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Just thinking about this and it reminded of the approach I was considering initially -- have you taken a look at Mask RCNN? it's basically a segmentation + detection model combined into one. When I looked at it, there were no 3D models and the combined approach was a bit complicated (i.e. it was not easy to get the bounding box predictions, cuda-issues, etc). But maybe things might have changed now? MaskRCNN is also quite old but there might be new models that do detection + segmentation a bit better?
Secondly, when I was thinking about this nnDetection was just starting and not as developed. Maybe you can also consider looking at it too? especially now since we're all experts in training nnUnets ;)
Projects steps :
Multiple Sclerosis (MS) lesion datasets: Canproco (PSIR, STIR)
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