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Found 4 papers, 2 papers with code
Histo-fetch -- On-the-fly processing of gigapixel whole slide images simplifies and speeds neural network training
We created a custom pipeline (histo-fetch) to efficiently extract random patches and labels from pathology whole slide images (WSIs) for input to a neural network on-the-fly.
A tool for user friendly, cloud based, whole slide image segmentation
As an extension of our previous work (arXiv:1812. 07509), we have developed a tool for segmentation of whole slide images (WSIs) with an easy to use graphical user interface.
Unsupervised Community Detection with a Potts Model Hamiltonian, an Efficient Algorithmic Solution, and Applications in Digital Pathology
We propose a fast statistical down-sampling of input image pixels based on the respective color features, and a new iterative method to minimize the Potts model energy considering pixel to segment relationship.
Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis
We track network performance improvements as a function of iteration and quantify the use of this pipeline for the segmentation of renal histologic findings on WSIs.
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