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Found 3 papers, 1 papers with code
GRASP: GRAph-Structured Pyramidal Whole Slide Image Representation
In this work, we present GRASP, a novel graph-structured multi-magnification framework for processing WSIs in digital pathology.
VOLTA: an Environment-Aware Contrastive Cell Representation Learning for Histopathology
To showcase the potential power of our proposed framework, we applied VOLTA to ovarian and endometrial cancers with very small sample sizes (10-20 samples) and demonstrated that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide novel insights that link histopathology and molecular subtypes of endometrial cancer.
CCRL: Contrastive Cell Representation Learning
In this work, we investigated the utility of Self-Supervised Learning (SSL) in cell clustering by proposing the Contrastive Cell Representation Learning (CCRL) model.
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