Sarah van Riel successfully defended her PhD thesis titled 'Malignancy risk estimation of screen-detected pulmonary nodules: validation of current management recommendations' on the 9th of December.
Midas Meijs successfully defended his PhD thesis titled 'Automated Image Analysis and Machine Learning to Detect Cerebral Vascular Pathology in 4D-CTA' on the 26th of November.
Sarah van Riel will defend her PhD thesis with the title 'Malignancy risk estimation of screen-detected pulmonary nodules: validation of current management recommendations' on 9th of December at 13.30.
Midas Meijs will defend his PhD thesis with the title, "Automated Image Analysis and Machine Learning to Detect Cerebral Vascular Pathology in 4D-CTA" on 26th of November at 15.30.
Francesco Ciompi of the Computational Pathology group has received a prestigious NWO-TTW VIDI grant of 800,000 euro for his project "Predicting Lung Cancer Immunotherapy Response. It's personal".
Nikolas Lessmann and Bram van Ginneken of DIAG received a TURBO grant of 80,000 euro for a collaboration project with Jelmer Wolterink and Christoph Brune from the faculty of Applied Mathematics at the University of Twente and Esther Tanck and Dennis Janssen from the Department of Orthopedics of Radboudumc …
Friday, September 25, 2020, the first AI for Health course concluded with a meeting where all participants presented their AI projects' results. About 25 Radboudumc employees from different backgrounds followed the first course. The second edition has now started and will run until February 2021. The third edition is scheduled …
In this project we aim to develop and validate AI techniques for the detection of serous tubal intra-epithelial carcinoma (STIC), a non-invasive lesion in the distal Fallopian tube which is expected to be a precursor for ovarian cancer.
Maschenka Balkenhol succesfully defended her PhD thesis titled 'Tissue-based biomarker assessment for predicting prognosis of triple negative breast cancer: the additional value of artificial intelligence' on the 15th of September.
The impact of scanner variations and stain normalization on CNN performance for prostate cancer classification on WSIs was investigated by Zaneta Swiderska-Chadaj and their colleagues, and the work was published in Nature Scientific Reports.