Accelerated Acquisition of High-resolution Diffusion-weighted Imaging of the Brain with a Multi-shot Echo-planar Sequence: Deep-learning-based Denoising.

Journal: Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Published Date:

Abstract

To accelerate high-resolution diffusion-weighted imaging with a multi-shot echo-planar sequence, we propose an approach based on reduced averaging and deep learning. Denoising convolutional neural networks can reduce amplified noise without requiring extensive averaging, enabling shorter scan times and high image quality. The preliminary experimental results demonstrate the superior performance of the proposed denoising method over state-of-the-art methods such as the widely used block-matching and 3D filtering.

Authors

  • Motohide Kawamura
    Department of Radiology, University of Yamanashi.
  • Daiki Tamada
    Department of Radiology, University of Yamanashi.
  • Satoshi Funayama
    Department of Radiology, Faculty of Medicine, University of Yamanashi, Chuo-city, Yamanashi 409-3898, Japan.
  • Marie-Luise Kromrey
    Department of Radiology, University of Yamanashi.
  • Shintaro Ichikawa
    Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA, USA.
  • Hiroshi Onishi
    Department of Radiology, University of Yamanashi, Yamanashi, Japan.
  • Utaroh Motosugi
    Department of Radiology, University of Yamanashi.