The damped Richardson-Lucy (DRL) algorithm is a popular spherical deconvolution technique to quantify fiber orientation distributions from single-shell brain diffusion MRI (dMRI) data. Thanks to the progress of acquisition hardware, it is becoming increasingly common to acquire multi-shell dMRI data, which has the potential, to deliver additional information on the microstructure of tissues. In this work we extended the DRL framework to accommodate multi-shell data while accounting for multiple tissue types in the brain, to reduce partial volume contamination on the main FODs. The approach was tested on two dataset and proved to be stable over different acquisition schemes.
This abstract and the presentation materials are available to members only; a login is required.