Compressive sensing based Q-space resampling for handling fast bulk motion in hardi acquisitions

Shireen Elhabian, Clement Vachet, Joseph Piven, Martin Styner, Guido Gerig

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Diffusion-weighted (DW) MRI has become a widely adopted imaging modality to reveal the underlying brain connectivity. Long acquisition times and/or non-cooperative patients increase the chances of motion-related artifacts. Whereas slow bulk motion results in inter-gradient misalignment which can be handled via retrospective motion correction algorithms, fast bulk motion usually affects data during the application of a single diffusion gradient causing signal dropout artifacts. Common practices opt to discard gradients bearing signal attenuation due to the difficulty of their retrospective correction, with the disadvantage to lose full gradients for further processing. Nonetheless, such attenuation might only affect limited number of slices within a gradient volume. Q-space resampling has recently been proposed to recover corrupted slices while saving gradients for subsequent reconstruction. However, few corrupted gradients are implicitly assumed which might not hold in case of scanning unsedated infants or patients in pain. In this paper, we propose to adopt recent advances in compressive sensing based reconstruction of the diffusion orientation distribution functions (ODF) with under sampled measurements to resample corrupted slices. We make use of Simple Harmonic Oscillator based Reconstruction and Estimation (SHORE) basis functions which can analytically model ODF from arbitrary sampled signals. We demonstrate the impact of the proposed resampling strategy compared to state-of-art resampling and gradient exclusion on simulated intra-gradient motion as well as samples from real DWI data.

    Original languageEnglish (US)
    Title of host publication2016 IEEE International Symposium on Biomedical Imaging
    Subtitle of host publicationFrom Nano to Macro, ISBI 2016 - Proceedings
    PublisherIEEE Computer Society
    Pages907-910
    Number of pages4
    ISBN (Electronic)9781479923502
    DOIs
    StatePublished - Jun 15 2016
    Event2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic
    Duration: Apr 13 2016Apr 16 2016

    Publication series

    NameProceedings - International Symposium on Biomedical Imaging
    Volume2016-June
    ISSN (Print)1945-7928
    ISSN (Electronic)1945-8452

    Other

    Other2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
    CountryCzech Republic
    CityPrague
    Period4/13/164/16/16

    Keywords

    • Artifact reduction
    • Compressive sensing
    • Diffusion weighted imaging
    • QBI
    • SHORE
    • Within-gradient motion

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Radiology Nuclear Medicine and imaging

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