@InProceedings{assemlal08,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Robust Variational Estimation of PDF functions from Diffusion MR Signal.},
booktitle = {CDMRI},
year = 2008,
address = {New York/USA},
month = {September},
theme = {misc},
abstract="We address the problem of robust estimation of tissue
microstructure from Diffusion Magnetic Resonance Imaging (dMRI). On
one hand, recent hardware improvements enable the acquisition of more
detailed images, on the other hand, this comes along with a low Signal
to Noise (SNR) ratio. In such a context, the approximation of the
Rician acquisition noise as Gaussian is not accurate. We propose to
estimate the volume of PDF-based characteristics from data samples by
minimizing a nonlinear energy functional which considers Rician MR
acquisition noise as well as additional spatial regularity
constraints. This approach relies on the approximation of the MR
signal by a series expansion based on Spherical Harmonics and
Laguerre-Gaussian functions. Results are presented to depict the
performance of this PDE-based approach on synthetic data and human
brain data sets respectively.",
url={HAL:=http://hal.archives-ouvertes.fr/hal-00329263, pdf:=http://hal.archives-ouvertes.fr/docs/00/32/92/63/PDF/cdmri08.pdf, Presentation:=https://brunl01.users.greyc.fr/ARTICLES/cdmri08-2.pdf}

 }