Par0012 - elastix

Registration Description

motion estimation; (cyclic) B-spline transformation; variance over last dimension

Image data

More details about the data are described in [1].

Application

Motion estimation from dynamical medical imaging data.

Results

4D chest CT: before registration (left), and after registration (right)

alt-text

4D cardiac CT

alt-text

3D carotid US

alt-text

3D pediatric lung MR

alt-text

Registration Settings

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

elastix version: 4.305

The zip file (see Github) contains all the parameter files used in [1]. The directory naming should be self-explanatory.

Command line calls

Two situations can be distinguished:

Parameter file combine script

This Python script (see Github) combines the forward and inverse transformations to make a transformation relative to a chosen reference time point. Syntax:

combine.py       [spacing=5000]

Options:

Example of combining forward and inverse transformation and corresponding transformix call to transform points from reference time point 12 to other time points
combine.py point TransformParameters.0.txt TransformParameters.1.txt Combined.0.txt Combined.1.txt 12

transformix -tp Combined.1.txt -def  -out

Note that contains the x, y, z coordinates of the point to transform and the t coordinate of the time point where you want to transform the points to. So given the above example with reference time point 12, you can transform point from time point 12 to time point 5 by specifying coordinates in the format x y z 5 in the .

Example of combining forward and inverse transformation and corresponding transformix call to align all time point images with reference time point 12
combine.py image TransformParameters.0.txt TransformParameters.1.txt Combined.0.txt Combined.1.txt 12

transformix -tp Combined.1.txt -in  -out

Known issues

The code for the 4D registration might not work correctly when the axes of the data are not equal to the coordinate system axes (direction cosines).

Published in

The method and experiments are published in:

[1] Nonrigid registration of dynamic medical imaging data using nD+t B-splines and a groupwise optimization approach, C.T. Metz, S. Klein, M. Schaap, T. van Walsum and W.J. Niessen, Medical Image Analysis, in press

© 2020 Viktor van der Valk