Checkerboard filter is a very, very poor visualization method for comparing images. It is one of those methods that only become somewhat popular because it is very easy to implement. The main problem is that you would need large squares to be able to interpret the image, but you need small squares so that you can compare the image contents (because you only see difference at the boundary of the squares).
For example visualizing misalignment using checkerboard with 4, 8, 16 divisions:
Instead, take one image and overlay edges extracted from the other image. You can use Canny edge detector or similar filters if you want to have a general idea about displacements/distortions. You need to first convert the input image to float type (using Cast Scalar Volume module) and then use Simple Filters module to do the Canny filtering (try with lower threshold = upper threshold = 50) or other filtering. You can change the colormap using Volumes module.
But in general, it is even better to segment the structure(s) of interest in one image and display that over the other image. It is also simpler, as segmentations is displayed already overlaid on the image. If you don’t want to segment any specific object then you can use simple thresholding to get a good set of contours.