A novel Riemannian metric for analyzing HARDI data

Sentibaleng Ncube; Anuj Srivastava

doi:10.1117/12.878100

11 March 2011 A novel Riemannian metric for analyzing HARDI data

Sentibaleng Ncube, Anuj Srivastava

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79620Q (2011) https://doi.org/10.1117/12.878100
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

We propose a novel Riemannian framework for analyzing orientation distribution functions (ODFs) in HARDI data sets, for use in comparing, interpolating, averaging, and denoising ODFs. A recently used Fisher-Rao metric does not provide physically feasible solutions, and we suggest a modification that removes orientations from ODFs and treats them as separate variables. This way a comparison of any two ODFs is based on separate comparisons of their shapes and orientations. Furthermore, this provides an explicit orientation at each voxel for use in tractography. We demonstrate these ideas by computing geodesics between ODFs and Karcher means of ODFs, for both the original Fisher-Rao and the proposed framework.

Citation Download Citation

Sentibaleng Ncube and Anuj Srivastava "A novel Riemannian metric for analyzing HARDI data", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79620Q (11 March 2011); https://doi.org/10.1117/12.878100

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