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Found 3 papers, 1 papers with code
Benchmarking Domain Generalization Algorithms in Computational Pathology
Deep learning models have shown immense promise in computational pathology (CPath) tasks, but their performance often suffers when applied to unseen data due to domain shifts.
On generalisability of segment anything model for nuclear instance segmentation in histology images
Pre-trained on a large and diverse dataset, the segment anything model (SAM) is the first promptable foundation model in computer vision aiming at object segmentation tasks.
Domain Generalization in Computational Pathology: Survey and Guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology (CPath) by tackling intricate tasks across an array of histology image analysis applications.
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