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We present a unified statistical approach to modeling disconnected 3Danatomical structures extracted from medical images. Due to image acquisitionand preprocessing noises, it is expected the imaging data is noisy. The surfacecoordinates of the structures are regressed using the weighted linearcombination of Laplace-Beltrami (LB) eigenfunctions to smooth out noisy dataand perform statistical analysis. The method is applied in characterizing the3D growth pattern of human hyoid bone between ages 0 and 20. We detected asignificant age effect on localized parts of the hyoid bone.

Kernel Regression on Manifolds and Its Application to Modeling Disconnected Anatomic Structures