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Found 4 papers, 2 papers with code
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
Thus, weakly-supervised semantic segmentation techniques are proposed to utilize weak supervision that is cheaper and quicker to acquire.
Quantifying Explainers of Graph Neural Networks in Computational Pathology
However, popular deep learning methods and explainability techniques (explainers) based on pixel-wise processing disregard biological entities' notion, thus complicating comprehension by pathologists.
NINEPINS: Nuclei Instance Segmentation with Point Annotations
Deep learning-based methods are gaining traction in digital pathology, with an increasing number of publications and challenges that aim at easing the work of systematically and exhaustively analyzing tissue slides.
From visual words to a visual grammar: using language modelling for image classification
The Bag--of--Visual--Words (BoVW) is a visual description technique that aims at shortening the semantic gap by partitioning a low--level feature space into regions of the feature space that potentially correspond to visual concepts and by giving more value to this space.
