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Found 3 papers, 2 papers with code
TIAViz: A Browser-based Visualization Tool for Computational Pathology Models
Throughout the development of a machine learning (ML) model in digital pathology, it is crucial to have flexible, openly available tools to visualize models, from their outputs and predictions to the underlying annotations and images used to train or test a model.
MesoGraph: Automatic Profiling of Malignant Mesothelioma Subtypes from Histological Images
Tissue is represented by a cell graph with both cell-level morphological and regional features.
An Aggregation of Aggregation Methods in Computational Pathology
Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide images (WSIs) often process a large number of tiles (sub-images) and require aggregating predictions from the tiles in order to predict WSI-level labels.
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