Dice loss problems

[Lijiaying201812]

When I run the program with example downloaded data,I found there was a problem with label_indices =1 and label_indices =2 ,because the dice were almost zero for these condition,What's the reason for the case? Thanks!

[YipengHu]

Hi thanks for the question. It is expected in particular during the initial stages of training. As most of the labels are small (except for Labels #0 which are always the gland segmentation), so they would not have any overlap before more iterations in. Even when it closes to convergence, some of them still can be quite small even zeros. Just FYI: these non-overlap landmarks still generate useful gradients, due to the multiscale loss, as explained in the paper.

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On Wed, 20 Mar 2019 at 02:41, Lijiaying201812 ***@***.***> wrote: When I run the program with example downloaded data,I found there was a problem with label_indices =1 and label_indices =2 ,because the dice were almost zero for these condition,What's the reason for the case? Thanks! — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#16>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ACd9_YR0JLQSpFJ4kpcSTXbrr9GW8eCsks5vYZ_kgaJpZM4b-B4k> .