Gleason grading of prostate cancer using artificial intelligence: lessons learned from the PANDA challenge

Kimmo Kartasalo, Peter Ström, Martin Eklund, Wouter Bulten, Hans Pinckaers, Geert Litjens, Po-Hsuan Cameron Chen, Kunal Nagpal, Pekka Ruusuvuori

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Assessing prostate biopsies is crucial for the clinical management of patients with suspected prostate cancer, but is associated with complications such as inter-observer variability. The PANDA challenge aimed at mitigating these issues through development and rigorous validation of image analysis algorithms for the task. In this short paper, we summarize the key insights gained from PANDA from the viewpoints of algorithm development and challenge organisation.
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Wednesday 6th July
Poster Session 1.1 - onsite 15:20 - 16:20, virtual 11:00 - 12:00 (UTC+2)
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