voxelmorph

Unsupervised Learning with CNNs for Image Registration
We incorporate several variants, presented at CVPR2018 (initial unsupervised learning) and MICCAI2018 (probabilistic & diffeomorphic)

Instructions

It might be useful to have each folder inside the ext folder on your python path. assuming voxelmorph is setup at /path/to/voxelmorph/:

export PYTHONPATH=$PYTHONPATH:/path/to/voxelmorph/ext/neuron/:/path/to/voxelmorph/ext/pynd-lib/:/path/to/voxelmorph/ext/pytools-lib/

Training:

These instructions are for the MICCAI2018 paper. If you'd like the CVPR version (no diffeomorphism or uncertainty measures and using CC) use train.py

Change the top parameters in train_miccai2018.py to the location of your image files.
Run train_miccai2018.py with options described in the main function. Example:

train_miccai2018.py --gpu 0 --model_dir /my/path/to/models

Testing (measuring Dice scores):

Put test filenames in data/test_examples.txt, and anatomical labels in data/test_labels.mat.
Run test_miccai2018.py [gpu-id] [model_dir] [iter-num]

Notes

We provide a T1 atlas used in our papers at data/atlas_norm.npz.
The spatial transform code, found at neuron.layers.SpatialTransform, accepts N-dimensional affine and dense transforms, including linear and nearest neighbor interpolation options. Note that original development of VoxelMorph used xy indexing, whereas we are now emphasizing ij indexing.
For the MICCAI2018 version, we integrate the velocity field using neuron.layers.VecInt. By default we integrate using scaling and squaring, which we found efficient.
You will likely need to write some of the data loading code in 'datagenerator.py' for your own datasets and data formats. There are several hard-coded elements related to data preprocessing and format.

Papers

If you use voxelmorph or some part of the code, please cite:

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

Contact:

For and problems or questions please open an issue in github or email us at voxelmorph@mit.edu