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Much progress in the field of Computational Pathology may be attributed to so-called ‘grand challenges’, international competitions that invite researchers in AI to solve clinically relevant problems. These challenges are very attractive for the AI community, because they present a well-defined and relevant problem, and give access to the data required to build a solution as well as give a framework to evaluate the AI performance. In this three part session, of which the first part will be presented by Dr Geert Litjens, the concepts of grand challenges are explained, examples of previous challenges are discussed, and the results are shown of two very recent challenges: CONIC and TIGER.
Geert Litjens is an assistant professor of Computational Pathology at Radboud University Medical Center and co-chairs the Computation Pathology Group within the Diagnostic Image Analysis Group. His work focusses on application of modern machine learning methods to oncological pathology. Furthermore, he leads and participates in several research projects bridging the gap between medical specialties such as in prostate and pancreatic cancer. Last, within the European BIGPICTURE project he leads the work package on artificial intelligence.
Dr. Litjens been awarded several prestigious Dutch and European grants and awards, such as the NWO Veni and Vidi, an ERC Starting Grant, and a KNAW Early Career Award. He is member of the MIDL Board and on the editorial board of Medical Image Analysis. Last, he is a prolific organizer of challenges in medical image analysis, such as PROMISE12, CAMELYON, and PANDA.
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