Lehrstuhl für Informatik 5 (Mustererkennung)


Beschreibung:


Wissenschaftler und Studenten am Lehrstuhl für Mustererkennung (LME) beschäftigen sich mit der Erforschung und Realisierung von Algorithmen zur Klassifikation und Analyse von Mustern wie beispielsweise Bild- oder Sprachdaten. Die laufenden Forschungsprojekte sind überwiegend interdisziplinär und konzentrieren sich auf folgende Gebiete: Medizinische Bildverarbeitung und Anwendungen im Gesundheitswesen. Der Lehrstuhl pflegt enge nationale und internationale Kontakte zu anderen Universitäten, Forschungseinrichtungen und Industrieunternehmen.



Eine Zusammenfassung der Lehrstuhlprojekte finden Sie in unserer ausführlichen Informationsbrochure (PDF)

Adresse:
Martensstraße 3
91058 Erlangen



Untergeordnete Organisationseinheiten

Juniorprofessur für Medizinische Bildverarbeitung
Professur für Informatik (Mustererkennung)
Stiftungs-Juniorprofessur für Sportinformatik (Digital Sports) - Umwidmung / Auflösung


Forschungsbereiche

Big Data Applications
Medical Image Processing
Pattern Recognition & Machine Learning
Sprachverarbeitung und Sprachverstehen


Forschungsprojekt(e)

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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: Automatisiertes Intraoperatives Tracking zu Ablauf- und Dosisüberwachung in Röntgengestützten Minimalinvasiven Eingriffen
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)



Publikationen (Download BibTeX)

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Bopp, J., Ludwig, V., Seifert, M., Pelzer, G., Maier, A., Anton, G., & Riess, C. (2019). Simulation study on X-ray phase contrast imaging with dual-phase gratings. International Journal of Computer Assisted Radiology and Surgery, 14(1), 3-10. https://dx.doi.org/10.1007/s11548-018-1872-x
Huang, X., Yang, H., Huang, Y., Shi, L., He, F., Maier, A., & Yan, M. (2019). Robust mixed one-bit compressive sensing. Signal Processing, 162, 161-168. https://dx.doi.org/10.1016/j.sigpro.2019.04.011
Bayer, S., Zhai, Z., Strumia, M., Tong, X., Gao, Y., Staring, M.,... Ravikumar, N. (2019). Registration of vascular structures using a hybrid mixture model. International Journal of Computer Assisted Radiology and Surgery, 1–10. https://dx.doi.org/10.1007/s11548-019-02007
Deitsch, S., Christlein, V., Berger, S., Buerhop-Lutz, C., Maier, A., Gallwitz, F., & Riess, C. (2019). Automatic classification of defective photovoltaic module cells in electroluminescence images. Solar Energy, 185, 455-468. https://dx.doi.org/10.1016/j.solener.2019.02.067
Yu, Z., Xiang, Q., Meng, J., Kou, C., Ren, Q., & Lu, Y. (2019). Retinal image synthesis from multiple-landmarks input with generative adversarial networks. Biomedical Engineering Online, 18. https://dx.doi.org/10.1186/s12938-019-0682-x
Facco Rodrigues, V., da Rosa Righi, R., Andre da Costa, C., Eskofier, B., & Maier, A. (2019). On Providing Multi-Level Quality of Service for Operating Rooms of the Future. Sensors, 19(10). https://dx.doi.org/10.3390/s19102303
Christlein, V. (2019). Handwriting Analysis with Focus on Writer Identification and Writer Retrieval (Dissertation).
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
Minakaki, G., Canneva, F., Chevessier, F., Bode, F., Menges, S., Timotius, I.,... Klucken, J. (2019). Treadmill exercise intervention improves gait and postural control in alpha-synuclein mouse models without inducing cerebral autophagy. Behavioural Brain Research, 363, 199-215. https://dx.doi.org/10.1016/j.bbr.2018.11.035
Schröter, H., Nöth, E., Maier, A., Cheng, R., Barth, V., & Bergler, C. (2019). Segmentation, Classification, and Visualization of Orca Calls Using Deep Learning. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 8231-8235). Brighton, GB: IEEE.
Maier, A., Syben, C., Lasser, T., & Riess, C. (2019). A gentle introduction to deep learning in medical image processing [Eine sanfte Einführung in Tiefes Lernen in der Medizinischen Bildverarbeitung]. Zeitschrift für Medizinische Physik, 29(2), 86-101. https://dx.doi.org/10.1016/j.zemedi.2018.12.003
Martindale, C., Sprager, S., & Eskofier, B. (2019). Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables. Sensors, 198. https://dx.doi.org/10.3390/s19081820
Mullan, P., Rieß, C., & Freiling, F. (2019). Forensic Source Identification using JPEG Image Headers: The Case of Smartphones. In Digital Investigation. Oslo, NO.
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
Stelzle, F., Oetter, N., Göllner, L., Adler, W., Rohde, M., Maier, A.,... Knipfer, C. (2019). Speech intelligibility in patients with oral cancer: An objective baseline evaluation of pretreatment function and impairment. Head and Neck-Journal For the Sciences and Specialties of the Head and Neck, 41(4), 1063-1069. https://dx.doi.org/10.1002/hed.25527
Schneider, M., Janas, G., Lugauer, F., Hoppe, E., Nickel, D., Dale, B.M.,... Bashir, M.R. (2019). Accurate fatty acid composition estimation of adipose tissue in the abdomen based on bipolar multi-echo MRI. Magnetic Resonance in Medicine, 81(4), 2330-2346. https://dx.doi.org/10.1002/mrm.27557
Diaz-Pinto, A., Morales, S., Naranjo, V., Köhler, T., Mossi, J.M., & Navea, A. (2019). CNNs for automatic glaucoma assessment using fundus images: an extensive validation. Biomedical Engineering Online, 18. https://dx.doi.org/10.1186/s12938-019-0649-y
Seifert, M., Ludwig, V., Käppler, S., Horn, F., Meyer, P., Pelzer, G.,... Anton, G. (2019). Talbot-Lau x-ray phase-contrast setup for fast scanning of large samples. Scientific Reports, 9. https://dx.doi.org/10.1038/s41598-018-38030-3
Zhong, X., Roser, P., Bayer, S., Ravikumar, N., Strobel, N., Birkhold, A.,... Maier, A. (2019). Pediatric Patient Surface Model Atlas Generation and X-Ray Skin Dose Estimation. In BVM. Lübeck, DE.
Felsner, L., Hu, S., Ludwig, V., Anton, G., Maier, A., & Rieß, C. (2019). On the Characteristics of Helical 3-D X-ray Dark-field Imaging. In Proceedings of the Bildverarbeitung für die Medizin (BVM 2019) (pp. 264-269). Lübeck.


Zusätzliche Publikationen (Download BibTeX)


Hariharan, S.G., Strobel, N., Kaethner, C., Kowarschik, M., Fahrig, R., & Navab, N. (2019). An analytical approach for the simulation of realistic low-dose fluoroscopic images. International Journal of Computer Assisted Radiology and Surgery, 14(4), 601-610. https://dx.doi.org/10.1007/s11548-019-01912-6
Hariharan, S.G., Kaethner, C., Strobel, N., Kowarschik, M., DiNitto, J., Albarqouni, S.,... Navab, N. (2019). Preliminary results of DSA denoising based on a weighted low-rank approach using an advanced neurovascular replication system. International Journal of Computer Assisted Radiology and Surgery. https://dx.doi.org/10.1007/s11548-019-01968-4

Zuletzt aktualisiert 2019-24-04 um 10:15