CALIBRATIONLESS MRI RECONSTRUCTION WITH A PLUG-IN DENOISER.

Journal: Proceedings. IEEE International Symposium on Biomedical Imaging
Published Date: May 25, 2021

Abstract

Magnetic Resonance Imaging (MRI) is a noninvasive imaging technique that provides excellent soft-tissue contrast without using ionizing radiation. MRI's clinical application may be limited by long data acquisition time; therefore, MR image reconstruction from highly under-sampled k-space data has been an active research area. Calibrationless MRI not only enables a higher acceleration rate but also increases flexibility for sampling pattern design. To leverage non-linear machine learning priors, we pair our High-dimensional Fast Convolutional Framework (HICU) [1] with a plug-in denoiser and demonstrate its feasibility using 2D brain data.

Authors

  • Shen Zhao
    Department of Electrical and Computer Engineering, The Ohio State University.
  • Lee C Potter
    Department of Electrical and Computer Engineering, The Ohio State University.
  • Rizwan Ahmad
    Department of Biomedical Engineering, The Ohio State University.

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