The objective of the 4-year project MARBLE is to develop and validate AI algorithms for breast cancer screening.
MARBLE description
While population-based breast cancer screening with mammography has shown to be very effective, mammography alone is not sufficient for the adequate screening of women who are carriers of genetic mutations or have other risk factors for breast cancer. In this project, we research how to improve early diagnosis of breast cancer through machine learning on image data from different types (e.g 2D and 3D tomography) and vendors (e.g. Siemens and Hologic). We will develop and validate machine learning algorithms for transfer learning and assess their effectiveness and limitations in the considered context. In MARBLE our industrial partner Screenpoint Medical, providing valorization and the RUMC are directly involved.
Funding
People at the Data Science department
Gijs van Tulder (PostDoc), Yao Tong (PhD student), Elena Marchiori (WP leader).