DiagSet: a dataset for prostate cancer histopathological image classification

Understand

Cancer diseases constitute one of the most significant societal challenges.

• In this paper, we introduce a novel histopathological dataset for prostate cancer detection.
• The proposed dataset, consisting of over 2.6 million tissue patches extracted from 430 fully annotated scans, 4675 scans with assigned binary diagnoses, and 46 scans with diagnoses independently provided by a group of histopathologists can be found at https://github.com/michalkoziarski/DiagSet.
• Furthermore, we propose a machine learning framework for detection of cancerous tissue regions and prediction of scan-level diagnosis, utilizing thresholding to abstain from the decision in uncertain cases.