Skip to Main content Skip to Navigation
Journal articles

Multiple q-shell diffusion propagator imaging

Abstract : Many recent high angular resolution diffusion imaging (HARDI) reconstruction techniques have been introduced to infer an orientation distribution function (ODF) of the underlying tissue structure. These methods are more often based on a single-shell (one b-value) acquisition and can only recover angular structure information contained in the ensemble average propagator (EAP) describing the three-dimensional (3D) average diffusion process of water molecules. The EAP can thus provide richer information about complex tissue microstructure properties than the ODF by also considering the radial part of the diffusion signal. In this paper, we present a novel technique for analytical EAP reconstruction from multiple q-shell acquisitions. The solution is based on a Laplace equation by part estimation between the diffusion signal for each shell acquisition. This simplifies greatly the Fourier integral relating diffusion signal and EAP, which leads to an analytical, linear and compact EAP reconstruction. An important part of the paper is dedicated to validate the diffusion signal estimation and EAP reconstruction on real datasets from ex vivo phantoms. We also illustrate multiple q-shell diffusion propagator imaging (mq-DPI) on a real in vivo human brain and perform a qualitative comparison against state-of-the-art diffusion spectrum imaging (DSI) on the same subject. mq-DPI is shown to reconstruct robust EAP from only several different b-value shells and less diffusion measurements than DSI. This opens interesting perspectives for new q-space sampling schemes and tissue microstructure investigation.
Complete list of metadatas
Contributor : Rachid Deriche <>
Submitted on : Tuesday, November 2, 2010 - 7:02:49 PM
Last modification on : Friday, November 13, 2020 - 1:42:04 PM




Maxime Descoteaux, Rachid Deriche, Denis Lebihan, Jean-François Mangin, Cyril Poupon. Multiple q-shell diffusion propagator imaging. Medical Image Analysis, Elsevier, 2011, 15 (4), pp.603-621. ⟨10.1016/⟩. ⟨hal-00531473⟩



Record views