DANTE-CAIPI Accelerated Contrast-Enhanced 3D T1: Deep Learning-Based Image Quality Improvement for Vessel Wall MRI.

Journal: AJNR. American journal of neuroradiology
PMID: 39038956

Abstract

BACKGROUND AND PURPOSE: Accelerated and blood-suppressed postcontrast 3D intracranial vessel wall MRI (IVW) enables high-resolution rapid scanning but is associated with low SNR. We hypothesized that a deep-learning (DL) denoising algorithm applied to accelerated, blood-suppressed postcontrast IVW can yield high-quality images with reduced artifacts and higher SNR in shorter scan times.

Authors

  • Mona Kharaji
    Vascular Imaging Lab, Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
  • Gador Canton
    Department of Radiology University of Washington Seattle WA.
  • Yin Guo
    Center for Stem Cell Biology & Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore MD 21201, USA.
  • Mohamad Hosaam Mosi
    From the Department of Radiology (M.K., G.C., M.H.M., N.B., M.M.-B.), University of Washington School of Medicine, Seattle, Washington.
  • Zechen Zhou
    Philips Research North America, Cambridge, MA 02141, United States. Electronic address: ze.chen.zhou@philips.com.
  • Niranjan Balu
    Department of Radiology, University of Washington, Seattle, WA 98195, United States.
  • Mahmud Mossa-Basha
    Department of Radiology, University of Washington School of Medicine, Seattle, WA.

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