Shape manifold regression with spherical harmonics for hippocampus shape analysis

Xuejiao Chen; Wenjing Li; Jing Hua; Xiaopeng Zhang; Huiguang He

doi:10.1117/12.2007158

20 March 2013 Shape manifold regression with spherical harmonics for hippocampus shape analysis

Xuejiao Chen, Wenjing Li, Jing Hua, Xiaopeng Zhang, Huiguang He

Author Affiliations +

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 866940 (2013) https://doi.org/10.1117/12.2007158
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Shape regression analysis is a powerful tool to study local shape changes as a function of an independent regressor variable. In this paper, we introduce spherical harmonic(SPHARM) representation to surface manifold learning and shape regression. Here, we use root mean square distance(RMSD) to measure the deformation degree of the surface, and find out that the hippocampus’ deformation degree is increased over age. We also investigate the particular changing area, and discover that the hippocampus have significant changes in the frontal area and tail area, especially in CA1 subfield.

Citation Download Citation

Xuejiao Chen, Wenjing Li, Jing Hua, Xiaopeng Zhang, and Huiguang He "Shape manifold regression with spherical harmonics for hippocampus shape analysis", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866940 (20 March 2013); https://doi.org/10.1117/12.2007158

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