I would like to ask a question about the proper way to calculate the Dice coefficient for an image dataset. We know that the Dice coefficient is calculated via the following equation:

However, how do we calculate the mean Dice coefficient for the entire dataset ? For example, suppose we have N images, each having size (H, W). There might be two ways:

• We calculate the Dice coefficient for each image, and then take the average for all images
• We flatten all of them into an array of size N * H * W, then calculate the Dice coefficient for this array.

I do not know which way is usually used in medical image segmentation. I have tried to search for some papers, but they do not go into details about this. It would be great if someone could reference some paper about this. Thank you very much.

I would like to ask a question about the proper way to calculate the Dice coefficient for an image dataset. We know that the Dice coefficient is calculated via the following equation:

$$Dice = \frac{TP +TP}{TP +TP +FP +FN}$$

However, how do we calculate the mean Dice coefficient for the entire dataset ? For example, suppose we have $N$ images, each having size $(H, W)$. There might be two ways:

• We calculate the Dice coefficient for each image, and then take the average for all images

• We flatten all of them into an array of size $N \times H \times W$, then calculate the Dice coefficient for this array.

I do not know which way is usually used in medical image segmentation. I have tried to search for some papers, but they do not go into details about this. It would be great if someone could reference some paper about this.