These are chat archives for thunder-project/thunder
@freeman-lab Image registration currently adds pixels with a value of 0 at the edge of images in order to keep dims the same as the dims of the reference image when preforming a transformation. The result is there will be a band of voxels at the edge of an image which suddenly go from a normal time series to 0 - this may create some problems with machine learning due to their high variance which is highly correlated.
I have currently been manually cropping out this dead space at the edge of my image but it might make sense to incorporate a cropping function into the image Registration model i.e once images are aligned the max transformation in x and y for the time series could be subtracted from the original dims to give post registration dims?
shiftmethod here using the
constantthen it would fill with zeros