Working with probabilistic atlas

I tried to use Brain_Data to load a mask based on DiFuMo atlas (https://parietal-inria.github.io/DiFuMo/) Using the standard method (loading mask with Brain_Data and using expand_mask) doesn’t work. When looking at the loaded atlas, I find that it is already loaded as expanded. But then, trying to use roi_to_brain doesn’t work as well.

a = nilearn.datasets.fetch_atlas_difumo(dimension=256)
mask = Brain_Data(a.maps)

[orduek]

Sounds good. I’ll have a go at it and let you know once I stumble into some issues.

[ljchang]

Hi @orduek, most of our mask functions are not designed to work with probabilistic masks, only binary ones. It’s easy to convert to binary using the dat.threshold() method. However, without knowing any of the details of those images, finding an appropriate threshold might be tricky with that particular mask.

Here is an example for how to binarize a single map, mask[0].threshold(upper=.0001, binarize=True), or all of them if you can use the same threshold mask_bin = mask.threshold(upper=.0001, binarize=True)