Exponential-Distance Weights for Reducing Grid-like Artifacts in Patch-Based Medical Image Registration
The code was written by Dr. Liang Wu, Shandong University.
keywords: patch fusion, EDW, distance, registration
Keras
Tensorflow
patch_fusion.py: This is our original code, it is flexible to modify, but the fusion time is very long.
patch_fusion_fast.py: Code for fast implementation.
patch_fusion_AAW.py: AAW method
If you use our code, please cite the following paper:
Wu L, Hu S, Liu C. Exponential-Distance Weights for Reducing Grid-Like Artifacts in Patch-Based Medical Image Registration. Sensors. 2021; 21(21):7112. https://doi.org/10.3390/s21217112
Some codes in this repository are modified from Labreg (https://github.com/YipengHu/label-reg) and VoxelMorph(https://github.com/voxelmorph/voxelmorph).
If you have any problems or questions please contact (wuliang@mail.sdu.edu.cn or hushunbo@lyu.edu.cn).