DEnse Displacement Sampling - deformable image registration

This package provides Python wrapper around DEEDS, an efficient version for 3D discrete deformable image registration which is reaching the highest accuracy in several benchmarks [1][2] and serves as a good baseline for new solutions.

Referencing and citing

If you use this implementation or parts of it please cite:

"MRF-Based Deformable Registration and Ventilation Estimation of Lung CT." by Mattias P. Heinrich, M. Jenkinson, M. Brady and J.A. Schnabel IEEE Transactions on Medical Imaging 2013, Volume 32, Issue 7, July 2013, Pages 1239-1248 http://dx.doi.org/10.1109/TMI.2013.2246577

and

"Multi-modal Multi-Atlas Segmentation using Discrete Optimisation and Self-Similarities" by Mattias P. Heinrich, Oskar Maier and Heinz Handels VISCERAL Challenge@ ISBI, Pages 27-30 2015 http://ceur-ws.org/Vol-1390/visceralISBI15-4.pdf

Installation

pip install git+https://github.com/wiktorowski211/deeds-registration

Usage

from deeds import registration
import SimpleITK as sitk

fixed = sitk.ReadImage(PATH)
moving = sitk.ReadImage(PATH)

moved = registration(fixed, moving)

Prerequesities

Input images must:

• have the same dimensions,
• be a SimpleITK image object.

Development

Build:

python setup.py build_ext --inplace

Test:

python -m unittest