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Train a model to detect spinal cord centerline #29
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Based on a brief (water cooler) conversation along with @valosekj, here's a proof-of-concept to test the feasibility of this idea. We could formulate this as a segmentation problem and make the model output the spinal cord (SC) centerlines as segmentation niftis. Rationale? - We already get decent outputs from Implementational details that need to be ironed out:
Alternative - If the above idea does not work for some reason, here's an alternative. Instead of posing it as a segmentation problem, pose it as a regression problem. This is because This is a rough sketch of what I had in mind, any suggestions are welcome! |
Also relevant ivadomed/canproco#7 |
I'm not sure I understand that part. Did you mean "other than sagittal"? And if so, at what level are you planning to enforce this orientation? Usually a specific orientation is not required (and should not) |
This is answered in this issue(comment). It would be great if you could follow-up with your latest thoughts on that instead! As a result, closing this issue here to avoid duplication. |
Given the importance of cropping the volume for training/inference, a possible strategy would be to train a model to detect the centerline, that would be specific to these image.
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