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

21 Apr 2022, 11:59 (edited 04 Jun 2022)MIDL 2022 Short PapersReaders: Everyone
  • Keywords: Computational pathology, prostate cancer, Gleason grading, challenge
  • TL;DR: Summary of the findings from the Prostate cancer grade assessment (PANDA) challenge
  • Abstract: 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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  • Paper Type: recently published or submitted journal contributions
  • Primary Subject Area: Application: Histopathology
  • Secondary Subject Area: Detection and Diagnosis
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