Prof. Dr.-Ing. Andreas Maier


Please find more details on my website.





Organisation


Department Informatik
Lehrstuhl für Informatik 5 (Mustererkennung)


Awards / Honours


2018 : ERC Synergy Grant



Project lead

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(Advancing osteoporosis medicine by observing bone microstructure and remodelling using a fourdimensional nanoscope):
4-D nanoSCOPE: Advancing osteoporosis medicine by observing bone microstructure and remodelling using a fourdimensional nanoscope
Prof. Dr.-Ing. Andreas Maier
(01/04/2019 - 31/03/2025)

(TIME MACHINE : BIG DATA OF THE PAST FOR THE FUTURE OF EUROPE):
Time Machine: Big Data of the Past for the Future of Europe
Prof. Dr.-Ing. Andreas Maier
(01/03/2019 - 29/02/2020)

Ait4Surgery: Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries
Prof. Dr. Björn Eskofier; Prof. Dr.-Ing. Andreas Maier
(01/06/2018 - 31/05/2021)

Verbesserte Charakterisierung des Versagensverhaltens von Blechwerkstoffen durch den Einsatz von Mustererkennungsmethoden
Prof. Dr.-Ing. Andreas Maier
(01/04/2017 - 31/03/2019)

DISPARITY: Digital, Semantic and Physical Analysis of Media Integrity
Prof. Dr.-Ing. Andreas Maier; Dr.-Ing. Christian Riess
(24/05/2016 - 23/05/2017)


Project member


ICONOGRAPHICS: ICONOGRAPHICS: Computational Understanding of Iconography and Narration in Visual Cultural Heritage
Prof. Dr. Peter Bell
(01/04/2019 - 31/03/2021)

Computer-based motive assessment
Prof. Dr. Oliver Schultheiss
(01/01/2016)


Publications (Download BibTeX)

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Li, Q., Luckner, C., Hertel, M., Radicke, M., & Maier, A. (2019). Combining Ultrasound and X-Ray Imaging for Mammography. In Bildverarbeitung für die Medizin 2019. (pp. 245--250). Springer.
Aubreville, M., Stöve, M., Oetter, N., Goncalves, M., Knipfer, C., Neumann, H.,... Maier, A. (2019). Deep learning-based detection of motion artifacts in probe-based confocal laser endomicroscopy images. International Journal of Computer Assisted Radiology and Surgery, 14(1), 31-42. https://dx.doi.org/10.1007/s11548-018-1836-1
Xu, Y., Schebesch, F., Ravikumar, N., & Maier, A. (2019). Detection of Unseen Low-Contrast Signals Using Classic and Novel Model Observers. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 212-217). Lübeck, DE: Springer Berlin Heidelberg.
Jaremenko, C., Ravikumar, N., Affronti, E., Merklein, M., & Maier, A. (2019). Determination of Forming Limits in Sheet Metal Forming Using Deep Learning. Materials, 12(7). https://dx.doi.org/10.3390/ma12071051
Vesal, S., Ravikumar, N., & Maier, A. (2019). Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRI. In STACOM 2018: Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges (pp. 319-328). Springer Verlag.
Folle, L., Vesal, S., Ravikumar, N., & Maier, A. (2019). Dilated deeply supervised networks for hippocampus segmentation in MRI. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 68-73). Lübeck, DE: Springer Berlin Heidelberg.
Preuhs, A., Maier, A., Manhart, M., Fotouhi, J., Navab, N., & Unberath, M. (2019). Double Your Views: Exploiting Symmetry in Transmission Imaging. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 171-). Lübeck, DE: Springer Berlin Heidelberg.
Roser, P., Birkhold, A., Zhong, X., Stepina, E., Kowarschik, M., Fahrig, R., & Maier, A. (2019). Effects of Tissue Material Properties on X-Ray Image, Scatter and Patient Dose A Monte Carlo Simulation. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 270-275). Lübeck, DE: Springer Berlin Heidelberg.
Stromer, D., Vetter, A., Özkan, H.C., Probst, C., & Maier, A. (2019). Enhanced Crack Segmentation (eCS): A Reference Algorithm for Segmenting Cracks in Multicrystalline Silicon Solar Cells. IEEE Journal of Photovoltaics, 9(3), 752-758. https://dx.doi.org/10.1109/JPHOTOV.2019.2895808
Syben, C., Stimpel, B., Lommen, J., Würfl, T., Dörfler, A., & Maier, A. (2019). Fan-to-Parallel Beam Conversion: Deriving Neural Network Architectures Using Precision Learning. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 29-). Lübeck, DE: Springer Berlin Heidelberg.

Last updated on 2019-22-01 at 17:48