@article{assemlal09,
author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun}, title = {Efficient and Robust Computation of PDF Features from Diffusion MR Signal}, journal = {Medical Image Analysis}, year = {2009}, volume=13, number=5, pages={715-729}, abstract=" We present a method for the estimation of various features of the tissue micro-architecture using the diffusion magnetic resonance imaging. The considered features are designed from the displacement probability density function (PDF). The estimation is based on two steps: first the approximation of the signal by a series expansion made of Gaussian-Laguerre and Spherical Harmonics functions; followed by a projection on a finite dimensional space. Besides, we propose to tackle the problem of the robustness to Rician noise corrupting emphin-vivo acquisitions. Our feature estimation is expressed as a variational minimization process leading to a variational framework which is robust to noise. This approach is very flexible regarding the number of samples and enables the computation of a large set of various features of the local tissues structure. We demonstrate the effectiveness of the method with results on both synthetic phantom and real MR datasets acquired in a clinical time-frame.", url={ HAL := http://hal.archives-ouvertes.fr/hal-00410615, pdf:=http://hal.archives-ouvertes.fr/docs/00/41/06/15/PDF/assemlal_MedIA09.pdf}
}