99 / 2021-11-01 13:41:33
Super Resolution of MR via Learning Virtual Parallel Imaging
virtual parallel imaging,Super-Resolution imaging,reversible network
Final Paper
Cailian Yang / Nanchang University
Xianghao Liao / Nanchang University
Yifan Liao / Huazhong University of Science and Technology
Minghui Zhang / Nanchang University
Qiegen Liu / Nanchang University
Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, it is often clinically challenging to obtain high-quality MR images. Super-resolution (SR) is potentially promising to improve MR image quality without any hardware upgrade. Instead of the classical SR reconstruction method that enhance the spatial resolution via utilizing the spatial information itself, in this work, we propose a novel SR method via learning channel information in virtual parallel imaging. We use auxiliary variable technology to make the channel number of network output to be equal to the network input, increasing the number of channels information to achieve SR reconstruction. Compared with state-of-the-art SR methods, the present approach is advantageous in generating more details with higher resolution.
Important Date
  • Conference Date

    Nov 13

    2021

    to

    Nov 14

    2021

  • Sep 30 2021

    Contribution Submission Deadline

  • Nov 14 2021

    Registration deadline

Sponsored By
Medical Physics Branch of Chinese Society of Biomedical Engineering
IEEE Beijing Section
Life Electronics Society of Chinese Institute of Electronics
Organized By
Anhui Biomedical Engineering Society.
University of Science and Technology of China
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