SPINNED: Simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast MRI perfusion data.

Journal: Magnetic resonance in medicine
Published Date: Apr 16, 2024

Abstract

PURPOSE: To propose the simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast (DSC) MRI (SPINNED) as an alternative for more robust and accurate deconvolution compared to existing methods.

Authors

  • Muhammad Asaduddin
    Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.
  • Eung Yeop Kim
    Department of Radiology, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea.
  • Sung-Hong Park
    From the Graduate School of Medical Science and Engineering (K.H.K., S.H.P.) and Department of Bio and Brain Engineering (S.H.P.), Korea Advanced Institute of Science and Technology, Room 1002, CMS (E16) Building, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea; Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.C.); Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea (S.H.C.); and Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea (S.H.C.).

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