Improving phase-based conductivity reconstruction by means of deep learning-based denoising of phase data for 3T MRI.

Journal: Magnetic resonance in medicine
Published Date: May 5, 2021

Abstract

PURPOSE: To denoise phase using a deep learning method for phase-based in vivo electrical conductivity reconstruction in a 3T MR system.

Authors

  • Kyu-Jin Jung
    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Stefano Mandija
    Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Jun-Hyeong Kim
    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Kanghyun Ryu
    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Soozy Jung
    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Chuanjiang Cui
    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Soo-Yeon Kim
  • Mina Park
  • Cornelis A T van den Berg
    Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Dong-Hyun Kim
    Neurobiota Research Center, College of Pharmacy, Kyung Hee University, Dongdaemun-gu, Seoul 02447, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals