Test new contrast-agnostic model

[jcohenadad]

Following up on #95 (comment), the purpose of this issue is to compare the performance of the contrast-agnostic model v2.3 vs. v2.4 on PSIR data.

Example:

The quality of segmentation is definitely better (see upper thoracic cord). Interestingly however, the model seems more "confident" in that there is much less smoothness in sagittal slices adjacent to the spinal cord:

Is that a good thing? Further validation required

@naga-karthik

[naga-karthik]

Interesting gifs! thank you for posting them!

could you also post the soft values from the 2nd gif? my guess that the soft values from the v2.3 model are already too soft from the looks of the label (i.e. they will be gone if we binarize with 0.5).

Note that these binarized labels (which don't have segmentations on the slices adj to the cord) were used for training so I think the model learned to output less soft values here

[jcohenadad]

could you also post the soft values from the 2nd gif?

I'm not sure I know what you mean by that. If you meant what threshold I used, the answer is '-thr 0' for both models.

Note that these binarized labels (which don't have segmentations on the slices adj to the cord) were used for training so I think the model learned to output less soft values here

right, good point

[jcohenadad]

Note: the 2.4 model is now part of SCT's master branch: spinalcordtoolbox/spinalcordtoolbox@bb479d8