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Journal Article (6)

2020
Journal Article
Kloenne, M., Niehaus, S., Lampe, L., Merola, A., Reinelt, J., Roeder, I., & Scherf, N. (2020). Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes. Scientific Reports, 10. doi:10.1038/s41598-020-67544-y
2019
Journal Article
Shah, G., Thierbach, K., Schmid, B., Waschke, J., Reade, A., Hlawitschka, M., … Huisken, J. (2019). Multi-scale imaging and analysis identify pan-embryo cell dynamics of germlayer formation in zebrafish. Nature Communications, 10. doi:10.1038/s41467-019-13625-0
Journal Article
Burek, P., Scherf, N., & Herre, H. (2019). Ontology patterns for the representation of quality changes of cells in time. Journal of Biomedical Semantics, 10. doi:10.1186/s13326-019-0206-4
Journal Article
Burek, P., Scherf, N., & Herre, H. (2019). A pattern-based approach to a cell tracking ontology. Procedia Computer Science, 159, 784–793.
2018
Journal Article
Morawski, M., Kirilina, E., Scherf, N., Jäger, C., Reimann, K., Trampel, R., … Weiskopf, N. (2018). Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology. NeuroImage, 182, 417–428.
2017
Journal Article
Weber, M., Scherf, N., Meyer, A. M., Panáková, D., Kohl, P., & Huisken, J. (2017). Cell-accurate optical mapping across the entire developing heart. ELife, 6. doi:10.7554/eLife.28307.001

Conference Paper (3)

2019
Conference Paper
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
Conference Paper
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
2018
Conference Paper
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.

Meeting Abstract (1)

2018
Meeting Abstract
Brammerloh, M., Weigelt, I., Arendt, T., Gavriilidis, F., Scherf, N., Jankuhn, S., … Kirilina, E. (2018). 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. Paris Expo Porte de Versailles. Retrieved from http://hdl.handle.net/21.11116/0000-0004-C222-A

Poster (2)

2019
Poster
Podranski, K., Zhang, R., Thierbach, K., Thieleking, R., Witte, A. V., Villringer, A., … Scherf, N. Detecting fat artifacts in diffusion MRI with deep learning. Poster presented at the 9th IMPRS NeuroCom Summer School, Leipzig, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-0004-C6C1-2
2018
Poster
Podranski, K., Scherf, N., & Weiskopf, N. Improving high-resolution qunatitative MRI maps for in-vivo histology MRI of the human brain. Poster presented at the Medical Imaging Summer School 2018 - Medical Imaging Meets Deep Learning, Favignana, Italy. Retrieved from http://hdl.handle.net/21.11116/0000-0004-C6C8-B

Working Paper (2)

2018
Working Paper
Thierbach, K., Bazin, P.-L., De Back , W., Gavriilidis, F., Kirilina, E., Jäger, C., … Scherf, N. (2018, April 9). Combining deep learning and active contours opens the way to robust, automated analysis of brain cytoarchitectonics. BioRxiv. doi:10.1101/297689
2017
Working Paper
Shah, G., Thierbach, K., Schmid, B., Reade, A., Roeder, I., Scherf, N., & Huisken, J. (2017, August 9). Pan-embryo cell dynamics of germlayer formation in zebrafish. BioRxiv. doi:10.1101/173583

Manuscript (1)

2019
Manuscript
Kloenne, M., Niehaus, S., Lampe, L., Merola, A., Reinelt, J., & Scherf, N. (2019, September 27). A framework for CT image segmentation inspired by the clinical environment. arXiv. Retrieved from http://hdl.handle.net/21.11116/0000-0004-C770-D
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