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Found 3 papers, 1 papers with code
FUSION: Fully Unsupervised Test-Time Stain Adaptation via Fused Normalization Statistics
Stain variation, defined as a chromatic difference between the source and the target, is caused by varying characteristics during staining, resulting in a distribution shift and poor performance on the target.
Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection
At the image level, we compare convolutional neural networks (CNNs) with vision transformers, and contrast self-supervised learning (SSL) with supervised learning, followed by an evaluation of transfer learning compared with training from scratch.
SDCT-AuxNet$^θ$: DCT Augmented Stain Deconvolutional CNN with Auxiliary Classifier for Cancer Diagnosis
However, the development of such a tool for ALL cancer was challenging so far due to the non-availability of a large training dataset.
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