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
Event17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel
Duration: 23 Oct 202227 Oct 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13803 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th 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
  • Computer Science (all)

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