Results of the Medical Segmentation Decathlon challenge published in Nature Communications
The journal paper describing the Medical Segmentation Decathlon challenge has been published in Nature Communications.
News
Henkjan Huisman appointed Professor of Medical Imaging AI
From June 29, 2022, Henkjan Huisman is appointed Professor of Medical Imaging AI at the NTNU.
Mathias Prokop receives Honorary Membership at ESTI
The European Society of Thoracic Imaging (ESTI) assigns the Honorary Membership to Mathias Prokop for his outstanding contributions in thoracic imaging.
Francesco Ciompi appointed Associate Professor of Computational Pathology
Starting the 1st of June 2022, Francesco Ciompi is appointed Associate Professor of Computational Pathology at the Radboud UMC.
Second-place honor for short-talk Mohs AI tool during PhD retreat
Daan Geijs' short-talk on the development of a Mohs surgery AI tool was reviewed as second-best during the annual PhD retreat of RIHS.
Jeroen van der Laak appointed professor of Computational Pathology
From February 1, 2022, Jeroen van der Laak was appointed full professor of computational Pathology at the Radboud UMC.
PhD defense Wouter Bulten
Wouter Bulten succesfully defended his PhD thesis titled 'Artificial intelligence as a digital fellow in pathology: human-machine synergy for improved prostate cancer diagnosis.' on the 28th of January.
Results of the PANDA challenge published in Nature Medicine
After two years of hard work, the final results of PANDA Challenge on AI for prostate cancer grading are published!
New publication on Deep Learning for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography
The latest work by Natália Alves, titled “Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography”, has been published in Cancers' special issue on Pancreatic Cancer: Pathogenesis, Early Diagnosis, and Management for Improved Survival.
ERC Starting Grant for Geert Litjens
The European Research Council awarded Geert Litjens with a grant for his project "AIS-CaP: Interpretable Artificial Intelligence across Scales for Next-Generation Cancer Prognostics".