Franziska Schirrmacher



Organisation


Lehrstuhl für Informatik 5 (Mustererkennung)
Sonderforschungsbereich/Transregio 89 Invasives Rechnen


Publications (Download BibTeX)


Stimpel, B., Syben, C., Schirrmacher, F., Hoelter, P., Dörfler, A., & Maier, A. (2019). Multi-Modal Super-Resolution with Deep Guided Filtering. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 110-115). Lübeck, DE: Springer Berlin Heidelberg.
Schirrmacher, F., Köhler, T., Husvogt, L., Fujimoto, J.G., Hornegger, J., & Maier, A. (2018). Abstract: QuaSI - Quantile Sparse Image A Prior for Spatio-Temporal Denoising of Retinal OCT Data. Paper presentation at Bildverarbeitung für die Medizin 2018, Erlangen.
Schirrmacher, F., Köhler, T., & Riess, C. (2018). Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging Problems.
Schirrmacher, F., Köhler, T., Endres, J., Lindenberger, T., Husvogt, L., Fujimoto, J.G.,... Maier, A. (2018). Temporal and Volumetric Denoising via Quantile Sparse Image Prior. Medical Image Analysis, 48(0), 131-146. https://dx.doi.org/10.1016/j.media.2018.06.002
Schirrmacher, F., Köhler, T., Husvogt, L., Fujimoto, J.G., Hornegger, J., & Maier, A. (2017). QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017, Proceedings, Part II (pp. 83-91). Quebec City, QC, Canada: Springer Verlag.
Schirrmacher, F., Taubmann, O., Unberath, M., & Maier, A. (2017). Towards Understanding Preservation of Periodic Object Motion in Computed Tomography. In Bildverarbeitung für die Medizin 2017 (pp. 116-121). DKFZ, Heidelberg: Springer Vieweg: Springer Vieweg.

Last updated on 2019-16-07 at 09:05