dsmil-wsi
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About ABMIL
I have read ABMIL's code (https://github.com/AMLab-Amsterdam/AttentionDeepMIL), the input size of its model is: (1, bag_length, 1, width, height), due to the images of the dataset being very small, memory problems may not occur. But when using WSI, bag_length, width and height are very big, so how to apply ABMIL to WSIs for the comparison?
You need only to swap in the ABMIL aggregation head which takes precomputed feature vectors as inputs.
Thank you for your reply. Are these two lines of code the aggregation head which I need to swap? Then replace with an input layer suitable for precomputed feature vectors? https://github.com/AMLab-Amsterdam/AttentionDeepMIL/blob/master/model.py#L41
H = self.feature_extractor_part1(x)
H = H.view(-1, 50 * 4 * 4)