Automated Gleason Grading of Prostate Biopsies using Deep Learning

The Gleason score is the most important prognostic marker for prostate cancer patients but suffers from significant inter-observer variability. We developed a fully automated deep learning system to grade prostate biopsies. The system was developed using 5834 biopsies from 1243 patients. A semi-auto...

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Bibliographic Details
Published in:arXiv.org 2019-07
Main Authors: Bulten, Wouter, Pinckaers, Hans, Hester van Boven, Vink, Robert, Thomas de Bel, Bram van Ginneken, Jeroen van der Laak, Christina Hulsbergen-van de Kaa, Litjens, Geert
Format: Article
Language:English
Subjects:
Annotations
Automation
Biopsy
Deep learning
Evaluation
Machine learning
Prostate cancer
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Summary:The Gleason score is the most important prognostic marker for prostate cancer patients but suffers from significant inter-observer variability. We developed a fully automated deep learning system to grade prostate biopsies. The system was developed using 5834 biopsies from 1243 patients. A semi-automatic labeling technique was used to circumvent the need for full manual annotation by pathologists. The developed system achieved a high agreement with the reference standard. In a separate observer experiment, the deep learning system outperformed 10 out of 15 pathologists. The system has the potential to improve prostate cancer prognostics by acting as a first or second reader.
ISSN:2331-8422
DOI:10.48550/arxiv.1907.07980