I think the DiceMetric may has an error when there is no foreground for y but has foreground for y_pred. According to the formula, the result should be 0, but so far the class will return nan:

torch.where(y_o > 0, (2.0 * intersection) / denominator, torch.tensor(float("nan"), device=y_o.device))

The earliest commit I can found is already use this way for calculation: see https://github.com/Project-MONAI/MONAI/pull/285/files#diff-df0f76defe29c2c91286e52334ead7a0f1f54e392d1a3e8280e2e714800dc4cbL96

I think we may need to use:

torch.where(denominator > 0, (2.0 * intersection) / denominator, torch.tensor(float("nan"), device=y_o.device))

In addition, we use a fixed value: nan to fill the cases that the ground truth (as I mentioned, may need to be placed by denominator) has no foreground. However, in some practical situations, people may consider to use other values such as 1 instead. For example, in
the latest Kaggle competition: https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation/overview/evaluation , it says:

where X is the predicted set of pixels and Y is the ground truth. The Dice coefficient is defined to be 1 when both X and Y are empty.

Therefore, I think we may need to add an argument here thus users can specify which value to use.

Hi @ristoh @Nic-Ma @wyli @ericspod , could you please help to double check it? Thanks!