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Daniel Stromer M. Sc.

Researcher in the Learning Approaches for Medical Big Data Analysis (LAMBDA) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg


Room: 09.153

Phone: +49 9131 85-25246

E-Mail: daniel.stromer(at)

Research Areas

Document Analysis

Within my research project "Opens external link in new windowDigitization of Fragile Historical Documents by Using 3-D X-ray Computed Tomography" I try to face the challenge of reading sealed documents. This can be books or scrolls that were damaged by external influences (e.g., fire, water) or they are too fragile to open them due to aging processes. As conventional digitization methods (using a scan robot) fail in these particular cases, non-invasive methods, such as X-ray CT or Terahertz imaging, can be capable of revealing the hidden contents. Trying to optimize the entire scan pipeline - from scanning to a final digitization - is my major goal.

Non-destructive Testing

Closely related to my PhD project, I am also highly interested in image processing and machine-vision algorithms for non-destructive testing of materials and goods. This includes 3-D reconstruction, image/volume processing and segmentation algorithms. I mainly work with X-ray CT, however, I am also interested in other technologies such as Terahertz or Ultrasound. 

Medical Imaging

After 10 years of working in the field of healthcare engineering, I am still highly interested in the ongoing research. My Bachelor's and Master's theses were in collaboration with Siemens Healthcare where I tried to increase the quality of 3-D Scans and integrated a predictive maintenance system for C-arm CT's. At the moment, I am an exchange visitor for seven months at the Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT) working on segmentation/machine-vision algorithms for Optical Coherence Tomography (OCT).