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Just writing down here one idea that we came across during the 2024-07-25 "lumbar classification challenge meeting" meeting:
explore multi-channel (4D nii image = one class per image) vs multi-label (3D nii image = one image with multiple classes, each class has a different int value) approach for rootlets segmentation
Currently, we use the multi-label (3D) approach.
The text was updated successfully, but these errors were encountered:
Just writing down here one idea that we came across during the 2024-07-25 "lumbar classification challenge meeting" meeting:
Currently, we use the multi-label (3D) approach.
The text was updated successfully, but these errors were encountered: