Code was initially written in python 2.7, and now transfered to 3.5.
We are currently cleaning up our code for general use. There are several hard-coded elements related to data preprocessing and format. You will likely need to rewrite some of the data loading code in 'datagenerator.py' for your own datasets.
We provide the atlas used in our papers at data/atlas_norm.npz.
Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration
Adrian V. Dalca, Guha Balakrishnan, John Guttag, Mert R. Sabuncu
MICCAI 2018. eprint arXiv:1805.04605
An Unsupervised Learning Model for Deformable Medical Image Registration
Guha Balakrishnan, Amy Zhao, Mert R. Sabuncu, John Guttag, Adrian V. Dalca
CVPR 2018. eprint arXiv:1802.02604
- Change base_data_dir in train.py to the location of your image files.
- Run train.py [model_name] [gpu-id]
Testing (Dice scores):
Put test filenames in data/test_examples.txt, and anatomical labels in data/test_labels.mat.
- Run test.py [model_name] [gpu-id] [iter-num]