Braumann, U.-D.; Scherf, N.; Einenkel, J.; Horn, L.-C.; Wentzensen, N.; Loeffler, M.; Kuska, J.-P.: Large histological serial sections for computational tissue volume reconstruction. Methods of Information in Medicine 46 (5), S. 614 - 622 (2007)

Burek, P.; Scherf, N.; Herre, H.: On the ontological foundations of cellular development. In: Proceedings of the Joint Ontology Workshops (JOWO) 2020. (2020)

Burek, P.; Scherf, N.; Herre, H.: On the formal representation and annotation of cellular genealogies. In: Knowledge Engineering and Knowledge Management: Lecture Notes in Computer Science, Bd. 12387, S. 194 - 203 (Hg. Keet, C. M.; Dumontier, M.). Springer International Publishing, Cham (2020)

De Back , W.; Seurig, S.; Wagner, S.; Marre, B.; Roeder, I.; Scherf, N.: Forensic age estimation with Bayesian convolutional neural networks based on panoramic dental X-ray imaging. In: Proceedings of the 2019 International Conference on Medical Imaging with Deep Learning (MIDL). (2019)

Kloenne, M.; Niehaus, S.; Lampe, L.; Merola, A.; Reinelt, J.; Scherf, N.: Convolutional neural network stacking for medical image segmentation in CT scans. In: 2019 Kidney Tumor Segmentation Challenge. MICCAI 2019, Shenzhen, China, 13. Oktober 2019 - 19. Oktober 2019. University of Minnesota Libraries Publishing, Minneapolis, MN (2019)

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. In: Machine Learning in Medical Imaging 2018, S. 179 - 187. 9th International Workshop on Machine Learning in Medical Imaging, Granada, Spain, 16. September 2018. Springer, Cham (2018)

Thierbach, K.; Shah, G.; Glauche, I.; Huisken, J.; Roeder, I.; Scherf, N.: Biology-inspired visualization of morphogenetic motion in the zebrafish endoderm. In: Proceedings of the 13th International Symposium on Biomedical Imaging (ISBI), S. 925 - 929. (2016)

Becker, T.; Kanje, W.; Rapoport, D.; Thierbach, K.; Scherf, N.; Roeder, I.; Mamlouk, A. M.: The benchmark data SET CeTReS.B-MI for in vitro mitosis detection. In: Proceedings of the 11th International Symposium on Biomedical Imaging (ISBI), S. 469 - 472. (2014)

Burek, P.; Scherf, N.; Herre, H.: OWL patterns for modeling the change over time exemplified by the cell tracking ontology. In: Ontologies and Data in Life Sciences (ODLS 2014). (2014)

Scherf, N.; Zerjatke, T.; Klemm, K.; Glauche, I.; Roeder, I.: Beyond genealogies: Mutual information of causal paths to analyse single cell tracking data. In: Proceedings of the 10th International Symposium on Biomedical Imaging, S. 440 - 443. (2013)

Scherf, N.; Kunze, M.; Thierbach, K.; Zerjatke, T.; Burek, P.; Herre, H.; Glauche, I.; Roeder, I.: Assisting the machine paradigms for human-machine interaction in single cell tracking. In: Bildverarbeitung für die Medizin 2013, S. 116 - 121 (Hg. Meinzer, H.-P.; Deserno, T. M.; Handels, H.; Tolxdorff, T.). Springer Berlin Heidelberg, Berlin, Heidelberg (2013)

Burek, P.; Herre, H.; Roeder, I.; Glauche, I.; Scherf, N.; Löffler, M.: Towards a cellular genealogy ontology. In: Proceedings of the OBML 2010 Workshop. (2010)

Scherf, N.; Kuska, J.-P.; Heine, C.; Braumann, U.-D.; Franke, H.: Segmentation of axonal fibres in tissue slices. Bildverarbeitung für die Medizin 2008, S. 178 - 182 (2008)

Brammerloh, M.; Weigelt, I.; Arendt, T.; Gavriilidis, F.; Scherf, N.; Jankuhn, S.; Morawski, M.; Weiskopf, N.; Kirilina, E.: Iron-induced relaxation mechanisms in the human substantia nigra: Towards quantifying iron load in dopaminergic neurons. In Proceedings of the ISMRM 26th Annual Meeting & Exhibition. Joint Annual Meeting ISMRM-ESMRMB 2018, Paris Expo Porte de Versailles, 16. Juni 2018 - 21. Juni 2019. (2018)

Heine, C.; Scherf, N.; Sygnecka, K.; Egerland, U.; Hage, T.; Franke, H.: Inhibitors of the phosphodiesterase 2 increased axonal fibre growth in a dopaminergic organotypic ex vivo slice co-culture model. In BMC Pharmacology, 11, S. P34 - P34. BioMed Central, London (2011)

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)

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. bioRxiv (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. medRxiv (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. arXiv (2020)