Klara, I have an idea but it's pretty rough - see what you can make of it.
Assume the MRI volume is highly refined - let's use this as the base mesh - I think for this both the MRI and the circles have to be volume meshed, not just surfaces. Take your purple regions and assign a Point variable of MRI and assign a value of 1 For each of your circles, assign a Point variable - let's assign a variable of "circle" and assign a value of 1 - n, where n is number of circles Now use Resample with Dataset using one of your meshed spheres as input and MRI as source - now you have a MRI cloud that has some elements with a circle value of 0 and some with a circle value of 1 (for circle #1). Threshold on circle value between .5 and 1 and you will get a subset of elements in circle 1 that are enclosed by the MRI cloud. Calculate the volume in the python calculator. Compare to volume of entire sphere (they all look like the same size, so you probably know total volume of sphere). This gives you % of circle that is inclosed by MRI cloud. I haven't tried it but you can probably combine all the circles and the MRI cloud using resample - maybe try Group Datasets on the spheres first. You could then get volume of MRI cloud with circle > 0 and compare to total volume of MRI cloud if you wanted that percentage. Part I don't know at all is how to volume mesh these parts if you have them only as surfaces. Not a polished answer, but food for thought. Hope this helps Dennis
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