Prof. Dr. Marc Aubreville


Prof. Dr. Marc Aubreville

Forschungsprofessor, Studienfachberater Computational Life Sciences

Raum: A236
Lehrgebiet: Bildverstehen und medizinische Anwendung der künstlichen Intelligenz
Fakultät: Fakultät I

Vita


  • Seit 10/2020 Forschungsprofessor an der THI
  • 05/2020-09/2020 (Teilzeit): Post-doc am Lehrstuhl für Mustererkennung der Friedrich-Alexander-Universität Erlangen-Nürnberg
  • 10/2016-05/2020 (Teilzeit): Promotion am Lehrstuhl für Mustererkennung der Friedrich-Alexander-Universität Erlangen-Nürnberg
  • 04/2017-09/2020 (Teilzeit): Systemarchitekt, Sivantos GmbH
  • 02/2010-03/2017: Entwicklungsingenieur Audiosignalverarbeitung, Siemens Audiologische Technik GmbH / Sivantos GmbH
  • 10/2003-12/2009: Studium der Elektro- und Informationstechnik, Karlsruher Institut für Technologie

Veröffentlichungen


  • Sievert, M., Mantsopoulos, K., Mueller, S. K., Eckstein, M., Rupp, R., Aubreville, M., … Goncalves, M. (2022). Systematic interpretation of confocal laser endomicroscopy: larynx and pharynx confocal imaging score. ACTA Otorhinolaryngologica Italica, 1–8.
  • Sievert, M., Oetter, N., Aubreville, M., Stelzle, F., Maier, A., Eckstein, M., … Others. (2021). Feasibility of intraoperative assessment of safe surgical margins during laryngectomy with confocal laser endomicroscopy: a pilot study. Auris Nasus Larynx48(4), 764–769.
  • Sievert, M., Stelzle, F., Aubreville, M., Mueller, S. K., Eckstein, M., Oetter, N., … Goncalves, M. (2021). Intraoperative free margins assessment of oropharyngeal squamous cell carcinoma with confocal laser endomicroscopy: a pilot study. European Archives of Oto-Rhino-Laryngology278(11), 4433–4439.
  • Aubreville, M., Bertram, C., Veta, M., Klopfleisch, R., Stathonikos, N., Breininger, K., … Maier, A. (2021). Quantifying the Scanner-Induced Domain Gap in Mitosis Detection. Medical Imaging with Deep Learning (MIDL)2021.
  • Goncalves, M., Stelzle, F., Aubreville, M., Mueller, S. K., Eckstein, M., Oetter, N., … Sievert, M. (2021). Intraoperative Free Margins Assessment of Oropharyngeal Squamous Cell Carcinoma with Confocal Laser Endomicroscopy: A Pilot Study. Laryngo-Rhino-Otologie100(S 02).
  • Bertram, C. A., Aubreville, M., Donovan, T. A., Bartel, A., Wilm, F., Marzahl, C., … Others. (2021). Computer-assisted mitotic count using a deep learning--based algorithm improves interobserver reproducibility and accuracy. Veterinary pathology, 03009858211067478.
  • Sievert, M., Eckstein, M., Mantsopoulos, K., Mueller, S. K., Stelzle, F., Aubreville, M., … Goncalves, M. (2021). Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma. European Archives of Oto-Rhino-Laryngology, 1–9.
  • Ganz, J., Kirsch, T., Hoffmann, L., Bertram, C. A., Hoffmann, C., Maier, A., … Aubreville, M. (2021). Automatic and explainable grading of meningiomas from histopathology images. MICCAI Workshop on Computational Pathology, 69–80. PMLR.
  • Theelke, L., Wilm, F., Marzahl, C., Bertram, C. A., Klopfleisch, R., Maier, A., … Aubreville, M., Breininger, K. (2021). Iterative Cross-Scanner Registration for Whole Slide Images. Proceedings of the IEEE/CVF International Conference on Computer Vision, 582–590.
  • Donovan, T. A., Moore, F. M., Bertram, C. A., Luong, R., Bolfa, P., Klopfleisch, R., … Aubreville,M., Meuten, D. (2021). Mitotic Figures—Normal, Atypical, and Imposters: A Guide to Identification. Veterinary pathology58(2), 243–257.
  • Marzahl, C., Aubreville, M., Bertram, C. A., Maier, J., Bergler, C., Kröger, C., … Maier, A. (2021). EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control. Scientific reports11(1), 1–11.
  • Bertram, C. A., Veta, M., Marzahl, C., Stathonikos, N., Maier, A., Klopfleisch, R., & Aubreville, M. (2020). Are pathologist-defined labels reproducible? Comparison of the TUPAC16 mitotic figure dataset with an alternative set of labels. In Interpretable and Annotation-Efficient Learning for Medical Image Computing (bll 204–213). Springer, Cham.
  • Aubreville, M., Bertram, C. A., Marzahl, C., Gurtner, C., Dettwiler, M., Schmidt, A., … Maier, A. (2020). Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region. Scientific RepoRtS10(1), 1–11.
  • Aubreville, M., Bertram, C. A., Donovan, T. A., Marzahl, C., Maier, A., & Klopfleisch, R. (2020). A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research. Scientific data7(1), 1–10.
  • Marzahl, C., Aubreville, M., Bertram, C. A., Stayt, J., Jasensky, A.-K., Bartenschlager, F., … Others. (2020). Deep learning-based quantification of pulmonary hemosiderophages in cytology slides. Scientific Reports10(1), 1–10.
  • Bertram, C. A., Aubreville, M., Gurtner, C., Bartel, A., Corner, S. M., Dettwiler, M., … Others. (2020). Computerized calculation of mitotic count distribution in canine cutaneous mast cell tumor sections: mitotic count is area dependent. Veterinary pathology57(2), 214–226.
  • Marzahl, C., Bertram, C. A., Aubreville, M., Petrick, A., Weiler, K., Gläsel, A. C., … Others. (2020). Are fast labeling methods reliable? A case study of computer-aided expert annotations on microscopy slides. International Conference on Medical Image Computing and Computer-Assisted Intervention, 24–32. Springer, Cham.
  • Aubreville, M., Stoeve, 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 surgery14(1), 31–42.
  • Goncalves, M., Aubreville, M., Mueller, S. K., Sievert, M., Maier, A., Iro, H., & Bohr, C. (2019). Probe-based confocal laser endomicroscopy in detecting malignant lesions of vocal folds. ACTA Otorhinolaryngologica Italica39(6), 389.
  • Bertram, C. A., Aubreville, M., Marzahl, C., Maier, A., & Klopfleisch, R. (2019). A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor. Scientific data6(1), 1–9.
  • Aubreville, M., Bertram, C., Klopfleisch, R., & Maier, A. (2018). SlideRunner - A Tool for Massive Cell Annotations in Whole Slide Images. In Bildverarbeitung für die Medizin 2018 (bll 309–314). Springer Vieweg, Berlin, Heidelberg.
  • Aubreville, M., Ehrensperger, K., Maier, A., Rosenkranz, T., Graf, B., & Puder, H. (2018). Deep denoising for hearing aid applications. 2018 16th International Workshop on Acoustic Signal Enhancement (IWAENC), 361–365. IEEE.
  • Aubreville, M., Knipfer, C., Oetter, N., Jaremenko, C., Rodner, E., Denzler, J., … Maier, A. (2017). Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning. Scientific reports7(1), 1–10.

 

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