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Is your feature request related to a problem? Please describe.
Dice loss considers true positive (TP), false positive (FP), and false negative (FN) [ref], which doesn't provide a full spectrum for the target and predictions and can cause sub-par training for certain scenarios.
Describe the solution you'd like
Matthews Correlation Coefficient Loss, on the other hand, considers all the entries of a confusion matrix including true negatives (TN) [ref], and could potentially provide better solutions to segmentation problems.
Describe alternatives you've considered
N.A.
Additional context
N.A.
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
Dice loss considers true positive (TP), false positive (FP), and false negative (FN) [ref], which doesn't provide a full spectrum for the target and predictions and can cause sub-par training for certain scenarios.
Describe the solution you'd like
Matthews Correlation Coefficient Loss, on the other hand, considers all the entries of a confusion matrix including true negatives (TN) [ref], and could potentially provide better solutions to segmentation problems.
Describe alternatives you've considered
N.A.
Additional context
N.A.
The text was updated successfully, but these errors were encountered: