Dr. Lukas Lichtensteiger

Projects

• Agroforestry Carbon Token System / Team member / laufend
• AC3T – AI powered CBCT for improved Combination Cancer Therapy / Deputy project leader / laufend
• SpaceVote / Project leader / abgeschlossen
• Neurological ICU Data / Team member / abgeschlossen
• Decentralized financing of Fairtrade producers using a blockchain-based solution / Team member / abgeschlossen
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Team member / abgeschlossen
• Data Driven Medical muscle Training / Deputy project leader / abgeschlossen
• Libra: A One-Tool Solution for MLD4 Compliance / Team member / abgeschlossen
• Complexity 4.0 / Team member / abgeschlossen
• New sensor and actuator technologies for robots / Project leader / abgeschlossen

Publications

• Amirian, Mohammadreza; Montoya-Zegarra, Javier A.; Herzig, Ivo; Eggenberger Hotz, Peter; Lichtensteiger, Lukas; Morf, Marco; Züst, Alexander; Paysan, Pascal; Peterlik, Igor; Scheib, Stefan; Füchslin, Rudolf Marcel; Stadelmann, Thilo; Schilling, Frank-Peter,

  2023.

  Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks.

  Medical Physics.

  50(10), pp. 6228-6242.

  Available from: https://doi.org/10.1002/mp.16405

• Füchslin, Rudolf Marcel; Dumont, Elisabeth; Flumini, Dandolo; Fuchs, Hans Ulrich; Hauser, Helmut; Jaeger, Christian; Scheidegger, Stephan; Schönenberger-Deuel, Johanna; Lichtensteiger, Lukas; Luchsinger, Rolf H.; Weyland, Mathias,

  2014.

  Morphological control : a design principle for applications in space science.

  Journal of the British Interplanetary Society.

  67, pp. 305-313.

  Available from: http://adsabs.harvard.edu/abs/2014JBIS...67..305F

• Hollenstein, Lukas; Lichtensteiger, Lukas; Stadelmann, Thilo; Amirian, Mohammadreza; Budde, Lukas; Meierhofer, Jürg; Füchslin, Rudolf Marcel; Friedli, Thomas,

  2019.

  Unsupervised learning and simulation for complexity management in business operations

  .

  In:

  Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt, eds.,

  Applied data science : lessons learned for the data-driven business.

  Cham:

  Springer.

  pp. 313-331.

  Available from: https://doi.org/10.1007/978-3-030-11821-1_17

• Herzig, Ivo; Paysan, Pascal; Scheib, Stefan; Züst, Alexander; Schilling, Frank-Peter; Montoya, Javier; Amirian, Mohammadreza; Stadelmann, Thilo; Eggenberger Hotz, Peter; Füchslin, Rudolf Marcel; Lichtensteiger, Lukas,

  2022.

  Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT [poster].

  In:

  AAPM Annual Meeting, Washington, DC, USA, 10-14 July 2022.

  American Association of Physicists in Medicine.

  pp. e325-e326.

  Available from: https://doi.org/10.1002/mp.15769

• Flumini, Dandolo; Lichtensteiger, Lukas,

  2023.

  Decentralized financing of Fairtrade producers using a blockchain-based solution [poster].

  In:

  Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.

  Winterthur:

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-27494

• Lichtensteiger, Lukas; Flumini, Dandolo; Gisler, Luis; Molnár, Viktoria; Schaefer, Markus,

  2023.

  Space vote : make your presence count [poster].

  In:

  Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.

  Winterthur:

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-27412

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