Question regarding converting a model back to a segmentation node


My question pertains to the conversion of a model back to a segmentation.

Currently i want to overlay 2 CT scans to calculate the dice score between 2 femoral segmentations (preoperative and postoperative).
These CT’s are not in the same orientation and do not overlap.

I first segment both, convert them to a model and use SlicerIGT’s model registration to overlap these models. Then convert them back to a segmentation node and us slicerRT segment comparison to compute the dice score and hausdorff distances.

If i return both models back to a segmentation node, will there be a loss in quality or will the original segmentation stay intact?

Any suggestion to my way of approaching this would also be quite welcome.

Thank you in advance.

You wouldn’t need to convert the models back to segmentations. You can just apply the transform to the segmentations and calculate your metrics in binary labelmap space.

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Truly overcomplicated it. Thank you, such a simple solution.