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Joining Forces for Pathology Diagnostics with AI Assistance: The EMPAIA Initiative
Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially.
Recommendations on test datasets for evaluating AI solutions in pathology
The recommendations are intended to help AI developers demonstrate the utility of their products and to help regulatory agencies and end users verify reported performance measures.
Improving Unsupervised Stain-To-Stain Translation using Self-Supervision and Meta-Learning
In digital pathology, many image analysis tasks are challenged by the need for large and time-consuming manual data annotations to cope with various sources of variability in the image domain.
Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations
Recently, generative adversarial networks exhibited excellent performances in semi-supervised image analysis scenarios.
CNN Cascades for Segmenting Whole Slide Images of the Kidney
Due to the increasing availability of whole slide scanners facilitating digitization of histopathological tissue, there is a strong demand for the development of computer based image analysis systems.
