Member of the MIDL board, initiator and member of the MICCAI Special Interest Group in Biomedical Image Registration (SIG-BIR), (co-)organizer of the Learn2Reg challenge, the Universal Lesion Segmentation challenge, and the MICCAI workshop on Lesion Evaluation and Follow-Up Assessment.
Research Experience
Worked as a research scientist at Fraunhofer MEVIS while pursuing her PhD; continued there as a senior scientist before fully transitioning to the Diagnostic Image Analysis Group in 2024.
Education
Studied Computational Life Science at the University of Lübeck, Germany. Completed her PhD as an external candidate under the supervision of Bram van Ginneken at the Diagnostic Image Analysis Group, focusing on deep-learning-based image registration and tumor follow-up analysis.
Background
Her current research focuses on efficient and accurate tumor follow-up assessment using deep learning. Furthermore, she is interested in the development of deep-learning-based image registration methods.
Miscellany
Current research projects include COMFORT, OncoFuture, Oncology, TotalReg, ULS23, and Unstructured Textual Data Integration for Radiology Image Analysis (UTDI).