Publikationen

Bende P, Vovk O, Caraveo O, Pechmann L and Leucker M, A Case Study on
Data Protection for a Cloud- and AI-based Homecare Medical Device. HEDA 2022 Konferenz:
https://cs.ttu.ee/events/heda-2022/, 2022.,
https://ceur-ws.org/Vol-3264/HEDA22_paper_3.pdf  

Bigalke A, und Hansen L, and Heinrich M P, End-to-end learning of body weight prediction from point clouds with basis point sets. Bildverarbeitung für die Medizin 2021. Springer, 2021. https://doi.org/10.1007/978-3-658-33198-6_59  

Bigalke A, und Hansen L, Diesel J, and Heinrich M P, Seeing under the cover with a 3D U-Net: point cloud-based weight estimation of covered patients. International Journal of Computer Assisted Radiology and Surgery 16.12: 2079-2087, Springer, 2021, https://doi.org/10.1007/s11548-021-02476-0  

Bigalke A, und Hansen L, Diesel J, and Heinrich M P, Domain adaptive 3d human pose estimation through anatomical constraints. MIDL 2022, https://research.uni-luebeck.de/en/publications/domain-adaptive-3d-human-pose-estimation-through-anatomical-const  

Bockelmann N, Kesslau D, Bonsanto M, Buschschlüter S and Ernst F, Towards machine learning-based tissue differentiation using an ultrasonic aspirator, in: CARS 2021: computer assisted radiology and surgery proceedings of the 35th international Congress and exhibition Munich, Germany, June 21–25, 2021, pages 107-108, 2021, https://doi.org/10.1007/s11548-021-02375-4


Bockelmann N, Schetelig D, Bonsanto M, Buschschlüter S and Ernst F, Intelligent ultrasonic-aspirator for CNS/ tumor tissue differentiation – a feasibility study using machine learning, in: 73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie, Köln, 2022, https://doi.org/10.3205/22dgnc188

Bockelmann N, Schetelig D, Kesslau D, Buschschlüter S, Ernst F and Bonsanto M, Toward intraoperative tissue classification: exploiting signal feedback from an ultrasonic aspirator for brain tissue differentiation (2022), in: International Journal of Computer Assisted Radiology and Surgery, https://doi.org/10.1007/s11548-022-02713-0

Diethei D, Colley A, Dannenberg L, Malik M F J and Schöning J, "The Usability and Trustworthiness of Medical Eye Images," 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), Victoria, BC, Canada, 2021, pp. 396-405, https://doi.org/10.1109/ICHI52183.2021.00065

Diethei D, Colley A, Kalving M, Salmela T, Häkkilä J and Schöning J. 2020. Medical Selfies: Emotional Impacts and Practical Challenges. 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services. Association for Computing Machinery, New York, NY, USA, Article 8, 1–12. https://doi.org/10.1145/3379503.3403555

Duczek N, Kerzel M, Allgeuer P and Wermter S (2022), "Self-organized learning from synthetic and real-world data for a humanoid exercise robot.",Front. Robot. AI 9:669719, https://doi.org/10.3389/frobt.2022.669719

Fischer S, Leucker M, Lüth C et al. KI-SIGS: Artificial Intelligence for the Northern German Health Ecosystem. Digitale Welt 4, 49–54 (2020). https://doi.org/10.1007/s42354-019-0232-5  

Gerdes H, Mairhöfer D, Laufer M, Leal dos Reis F, Preuss J, Käster T, Barth E, Martinetz T,
Barkhausen J, Bischof A, Sieren MM: Automatisierte Qualitätsbewertung von Röntgenaufnahmen des
oberen Sprunggelenks mittels künstlicher Intelligenz, Deutscher Röntgenkongress, Wiesbaden,
2022,
https://doi.org/10.1055/s-0042-1749773

Hennigs C, Brehmer K and Rostalski P: The effect of body mass index on pressure controlled ventilator settings. AUTOMED 2021, 2021, https://doi.org/10.5281/zenodo.4925843


Hennigs C, Brehmer K, Hardel T and Rostalski P: Model-based automation of pressure-controlled ventilation in relation to body mass index (BMI) and chronic obstructive pulmonary disease (COPD). at – Automatisierungstechnik, De Gruyter, 2022, https://doi.org/10.1515/auto-2022-0011  

Hennigs C, Becher T and Rostalski P: Mathematical lung model for local gas exchange based in EIT-measurements. BMT 2022, https://doi.org/10.1515/cdbme-2022-1096

Häger S, Lange A, Heldmann S, Modersitzki J, Petersik A, Schröder M, Gottschling H, Lieth T, Zähringer E and Moltz J H: Robust Intensity-Based Initialization for 2D-3D Pelvis Registration (RobIn), Bildverarbeitung für die Medizin 2022., https://research.uni-luebeck.de/en/publications/robust-intensity-based-initialization-for-2d-3d-pelvis-registrati  

Himstedt M, Häger S, Heldmann S, Petersik A, Zähringer E, Gottschling H, Schröder M, Lieth T, Modersitzki J: DRR to C-arm X-Ray Image Translation with Application to Trauma Surgery, Computer Assisted Radiology and Surgery 2021. https://content.e-bookshelf.de/media/reading/L-17879544-4404d73f53.pdf

Kepp T, Andresen J, Sudkamp H, Burchard C, Roider J, Hüttmann G, Ehrhardt J and Handels
H, Epistemic and Aleatoric Uncertainty Estimation for PED Segmentation in Home OCT ImagesIn:
Maier-Hein K., Deserno T., Handels H., Maier A., Palm C., Tolxdorff T., Bildverarbeitung für die
Medizin 2022, Heidelberg, Informatik Aktuell, Springer Vieweg, Wiesbaden, 32-37, 2022,
https://doi.org/10.1007/978-3-658-36932-3_7

Leal dos Reis F, Laufer M, Mairhöfer D, Gerdes H, Preuss J, Käster T, Barth E, Martinetz T,
Barkhausen J, Bischof A and Sieren MM: Vorhersage der Röntgenbildqualität des oberen Sprunggelenks mittels Tiefenbildtechnik und künstlicher Intelligenz – eine Kadaverstudie, Deutscher Röntgenkongress, Wiesbaden, 2022,
https://doi.org/10.1055/s-0042-1749783 

Mairhöfer D, Laufer M, Simon P, Sieren M, Bischof A, Käster T, Barth E, Barkhausen J and Martinetz T, An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs in Proceedings of Machine Learning Research 143, pages 484-496, 2021, https://proceedings.mlr.press/v143/mairhofer21a.html

Mandel C, Stich K, Autexier S, Lüth C, Ziehn A, Hochbaum K, Dembinski R, Int-Veen C: "Using Gated Recurrent Unit Networks for the Prediction of Hemodynamic and Pulmonary Decompensation," 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Glasgow, Scotland, United Kingdom, 2022, pp. 4584-4589, https://doi.org/10.1109/EMBC48229.2022.9871500

Petersen E, Potdevin Y, Mohammadi E, Zidowitz S, Breyer S, Nowotka D, Henn S, Pechmann L, Leucker M, Rostalski Z and Herzog C, Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions, 2021, https://arxiv.org/abs/2107.09546

Rahrakhshan N, Kerzel M, Allgeuer P, Duczek Z and Stefan Wermter, "Learning to Autonomously Reach Objects with NICO and Grow-When-Required Networks", in 2022 IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2022. https://deepai.org/publication/learning-to-autonomously-reach-objects-with-nico-and-grow-when-required-networks  

Santarossa M, Tatli A, von der Burchard C, Schmarje L, Zelenka C, Reinhold S, Roider J and Koch R: MedRegNet – Unsupervised Multimodal Retinal-Image Registration with GANs and Ranking Loss, Proc. SPIE 12032, Medical Imaging 2022: Image Processing, 1203218; https://doi.org/10.1117/12.2607653

Santarossa M, Tatli A, von der Burchard C, Andresen J, Roider J, Handels H and Koch R, "Chronological Registration of OCT and Autofluorescence Findings in CSCR: Two Distinct Patterns in Disease Course" Diagnostics 12, no. 8: 1780, 2022, https://doi.org/10.3390/diagnostics12081780  

Uzunova, H, Basso L, Ehrhardt J and Handels H (2022). Abstract: Synthesis of Annotated Pathological Retinal OCT Data with Pathology-Induced Deformations. In: Maier-Hein, K., Deserno, T.M., Handels, H., Maier, A., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2022. Informatik aktuell. Springer Vieweg, Wiesbaden, online ISBN: 978-3-658-36932-3,  https://doi.org/10.1007/978-3-658-36932-3_42
 

Auszeichnungen

AP310 - IMI: Auszeichnung von Leonie Basso mit dem Prof. Dr. Werner Petersen-Preis der Technik 2021 für ihre Masterarbeit unter Betreuung von Prof. Dr. Heinz Handels mit dem Titel: "Generierung synthetischer annotierter Retina-OCT-Bilder mit Generative Adversarial Networks" durch die Prof. Dr. Werner Petersen-Stiftung, Kiel, 13.12.21. Die Masterarbeit wurde im Kontext des KI-SIGS-Projektes iAuge durchgeführt und von Prof. Dr. Heinz Handels betreut.

AP360 - BVM-Preis, Beste Wissenschaftliche Arbeit, 3. Platz - Alexander Bigalke für das Paper "End-to-end learning of body weight prediction from point clouds with basis point sets" 2021

KI-SIGS Projekt als ein Gewinner des Bundeswettbewerbs "KI als Treiber für volkswirtschaftlich relevante Ökosysteme" https://www.bmwk.de/Redaktion/DE/Publikationen/Technologie/ki-innovationswettbewerb.html