Shape Analysis with Overcomplete Spherical Wavelets

Authors:
B. T. Yeo;Peng Yu;P. Ellen Grant;Bruce Fischl;Polina Golland
Affiliations:
Computer Science and Artificial Intelligence Laboratory, MIT, , USA and Division of Pediatric Radiology, MGH, , USA;Division of Health Sciences and Technology, MIT, , USA;Athinoula A. Martinos Center for Biomedical Imaging, MGH/HMS, , USA and Division of Pediatric Radiology, MGH, , USA;Computer Science and Artificial Intelligence Laboratory, MIT, , USA and Athinoula A. Martinos Center for Biomedical Imaging, MGH/HMS, , USA;Computer Science and Artificial Intelligence Laboratory, MIT, , USA
Venue:
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Year:
2008

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Abstract

In this paper, we explore the use of over-complete spherical wavelets in shape analysis of closed 2D surfaces. Previous work has demonstrated, theoretically and practically, the advantages of over-complete over bi-orthogonal spherical wavelets. Here we present a detailed formulation of over-complete wavelets, as well as shape analysis experiments of cortical folding development using them. Our experiments verify in a quantitativefashion existing qualitativetheories of neuro-anatomical development. Furthermore, the experiments reveal novelinsights into neuro-anatomical development not previously documented.