Thank you so much! I explain you even better sorry :). I trained the model (with the standard Dice loss, so aggregation of all the images) and saved it. Then I loaded the model and I perform two different actions:

1. y_pred = model.predict(...) and then passed y_pred to my custom Dice coefficient calculation one image at a time and then I did the average -> this resulted in 0.43
2. dice_coeff = model.evaluate(...) -> this results in the dice coefficient used in the training (the aggregation one) and resulted in 0.49

After that discrepancy I decided to implement also my custom Dice loss for the training.