Add distance based loss #178
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constantinpape
commented
Dec 6, 2023
| # Because it always interprets the first axis as channel, | ||
| # and treats it differently (sums over it independently). | ||
| # This will lead to a very large dice loss that dominates over everything else. | ||
| fg_input, fg_target = input_[:, 0:1], target[:, 0:1] |
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This is crucial, if we don't keep the channels then the dice loss does wrong things.
| return overall_loss | ||
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| class DiceBasedDistanceLoss(DistanceLoss): |
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I by accident tried this (using dice loss both for the foreground and distance loss term) and this seems to work really good. We should give it a try.
| @@ -27,7 +27,8 @@ def __init__( | |||
| out_channels=1, | |||
| use_sam_stats=False, | |||
| use_mae_stats=False, | |||
| encoder_checkpoint_path=None | |||
| encoder_checkpoint_path=None, | |||
| final_activation=None, | |||
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As discussed, it's not a good idea to hard-code the final activation to sigmoid. I updated this to use the same logic and syntax as in our U-Net implementation.
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