Publications of Nico Scherf

Scherf, N., & Mueller, K. Data Science Clinic. Courseware_lecture presented at the Seminar, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2D55-4

Mueller, K., & Scherf, N. Methods Club. Courseware_lecture presented at the Seminar, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2D59-0

Hinnerichs, T. (2022). Finding gene expression patterns and their link to connectivities in mouse brains by exploiting interaction networks (Diploma Thesis). TU Dresden, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2F42-7

Kiakou, D. (2022). Geometric deep learning in neuroimaging (Master's Thesis). Hellenic Open University, Patras, Greece. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2F30-B

Meussling, M. (2022). Segmentierung und Analyse von Astrozyten und Nervenfasern des menschlichen Gehirns (Master's Thesis). Hochschule für Technik, Wirtschaft und Kultur, Leipzig, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2F34-7

Mueller, G. (2022). Quantifying differences in the microanatomy of the auditory cortex between both hemispheres of the mammalian brain (Master's Thesis). TU Dresden, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2F39-2

Horlava, N. (2021). Robust, structure-aware classification of neurodegeneration (Master's Thesis). TU Dresden, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2F37-4

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

Haase, R., Tischer, C., & Scherf, N. (2024, April 21). Benchmarking large language models for bio-image analysis code generation. BioRxiv. doi:10.1101/2024.04.19.590278

Williams, E., Kienast, M., Medawar, E., Reinelt, J., Merola, A., Klopfenstein, S. A. I., … Niehaus, S. (2022, November 13). FHIR-DHP: A standardized clinical data harmonisation pipeline for scalable AI application deployment. MedRxiv. doi:10.1101/2022.11.07.22281564

Waschke, J., Hlawitschka, M., Anlas, K., Trivedi, V., Roeder, I., Huisken, J., & Scherf, N. (2021, January 8). linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser. BioRxiv. doi:10.1101/2020.04.17.043323

Hoffmann, H., Baldow, C., Zerjatke, T., Gottschalk, A., Wagner, S., Karg, E., … Scherf, N. (2020, December 7). How to predict relapse in leukaemia using time series data: A comparative in silico study. MedRxiv. doi:10.1101/2020.12.04.20243907

Horlava, N., Mironenko, A., Niehaus, S., Wagner, S., Roeder, I., & Scherf, N. (2020, November 11). A comparative study of semi- and self-supervised semantic segmentation of biomedical microscopy data. ArXiv. doi:10.48550/arXiv.2011.08076

Wagner, S., Thierbach, K., Zerjatke, T., Glauche, I., Roeder, I., & Scherf, N. (2020, February 14). TraCurate: Efficiently curating cell tracks. BioRxiv. doi:10.1101/2020.02.14.936740

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

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

Computer statt Mensch: Kann KI unsere Probleme lösen? (2022, July 14). Alles Wissen. Hessischer Rundfunk (hr). Retrieved from http://hdl.handle.net/21.11116/0000-000B-1AD7-6