Complementary Phase Encoding for Pair-Wise Neural Deblurring of Accelerated Brain MRI

  • Gali Hod
  • , Michael Green
  • , Mark Waserman
  • , Eli Konen
  • , Shai Shrot
  • , Ilya Nelkenbaum
  • , Nahum Kiryati
  • , Arnaldo Mayer

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    MRI has become an invaluable tool for diagnostic brain imaging, providing unrivalled qualitative and quantitative information to the radiologist. However, due to long scanning times and capital costs, access to MRI lags behind CT. Typical brain protocols lasting over 30 min set a clear limitation to patient experience, scanner throughput, operation profitability, and lead to long waiting times for an appointment. As image quality, in terms of spatial resolution and noise, is strongly dependent on acquisition duration, significant scanning acceleration must successfully address challenging image degradation. In this work, we consider the scan acceleration scenario of a strongly anisotropic acquisition matrix. We propose a neural approach that jointly deblurs scan pairs acquired with mutually orthogonal phase encoding directions. This leverages the complementarity of the respective phase encoded information as blur directions are also mutually orthogonal between the scans in the pair. The proposed architecture, trained end-to-end, is applied to T1w scan pairs consisting of one scan with contrast media injection (CMI), and one without. Qualitative and quantitative validation is provided against state-of-the-art deblurring methods, for an acceleration factor of 4 beyond compressed sensing acceleration. The proposed method outperforms the compared methods, suggesting its possible clinical applicability for this challenging task.

    Original languageEnglish
    Title of host publicationComputer Vision – ECCV 2022 Workshops, Proceedings
    EditorsLeonid Karlinsky, Tomer Michaeli, Ko Nishino
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages268-280
    Number of pages13
    ISBN (Print)9783031250651
    DOIs
    StatePublished - 1 Jan 2023
    EventWorkshops held at the 17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel
    Duration: 23 Oct 202227 Oct 2022

    Publication series

    NameLecture Notes in Computer Science
    Volume13803 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceWorkshops held at the 17th European Conference on Computer Vision, ECCV 2022
    Country/TerritoryIsrael
    CityTel Aviv
    Period23/10/2227/10/22

    Keywords

    • Deblurring
    • Deep learning
    • Medical imaging
    • MRI acceleration
    • Multi-modal mri

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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