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Found 2 papers, 1 papers with code
CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification
On the other hand, acquiring extensive datasets with localized labels for training is not feasible.
Contrastive Learning
Histopathological Image Classification
+2
An attention-based multi-resolution model for prostate whole slide imageclassification and localization
The model achieved state-of-the-art performance for prostate cancer grading with an accuracy of 85. 11\% for classifying benign, low-grade (Gleason grade 3+3 or 3+4), and high-grade (Gleason grade 4+3 or higher) slides on an independent test set.
