Ivana Išgum
University Professor of AI and Medical Imaging
Group Leader
Welcome to the page of the Quantitative Medical Image Analysis (QIA) group at the Amsterdam UMC. The QIA group is part of the Department of Biomedical Engineering and Physics, located at the AMC.
My group is focused on the development of algorithms for quantitative analysis of medical images to enable automatic patient risk profiling and prognosis using techniques from the fields of machine learning and deep learning. To develop clinically meaningful methods that can be applied, we closely collaborate with clinical researchers.
Marinka Oudkerk pool receives Best abstract award with the working group e-cardiology on the European Society of Cardiology conference 2020 for her abstract titled “Distinguishing sinus rhythm from atrial fibrillation on single-lead ECGs using a deep neural network”.
In a challenge on reconstructing accelerated brain MRI scans, the Recurrent Inference Machine developed in our group scored highest among all submitted models, read more here. Source code of the Deep learning for Image Reconstruction Toolbox (DIRECT) is available online.
We are co-organizing a workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020 on October 4, 2020 For details please follow this link.
RSNA report about our recent paper on calcium scoring based on the interview with Sanne van Velzen is available here.
Sanne receives award for her work on Coronary Artery Calcium Scoring: Can we do Better? proposing to score coronary calcium without thresholding
