Joint k-q Space Compressed Sensing for Accelerated Multi-Shell Acquisition and Reconstruction of the diffusion signal and Ensemble Average Propagator - Archive ouverte HAL Access content directly
Conference Papers Year : 2014

Joint k-q Space Compressed Sensing for Accelerated Multi-Shell Acquisition and Reconstruction of the diffusion signal and Ensemble Average Propagator

Abstract

High Angular Resolution Diffusion Imaging (HARDI) has been proposed to avoid the limitations of the conventional Diffusion Tensor Imaging (DTI) and to better explore white matter micro-structure non-invasively. However, HARDI methods normally require many more samples than DTI. For example, Diffusion Spectrum Imaging (DSI)[1], estimates the diffusion Ensemble Average Propagator (EAP) from typically 515 diffusion-weighted images, taking nearly one hour. Therefore, one important area of research in HARDI is to improve estimation of quantities such the diffusion propagator, the orientation distribution function, and diffusion-weighted signals from a reduced number of diffusion-weighted measurements. A solution to this problem is compressed sensing (CS). Existing approaches to compressed sensing diffusion MRI (CS-DMRI) mainly focus on applying CS in the q-space of diffusion signal measurements. For example, it has been shown in [2] that it is possible to accurately estimate the diffusion signal, with low root-mean-square-error (RMSE), from about 100 diffusion-weighted measurements in multiple shells (multiple b-values). However, this line of work fails to harness information redundancy in the k-space. By sub-sampling in both k-space and q-space, the scanning time can be significantly reduced, while keeping good estimation quality. To our knowledge, [3,4] are the only works using joint k-q space CS schemes to estimate the fiber ODF from single-shell data. The utility of this joint CS approach in multi-shell acquisition has not been sufficiently studied. In the current work, we propose a general framework, called k-q compressed sensing diffusion MRI (kq-CS-DMRI), to estimate the diffusion signal and the diffusion propagator from data sub-sampled in both k-space and q-space.

Domains

Medical Imaging
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Dates and versions

hal-01011893 , version 1 (27-06-2014)

Identifiers

  • HAL Id : hal-01011893 , version 1

Cite

Jian Cheng, Dinggang Shen, Pew-Thian Yap. Joint k-q Space Compressed Sensing for Accelerated Multi-Shell Acquisition and Reconstruction of the diffusion signal and Ensemble Average Propagator. ISMRM, May 2014, Italy. pp.664. ⟨hal-01011893⟩
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