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This is an implementation of paper "S. Xue and R. Bai. 2D Probabilistic Undersampling Pattern Optimization for MR Image Reconstruction. IEEE Transactions on Medical Imaging, 2020, under review."

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2D-PUPO

This is an implementation of paper "S. Xue and R. Bai. 2D Probabilistic Undersampling Pattern Optimization for MR Image Reconstruction. IEEE Transactions on Medical Imaging, 2020, under review."

10% sampling rate 20% probability matrix

Environment

  • OS: Ubuntu Linux kernel 4.15.0-76-generic x86_64
  • CPU: Intel Xeon(R) Platinum 8163 CPU @ 2.50GHz x 96
  • Memory: 503 GB
  • GPU: NVIDIA Tesla V100 (32 GB) x 4

Software

  • Python 2.7.15
  • Tensorflow 1.13.1
  • Keras 2.2.4
  • CUDA Toolkit 10.0.130
  • CUDNN 7.6.5
  • OpenCV 2.4.11
  • Numpy 1.16.5

Dataset

  • 3T MR images
  • MICCAI images

Train

python main.py --gpu=0 --run=train --dataset=MRI_3T --model=VDSR

Parameters for training

Test

python main.py --gpu=0 --run=validate --dataset=MRI_3T --model=VDSR

Contact

Ph.D., Shengke Xue

College of Information Science and Electronic Engineering

Zhejiang University, Hangzhou, P.R. China

Email: xueshengke@zju.edu.cn, xueshengke93@gmail.com

About

This is an implementation of paper "S. Xue and R. Bai. 2D Probabilistic Undersampling Pattern Optimization for MR Image Reconstruction. IEEE Transactions on Medical Imaging, 2020, under review."

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