Dr. Lukas Lichtensteiger
Dr. Lukas Lichtensteiger
ZHAW
School of Engineering
Medical Complex Systems
Technikumstrasse 9
8400 Winterthur
Projects
- Mira: Hybrid Logic-AI for Claims / Deputy project leader / ongoing
- Blockchain-Enabled Financing of Supply Chains / Project leader / ongoing
- Blockchain-Enabled Sustainable Financing / Project leader / completed
- Blockchain-Based Verified Career Records for Enhanced Professional Credibility / Team member / completed
- Agroforestry Carbon Token System / Team member / completed
- SpaceVote / Project leader / completed
- Neurological ICU Data / Team member / completed
- AI powered CBCT for improved Combination Cancer Therapy / Deputy project leader / completed
- Decentralized financing of Fairtrade producers using a blockchain-based solution / Team member / completed
- DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Team member / completed
- Data Driven Medical muscle Training / Deputy project leader / completed
- Libra: A One-Tool Solution for MLD4 Compliance / Team member / completed
- Complexity 4.0 / Team member / completed
- New sensor and actuator technologies for robots / Project leader / completed
Publications
Articles in scientific journal, peer-reviewed
- Barco, D. et al. (2026) 'MInDI-3D : iterative deep learning in 3D for sparse-view cone beam computed tomography', IEEE Access, 14, pp. 6438–6449. doi: 10.1109/access.2026.3652627.
- Amirian, M. et al. (2023) 'Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks', Medical Physics, 50(10), pp. 6228–6242. doi: 10.1002/mp.16405.
- Füchslin, R. M. et al. (2014) 'Morphological control : a design principle for applications in space science', Journal of the British Interplanetary Society, 67, pp. 305–313. Available at: http://adsabs.harvard.edu/abs/2014JBIS...67..305F.
Book chapters, peer-reviewed
Hollenstein, L. et al. (2019) 'Unsupervised learning and simulation for complexity management in business operations', in Braschler, M., Stadelmann, T., and Stockinger, K. (eds) Applied data science : lessons learned for the data-driven business. Cham: Springer, pp. 313–331. doi: 10.1007/978-3-030-11821-1_17.
Written conference contributions, peer-reviewed
Herzig, I. et al. (2022) 'Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT', in Medical Physics. American Association of Physicists in Medicine, pp. e325–e326. doi: 10.1002/mp.15769.
Other publications
- Barco, D. et al. (2025) MInDI-3D : iterative deep learning in 3D for sparse-view cone beam computed tomography. arXiv. doi: 10.48550/arXiv.2508.09616.
- Lichtensteiger, L. et al. (2023) 'Space vote : make your presence count', in Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. doi: 10.21256/zhaw-27412.
- Flumini, D. and Lichtensteiger, L. (2023) 'Decentralized financing of Fairtrade producers using a blockchain-based solution', in Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. doi: 10.21256/zhaw-27494.