Publikationen von Nico Scherf

Podranski, K.; Zhang, R.; Thierbach, K.; Thieleking, R.; Witte, A. V.; Villringer, A.; Weiskopf, N.; Scherf, N.: Detecting fat artifacts in diffusion MRI with deep learning. 9th IMPRS NeuroCom Summer School, Leipzig, Germany (2019)

Podranski, K.; Scherf, N.; Weiskopf, N.: Improving high-resolution qunatitative MRI maps for in-vivo histology MRI of the human brain. Medical Imaging Summer School 2018 - Medical Imaging Meets Deep Learning, Favignana, Italy (2018)

Kloenne, M.; Niehaus, S.; Lampe, L.; Merola, A.; Reinelt, J.; Scherf, N.: A framework for CT image segmentation inspired by the clinical environment. arXiv (2019)

Waschke, J.; Hlawitschka, M.; Anlas, K.; Trivedi, V.; Roeder, I.; Huisken, J.; Scherf, N.: linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser. (2021)

Hoffmann, H.; Baldow, C.; Zerjatke, T.; Gottschalk, A.; Wagner, S.; Karg, E.; Niehaus, S.; Roeder, I.; Glauche, I.; Scherf, N.: How to predict relapse in leukaemia using time series data: A comparative in silico study. (2020)

Horlava, N.; Mironenko, A.; Niehaus, S.; Wagner, S.; Roeder, I.; Scherf, N.: A comparative study of semi- and self-supervised semantic segmentation of biomedical microscopy data. (2020)

Wagner, S.; Thierbach, K.; Zerjatke, T.; Glauche, I.; Roeder, I.; Scherf, N.: TraCurate: Efficiently curating cell tracks. (2020)

Thierbach, K.; Bazin, P.-L.; De Back , W.; Gavriilidis, F.; Kirilina, E.; Jäger, C.; Morawski, M.; Geyer, S.; Weiskopf, N.; Scherf, N.: Combining deep learning and active contours opens the way to robust, automated analysis of brain cytoarchitectonics. (2018)

Shah, G.; Thierbach, K.; Schmid, B.; Reade, A.; Roeder, I.; Scherf, N.; Huisken, J.: Pan-embryo cell dynamics of germlayer formation in zebrafish. (2017)