Computational Health Center Institute of Machine Learning in Biomedical Imaging
The Institute of Machine Learning in Biomedical Imaging (IML) focuses on research to leverage machine learning for the grand challenges in biomedical imaging in areas of unmet clinical need. Its goal is to transform the use of imaging for diagnostics and prognostics fundamentally. Novel and affordable solutions should empower clinics to make more accurate, fast, and reliable decisions for early detection, treatment planning, and improved patient outcomes. Julia Schnabel’s research focus is on applications in cancer, cardiovascular diseases, and maternal/perinatal health.
For more information on our team, up-to-date research news, and open positions, please visit our website.
The Institute of Machine Learning in Biomedical Imaging (IML) focuses on research to leverage machine learning for the grand challenges in biomedical imaging in areas of unmet clinical need. Its goal is to transform the use of imaging for diagnostics and prognostics fundamentally. Novel and affordable solutions should empower clinics to make more accurate, fast, and reliable decisions for early detection, treatment planning, and improved patient outcomes. Julia Schnabel’s research focus is on applications in cancer, cardiovascular diseases, and maternal/perinatal health.
For more information on our team, up-to-date research news, and open positions, please visit our website.
Our Key Publications
2025 Nature Communications
2024 Nature Reviews Cardiology
2024 IEEE Transactions on Medical Imaging
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review