Self-oriented Diffusion Basis Functions for white matter structure estimation. Aranda, R., Rivera, M., & Ramirez-Manzanares, A. In pages 1138–1141, April, 2013. doi abstract bibtex We present an extension to the Diffusion Basis Function Model for fitting the in vivo brain axonal orientations from Diffusion Weighted Magnetic Resonance Images. The standard Diffusion Basis Functions method assumes that the observed Magnetic Resonance signal at each voxel is a linear combination of a static set of basis functions with equally distributed orientations into the 3D unitary sphere. Our proposal, overcomes the limited angular resolution of the original model by adapting the basis orientations using a sophisticated non-linear optimization procedure. The improvements over the standard Diffusion Basis Functions model estimation by our proposal are demonstrated on the synthetic data-sets used on the 2012 HARDI Reconstruction Challenge.
@inproceedings{aranda_self-oriented_2013,
title = {Self-oriented {Diffusion} {Basis} {Functions} for white matter structure estimation},
doi = {10.1109/ISBI.2013.6556680},
abstract = {We present an extension to the Diffusion Basis Function Model for fitting the in vivo brain axonal orientations from Diffusion Weighted Magnetic Resonance Images. The standard Diffusion Basis Functions method assumes that the observed Magnetic Resonance signal at each voxel is a linear combination of a static set of basis functions with equally distributed orientations into the 3D unitary sphere. Our proposal, overcomes the limited angular resolution of the original model by adapting the basis orientations using a sophisticated non-linear optimization procedure. The improvements over the standard Diffusion Basis Functions model estimation by our proposal are demonstrated on the synthetic data-sets used on the 2012 HARDI Reconstruction Challenge.},
author = {Aranda, R. and Rivera, M. and Ramirez-Manzanares, A.},
month = apr,
year = {2013},
keywords = {3D unitary sphere, Brain, Computational modeling, DW-MRI, Diffusion basis functions, Estimation, HARDI reconstruction challenge, Handheld computers, Magnetic Resonance Imaging, Proposals, Self-orientation, Standards, Tensile stress, biodiffusion, biomedical MRI, diffusion tensor, diffusion weighted magnetic resonance images, in vivo brain axonal orientation, optimisation, self-oriented diffusion basis function model, sophisticated nonlinear optimization procedure, synthetic data-sets, white matter structure estimation},
pages = {1138--1141},
}
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