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

21 Apr 2022, 11:59 (modified: 04 Jun 2022, 12:07)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.
Registration: I acknowledge that acceptance of this work at MIDL requires at least one of the authors to register and present the work during the conference.
Authorship: I confirm that I am the author of this work and that it has not been submitted to another publication before.
Paper Type: recently published or submitted journal contributions
Primary Subject Area: Application: Histopathology
Secondary Subject Area: Detection and Diagnosis
Confidentiality And Author Instructions: I read the call for papers and author instructions. I acknowledge that exceeding the page limit and/or altering the latex template can result in desk rejection.
1 Reply