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A Pytorch implementation of Dual-domain Adaptive-scaling Non-local Network for CT Metal Artifact Reduction.

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DAN-Net


paper:DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction

by Tao Wang scuer_wt@scu.stu.edu.cn. This repository implements DAN-Net by Pytorch for metal artifacts reduction (MAR) in CT images. We re-implement the reconstruction layer according to the formulas in DuDoNet and we used Numba in Python to achieve parallel computing.

This work was accepted by MICCAI2021, and the extended version was accepted by Physics in Medicine & Biology (PMB).

Prerequisites

This repository needs the following system settings:

  • Python 3.6
  • Pytorch 1.6.0
  • CUDA 10.1
  • Matlab R2017b

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A Pytorch implementation of Dual-domain Adaptive-scaling Non-local Network for CT Metal Artifact Reduction.

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