Publications of Nico Scherf

Bach, E., Zerjatke, T., Herklotz, M., Scherf, N., Niederwieser, D., Roeder, I., … Glauche, I. (2014). Elucidating functional heterogeneity in hematopoietic progenitor cells: A combined experimental and modeling approach. Experimental Hematology, 42, 826–837.e17.

Rashidi, N. M., Scott, M. K., Scherf, N., Krinner, A., Kalchschmidt, J. S., Gounaris, K., … Lo Celso, C. (2014). In vivo time-lapse imaging shows diverse niche engagement by quiescent and naturally activated hematopoietic stem cells. Blood, 124, 79–83.

Heine, C., Sygnecka, K., Scherf, N., Berndt, A., Egerland, U., Hage, T., & Franke, H. (2013). Phosphodiesterase 2 inhibitors promote axonal outgrowth in organotypic slice co-cultures. Neurosignals, 21, 197–212.

Weber, M., Scherf, N., Kahl, T., Braumann, U.-D., Scheibe, P., Kuska, J.-P., … Franke, H. (2013). Quantitative analysis of astrogliosis in drug-dependent humans. Brain Research, 1500, 72–87.

Schmid, B., Shah, G., Scherf, N., Weber, M., Thierbach, K., Campos, C. P., … Huisken, J. (2013). High-speed panoramic light-sheet microscopy reveals global endodermal cell dynamics. Nature Communications, 4. doi:10.1038/ncomms3207

Scherf, N., Herberg, M., Thierbach, K., Zerjatke, T., Kalkan, T., Humphreys, P., … Roeder, I. (2012). Imaging, quantification and visualization of spatio-temporal patterning in mESC colonies under different culture conditions. Bioinformatics, 28, i556–i561.

Scherf, N., Franke, K., Glauche, I., Kurth, I., Bornhäuser, M., Werner, C., … Roeder, I. (2012). On the symmetry of siblings: Automated single-cell tracking to quantify the behavior of hematopoietic stem cells in a biomimetic setup. Experimental Hematology, 40, 119–130.e9.

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

Kiakou, D., Adamopoulos, A., & Scherf, N. (2023). Graph-based disease prediction in neuroimaging: Investigating the impact of feature selection. In Advances in Experimental Medicine and Biology (AEMB) (Vol. 1424, pp. 223–230). Springer.

Burek, P., Scherf, N., & Herre, H. (2020). On the ontological foundations of cellular development. In Proceedings of the Joint Ontology Workshops (JOWO) 2020. doi:10.1101/2020.05.30.124875

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

De Back , W., Seurig, S., Wagner, S., Marre, B., Roeder, I., & Scherf, N. (2019). 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). Retrieved from http://hdl.handle.net/21.11116/0000-0004-C779-4

Kloenne, M., Niehaus, S., Lampe, L., Merola, A., Reinelt, J., & Scherf, N. (2019). Convolutional neural network stacking for medical image segmentation in CT scans. In 2019 Kidney Tumor Segmentation Challenge. Minneapolis, MN: University of Minnesota Libraries Publishing. doi:10.24926/548719.090

Thierbach, K., Bazin, P.-L., de Back, W., Gavriilidis, F., Kirilina, E., Jäger, C., … Scherf, N. (2018). Combining deep learning and active contours opens the way to robust, automated analysis of brain cytoarchitectonics. In Machine Learning in Medical Imaging 2018 (pp. 179–187). Cham: Springer.

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

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

Burek, P., Scherf, N., & Herre, H. (2014). OWL patterns for modeling the change over time exemplified by the cell tracking ontology. In Ontologies and Data in Life Sciences (ODLS 2014). Retrieved from http://hdl.handle.net/21.11116/0000-0007-CFC1-6

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

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

Burek, P., Herre, H., Roeder, I., Glauche, I., Scherf, N., & Löffler, M. (2010). Towards a cellular genealogy ontology. In Proceedings of the OBML 2010 Workshop. Retrieved from http://hdl.handle.net/21.11116/0000-0007-CF40-8