Par0059 - elastix

Registration Description

Intrapatient, B-spline transformation, mutual information, rigidity penalty


CT and MR images in the pelvic region.

Image data


Acquired on a 3T Philips Ingenia.


Acquired on Brilliance Big Bore.


MR and CT scans were acquired for 27 male patient for radiotherapy purposes. Non-rigid registration was used to align and resample the MR and CT volumes to train a deep learning model for synthetic CT generation. MR was the fixed image and CT the moving image.

Registration Settings

For parameter files see the Elastix Model Zoo repository on GitHub.

Elastix version: 4.9


Command line call:

elastix -p  par0059_rigid.txt -p par0059_bspline.txt –f MR_image.nii.gz -m CT_image.nii.gz -out output_dir -fMask MR_body_mask.nii.gz

Published in

Florkow et al. (2019), Deep learning-based MR-to-CT synthesis: the influence of varying gradient echo-based MR images as input channels, under submission

© 2020 Viktor van der Valk