Skip to content

Latest commit

 

History

History
36 lines (24 loc) · 1.28 KB

README.md

File metadata and controls

36 lines (24 loc) · 1.28 KB
Raw

voxelmorph

Binder

Notes

  • 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.

Papers

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

Instructions

Training:

  1. Change base_data_dir in train.py to the location of your image files.
  2. 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.

  1. Run test.py [model_name] [gpu-id] [iter-num]

Contact:

voxelmorph@mit.edu