Individualized breast cancer MRI screening in high-risk women enabled by machine learning
MALBACS is funded by the Vienna Comprehensive Cancer Center (CCC) to improve early detection and diagnosis of breast cancer.
Team: Georg Langs, Maria Bernathova, Lorenz Perschy, Philipp Seeböck, Bianca Burger, Yen Tan, Christian Singer, Thomas Helbich, Bettina Röthlin
Project summary:
The project aims at enhancing MRI breast cancer (BC) screening with help of machine learning, to improve improving the outcome for women at high-risk of developing BC. We will develop and validate machine learning techniques for personalized screening, early detection of breast cancer, and a reduction of false positives leading to unnecessary biopsies.
Publications
- Kamran M, Bernathova M, Varga R, Helbich TH, Langs G, Seeböck P. Beyond The Human Eye: Automatic Segmentation Of Breast
Lesions In High-Risk CE-MRI. ECR 2025 - Burger B, Bernathova M, Helbich T, Singer C F, Langs G: Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study, European Readiology Experimental 7, 32, (2023)
- Bianca Burger, Maria Bernathova, Philipp Seeböck, Christian F. Singer, Paola Clauser, Pascal Baltzer, Thomas H. Helbich, Georg Langs: AI-based Anomaly Detection Identifies Precursors of Future Lesions in Breast MRI of High-Risk Women: a Feasibility Study, ECR 2023
Lorenz Perschy Bianca Burger, Maria Bernathova, R. Varga, Thomas H. Helbich, Georg Langs, Philipp Seeböck. Prediction of breast cancer in high-risk patients using deep learning in MR imaging. accepted at ECR 2023
Image credits: MedUni Wien/Lorenz Perschy