Inquiry about Missing Slides when Patching about wsi-finetuning

[invoker-LL]

These 2 slides are of very few tissue areas, thus may be filtered by operations (like otsu) during pre-processing.
But the otsu is useful during reproduce the result of CLAM.

[bryanwong17]

So do you have any suggestions in order to reproduce the result? how did you deal with this issue?

[invoker-LL]

You can just omit these 2 slides during training, which will get about similar AUC score compared to CLAM.
But if the OTSU is not included during preprocess, I can only get an AUC score of 0.82-0.83. (I am not quite sure about the details in their experiments either, or you may try the preprocess in DTFD?)
Above results are mainly caused by the weak embedding of ImageNet pretraining, if your use pretraining embedding like lunit, which may not be a question.
Though I think there will also be some improvement using our fine-tuning based on lunit embedding, but Camelyon-16 may easily meet its upper-bound, like an AUC of 0.96-0.97, thus the improvement may be slightly.

[bryanwong17]

Got it. Thank you for your help!