Development of methods for application factors in computer vision, such as interpretability, managing high-resolution images, inclusion of domain knowledge, etc.
Applying deep learning to vision problems in digital health
Martin Gerstmaier, M.Sc. IT Systems Engineering, HPI, Self-Attention in Medical Imaging
Marius Pullig, M.Sc., TU Berlin, Deep learning models for 3D MRI brain classification: a multi-sequence comparison
DuyHung Nguyen, M.Sc. IT Systems Engineering, HPI, Building a Text Embedding Model for the Imaging Research Warehouse at Mount Sinai
Tim Henning, M.Sc. IT Systems Engineering, HPI, HistoFlow: Label-Efficient and Interactive Deep Learning Cell Analysis
2019
Ahmed Rekik (M.Sc. IT Systems Engineering, HPI), Learning liver and tumor segmentation with small annotated datasets
Education
M.Sc. Digital Engineering, Otto-von-Guericke-Universität Magdeburg (2018)
Grade: 1.3, best of class 2018
Thesis: Automatic Landmark Detection for Preoperative Planning of Hip Surgery using Image Processing and Convolutional Neural Networks, in collaboration with Sectra Medical (Linköping, Sweden), Link
Semester abroad, Information systems, Universidade Federal de Santa Catarina, Brazil (2017)
Thesis: Design and development of a Car2Car communication interface for autonomous vehicles
Publications
Peer-reviewed conference articles
Da Cruz, H. F., Bergner, B., Konak, O., Schneider, F., Bode, P., Lempert, C., & Schapranow, M. P. (2019, October). MORPHER-A Platform to Support Modeling of Outcome and Risk Prediction in Health Research. In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 462-469). IEEE Computer Society. Link
Oleynik, M., Faessler, E., Sasso, A. M., Kappattanavar, A., Bergner, B., Da Cruz, H. F., ... & Böttinger, E. P. (2018, November). HPI-DHC at TREC 2018 Precision Medicine Track. In TREC. Link
Bergner, B., & Krempl, G. (2016). Active Subtopic Detection in Multitopic Data. In AL@ iKNOW (pp. 35- 44). Link
Preprints
Taleb, A., Loetzsch, W., Danz, N., Severin, J., Gaertner, T., Bergner, B., & Lippert, C. (2020). 3D Self-Supervised Methods for Medical Imaging. arXiv preprint arXiv:2006.03829. Link
Henning, T., Bergner, B., & Lippert, C. (2020). HistoFlow: Label-Efficient and Interactive Deep Learning Cell Analysis. bioRxiv. Link
Contact
Chair Representative:
Prof. Dr. Christoph Lippert Professor for Digital Health & Machine Learning Room: G-2.1.23 Tel.: +49-(0)331 5509-4850 E-Mail: office-lippert(at)hpi.de
Office:
Campus III, Haus G2 Room: G-2.1.22 Tel.: +49-(0)331 5509-4850 Fax: +49-(0)331 5509-4849 E-Mail: office-lippert(at)hpi.de
Visiting address:
Campus III Building G2 Rudolf-Breitscheid-Straße 187 14482 Potsdam, Germany