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International Workshop on Machine Learning in Medical Imaging

MLMI 2021: Machine Learning in Medical Imaging pp 447–456Cite as

Using Spatio-Temporal Correlation Based Hybrid Plug-and-Play Priors (SEABUS) for Accelerated Dynamic Cardiac Cine MRI

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12966))

Abstract

The plug-and-play prior (P\(^{3}\)) is known as denoising prior which has been successfully applied to various imaging problems. In this work for accelerated dynamic cardiac cine magnetic resonance imaging (Dcc-MRI), we introduce a Spatio-tEmporal correlAtion based hyBrid plUg-and-play priorS (SEABUS) integrating local P\(^{3}\) and nonlocal P\(^{3}\), which further help both suppress aliasing artifacts and capture dynamic features. Specifically, the local P\(^{3}\) enforces the pixel-wise edge-orientation consistency by reference frame guided multi-scale orientation projection (MSOP) in a subset of few adjacent frames. The nonlocal P\(^{3}\) constrains the cube-wise anatomic-structure similarity by cube matching and 4D filtering (CM4D) in all frames. By composite splitting algorithm (CSA), the SEABUS is coupled into fast iterative shrinkage-thresholding algorithm (FISTA) and then a new Dcc-MRI approach that is named as SEABUS-FCSA is proposed. The experimental results on the in-vivo cardiac MR datasets demonstrated the efficiency and potential of the proposed SEABUS-FCSA approach.

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Author information

Authors and Affiliations

  1. Medical AI Research Centre, Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen, Guangdong, China

    Qingyong Zhu & Dong Liang

  2. Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen, Guangdong, China

    Dong Liang

Authors
  1. Qingyong Zhu
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  2. Dong Liang
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Corresponding author

Correspondence to Dong Liang .

Editor information

Editors and Affiliations

  1. Xi'an Jiaotong University, Xi'an, China

    Chunfeng Lian

  2. United Imaging Intelligence, Shanghai, China

    Xiaohuan Cao

  3. Istanbul Technical University, Istanbul, Turkey

    Islem Rekik

  4. Rensselaer Polytechnic Institute, Troy, NY, USA

    Xuanang Xu

  5. Rensselaer Polytechnic Institute, Troy, NY, USA

    Pingkun Yan

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Zhu, Q., Liang, D. (2021). Using Spatio-Temporal Correlation Based Hybrid Plug-and-Play Priors (SEABUS) for Accelerated Dynamic Cardiac Cine MRI. In: Lian, C., Cao, X., Rekik, I., Xu, X., Yan, P. (eds) Machine Learning in Medical Imaging. MLMI 2021. Lecture Notes in Computer Science(), vol 12966. Springer, Cham. https://doi.org/10.1007/978-3-030-87589-3_46

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  • DOI: https://doi.org/10.1007/978-3-030-87589-3_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87588-6

  • Online ISBN: 978-3-030-87589-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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