Acceleration of High-Resolution 3D MR Fingerprinting via a Graph Convolutional Network

Feng Cheng, Yong Chen, Xiaopeng Zong, Weili Lin, Dinggang Shen, Pew Thian Yap

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

    4 Citations (Scopus)

    Abstract

    Magnetic resonance fingerprinting (MRF) is a novel imaging framework for fast and simultaneous quantification of multiple tissue properties. Recently, 3D MRF methods have been developed, but the acquisition speed needs to be improved before they can be adopted for clinical use. The purpose of this study is to develop a novel deep learning approach to accelerate 3D MRF acquisition along the slice-encoding direction in k-space. We introduce a graph-based convolutional neural network that caters to non-Cartesian spiral trajectories commonly used for MRF acquisition. We improve tissue quantification accuracy compared with the state of the art. Our method enables fast 3D MRF with high spatial resolution, allowing whole-brain coverage within 5 min, making MRF more feasible in clinical settings.

    Original languageEnglish
    Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings
    EditorsAnne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages158-166
    Number of pages9
    ISBN (Print)9783030597122
    DOIs
    Publication statusPublished - 2020
    Event23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru
    Duration: 2020 Oct 42020 Oct 8

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume12262 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020
    Country/TerritoryPeru
    CityLima
    Period20/10/420/10/8

    Bibliographical note

    Publisher Copyright:
    © 2020, Springer Nature Switzerland AG.

    Keywords

    • 3D MR fingerprinting
    • GRAPPA
    • Graph convolution
    • K-space interpolation

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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