Histopathological Segmentation
3 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Histopathological Segmentation
CoCaHis
Most implemented papers
GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentation
suhas-srinath/genselfdiff-his
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The basic idea of SSL is to train a network to perform one or many pseudo or pretext tasks on unannotated data and use it subsequently as the basis for a variety of downstream tasks.
Weakly supervised multiple instance learning histopathological tumor segmentation
MarvinLer/tcga_segmentation
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In this paper, we propose a weakly supervised framework for whole slide imaging segmentation that relies on standard clinical annotations, available in most medical systems.
Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for deploying models in an interactive interface.
