011
• Where: ISBI
• Authors: Seongho Seo, Moo K. Chung
• Keywords: Eigenfunctions, Intrinsic Geometry, ISBI 2011, Medical Imaging, Shape Representation