Prof. Dr. Franziska Mathis-Ullrich

2024

• Fischer, N., Ho, P., Marzi, C., Schuler, P., & Mathis-Ullrich, F. (2024). A Laryngoscope with Shape Memory Actuation. Current Directions in Biomedical Engineering, 10(2), 58-61. https://doi.org/10.1515/cdbme-2024-1067
• Henrich, P., Gyenes, B., Scheikl, P., Neumann, G., & Mathis-Ullrich, F. (2024). Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud. In Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 (pp. 3117-3126). Waikoloa, HI, US: Institute of Electrical and Electronics Engineers Inc..
• Lemke, H.U., & Mathis-Ullrich, F. (2024). Design criteria for AI-based IT systems. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-024-03064-8
• Matasyoh, N.M., Schmidt, R., Zeineldin, R., Spetzger, U., & Mathis-Ullrich, F. (2024). Interactive Surgical Training in Neuroendoscopy: Real-Time Anatomical Feature Localization using Natural Language Expressions. IEEE Transactions on Biomedical Engineering, 1-9. https://doi.org/10.1109/TBME.2024.3405814
• Peter, R., Moreira, S., Tagliabue, E., Hillenbrand, M., Nunes, R.G., & Mathis-Ullrich, F. (2024). Stereo reconstruction from microscopic images for computer-assisted ophthalmic surgery. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-024-03177-0
• Scheikl, P., Schreiber, N., Haas, C., Freymuth, N., Neumann, G., Lioutikov, R., & Mathis-Ullrich, F. (2024). Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects. IEEE Robotics and Automation Letters, 1-8. https://doi.org/10.1109/LRA.2024.3382529
• Younis, R., Yamlahi, A., Bodenstedt, S., Scheikl, P., Kisilenko, A., Daum, M.,... Wagner, M. (2024). A surgical activity model of laparoscopic cholecystectomy for co-operation with collaborative robots. Surgical Endoscopy. https://doi.org/10.1007/s00464-024-10958-w
• Zeineldin, R., Karar, M.E., Burgert, O., & Mathis-Ullrich, F. (2024). NeuroIGN: Explainable Multimodal Image-Guided System for Precise Brain Tumor Surgery. Journal of Medical Systems, 48(1), 25-. https://doi.org/10.1007/s10916-024-02037-3
• Zeineldin, R., Karar, M.E., Elshaer, Z., Coburger, J., Wirtz, C.R., Burgert, O., & Mathis-Ullrich, F. (2024). Explainable hybrid vision transformers and convolutional network for multimodal glioma segmentation in brain MRI. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-54186-7

2023

• Fischer, N., Knapp, J., & Mathis-Ullrich, F. (2023). Shape-sensing by self-sensing of shape memory alloy instruments for minimal invasive surgery. At-Automatisierungstechnik, 71(7), 554-561. https://doi.org/10.1515/auto-2023-0058
• Fischer, N., Kriechbaum, J., Berwanger, D., & Mathis-Ullrich, F. (2023). Compliant Hall-Effect Sensor Array for Passive Magnetic Instrument Tracking. IEEE Sensors Letters, 1-4. https://doi.org/10.1109/LSENS.2023.3250971
• Fischer, N., Marzi, C., Meisenbacher, K., Kisilenko, A., Davitashvili, T., Wagner, M., & Mathis-Ullrich, F. (2023). A sensorized modular training platform to reduce vascular damage in endovascular surgery. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-023-02935-w
• Fischer, N., & Mathis-Ullrich, F. (2023). Compact flexible actuator based on a shape memory alloy for shaping surgical instruments. At-Automatisierungstechnik, 71(7), 547-553. https://doi.org/10.1515/auto-2023-0049
• Karstensen, L., Ritter, J., Hatzl, J., Ernst, F., Langejürgen, J., Uhl, C., & Mathis-Ullrich, F. (2023). Recurrent neural networks for generalization towards the vessel geometry in autonomous endovascular guidewire navigation in the aortic arch. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-023-02938-7
• Marzi, C., Buck, F., & Mathis-Ullrich, F. (2023). Continuum robot actuation by a single motor per antagonistic tendon pair: workspace and repeatability analysis. At-Automatisierungstechnik, 71(7), 528-536. https://doi.org/10.1515/auto-2023-0066
• Rauter, G., & Mathis-Ullrich, F. (2023). Special issue: Minimal-invasive robotics. At-Automatisierungstechnik, 71(7), 503-504. https://doi.org/10.1515/auto-2023-0098
• Scheikl, P.M., Tagliabue, E., Gyenes, B., Wagner, M., Dall'Alba, D., Fiorini, P., & Mathis-Ullrich, F. (2023). Sim-to-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery. IEEE Robotics and Automation Letters, 8(2), 560-567. https://doi.org/10.1109/LRA.2022.3227873
• Zeineldin, R.A., Junger, D., Mathis-Ullrich, F., & Burgert, O. (2023). Development of an AI-driven system for neurosurgery with a usability study: a step towards minimal invasive robotics. At-Automatisierungstechnik, 71(7), 537-546. https://doi.org/10.1515/auto-2023-0061

2022

• Alt, B., Kunz, C., Katic, D., Younis, R., Jaekel, R., Mueller-Stich, B.P.,... Mathis-Ullrich, F. (2022). LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes. In IEEE International Conference on Intelligent Robots and Systems (pp. 5265-5270). Kyoto, JPN: Institute of Electrical and Electronics Engineers Inc..
• García, G., Fischer, N., Marzi, C., & Mathis-Ullrich, F. (2022). Robotic Sensorized Gastroendoscopy with Wireless Single-Hand Control. Current Directions in Biomedical Engineering, 8(1), 66-69. https://doi.org/10.1515/cdbme-2022-0017
• Hopp, T., Springer, L., Gross, C., Grudzenski-Theis, S., Mathis-Ullrich, F., & Ruiter, N. (2022). Segmentation of the mouse skull for MRI guided transcranial focused ultrasound therapy planning. In Cristian A. Linte, Jeffrey H. Siewerdsen (Eds.), Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Virtual, Online: SPIE.
• Karstensen, L., Ritter, J., Hatzl, J., Paetz, T., Langejuergen, J., Uhl, C., & Mathis-Ullrich, F. (2022). Learning-based autonomous vascular guidewire navigation without human demonstration in the venous system of a porcine liver. International Journal of Computer Assisted Radiology and Surgery, 17(11), 2033-2040. https://doi.org/10.1007/s11548-022-02646-8
• Kunz, C., Maierhofer, P., Gyenes, B., Franke, N., Younis, R., Müller-Stich, B.P.,... Mathis-Ullrich, F. (2022). Augmented Reality-based Robot Control for Laparoscopic Surgery. Current Directions in Biomedical Engineering, 8(1), 54-57. https://doi.org/10.1515/cdbme-2022-0014
• Marzi, C., Alagi, H., Rau, O., Hampe, J., Korvink, J.G., Hein, B., & Mathis-Ullrich, F. (2022). Capacitive Proximity Sensor for Non-Contact Endoscope Localization. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 9614-9620). Philadelphia, PA, US: Institute of Electrical and Electronics Engineers Inc..
• Peikert, S., Kunz, C., Fischer, N., Hlavac, M., Pala, A., Schneider, M., & Mathis-Ullrich, F. (2022). Automated Linear and Non-Linear Path Planning for Neurosurgical Interventions. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 7731-7737). Philadelphia, PA, US: Institute of Electrical and Electronics Engineers Inc..
• Philipp, M., Alperovich, A., Gutt-Will, M., Mathis, A., Saur, S., Raabe, A., & Mathis-Ullrich, F. (2022). Dynamic CNNs using uncertainty to overcome domain generalization for surgical instrument localization. In Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022 (pp. 1727-1736). Waikoloa, HI, USA: Institute of Electrical and Electronics Engineers Inc..
• Philipp, M., Alperovich, A., Lisogorov, A., Gutt-Will, M., Mathis, A., Saur, S.,... Mathis-Ullrich, F. (2022). Annotation-efficient learning of surgical instrument activity in neurosurgery. Current Directions in Biomedical Engineering, 8(1), 30-33. https://doi.org/10.1515/cdbme-2022-0008
• Philipp, M., Bacher, N., Saur, S., Mathis-Ullrich, F., & Bruhn, A. (2022). From Chairs To Brains: Customizing Optical Flow For Surgical Activity Localization. In Proceedings - International Symposium on Biomedical Imaging. Kolkata, IND: IEEE Computer Society.
• Prinzen, T., Marzi, C., Haag, J., Mathis-Ullrich, F., Schipper, J., & Klenzner, T. (2022). Erkennung von Bildmerkmalen im Mikroskopbild für robotisch assistierte Mikrochirurgie: erste Ergebnisse und klinische Perspektive. In Laryngorhinootologie 2022. Georg Thieme Verlag KG.
• Ritter, J., Karstensen, L., Langejürgen, J., Hatzl, J., Mathis-Ullrich, F., & Uhl, C. (2022). Quality-dependent Deep Learning for Safe Autonomous Guidewire Navigation. Current Directions in Biomedical Engineering, 8(1), 21-24. https://doi.org/10.1515/cdbme-2022-0006
• Zeineldin, R.A., Karar, M.E., Elshaer, Z., Coburger, J., Wirtz, C.R., Burgert, O., & Mathis-Ullrich, F. (2022). Explainability of deep neural networks for MRI analysis of brain tumors. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-022-02619-x
• Zeineldin, R.A., Karar, M.E., Mathis-Ullrich, F., & Burgert, O. (2022). Ensemble CNN Networks for GBM Tumors Segmentation Using Multi-parametric MRI. In Alessandro Crimi, Spyridon Bakas (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 473-483). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
• Zeineldin, R.A., Pollok, A., Mangliers, T., Karar, M.E., Mathis-Ullrich, F., & Burgert, O. (2022). Deep automatic segmentation of brain tumours in interventional ultrasound data. Current Directions in Biomedical Engineering, 8(1), 133-137. https://doi.org/10.1515/cdbme-2022-0034

2021

• Fischer, N., Scheikl, P.M., Marzi, C., Galindo-Blanco, B., Kisilenko, A., Müller-Stich, B.P.,... Mathis-Ullrich, F. (2021). Flexible Facile Tactile Sensor for Smart Vessel Phantoms. Current Directions in Biomedical Engineering, 7(1). https://doi.org/10.1515/cdbme-2021-1019
• Gerst, M., Kunz, C., Henrich, P., & Mathis-Ullrich, F. (2021). Multimodal risk-map for navigation planning in neurosurgical interventions. In Mechanisms and Machine Science (pp. 183-191). Springer Science and Business Media B.V..
• Karstensen, L., Pätz, T., Mathis-Ullrich, F., & Stallkamp, J. (2021). Facile Testbed for Robotic X-ray based Endovascular Interventions. Current Directions in Biomedical Engineering, 7(1). https://doi.org/10.1515/cdbme-2021-1026
• Kunz, C., Gerst, M., Henrich, P., Schneider, M., Hlavac, M., Pala, A., & Mathis-Ullrich, F. (2021). Multimodal risk-based path planning for neurosurgical interventions. Journal of Medical Devices-Transactions of the Asme, 15(1). https://doi.org/10.1115/1.4049550
• Kunz, C., Hlavac, M., Schneider, M., Pal'a, A., Henrich, P., Jickeli, B.,... Mathis-Ullrich, F. (2021). Autonomous Planning and Intraoperative Augmented Reality Navigation for Neurosurgery. IEEE Transactions on Medical Robotics and Bionics, 3(3), 738-749. https://doi.org/10.1109/TMRB.2021.3091184
• Marzi, C., Fischer, N., & Mathis-Ullrich, F. (2021). Biocompatible Soft Material Actuator for Compliant Medical Robots. Current Directions in Biomedical Engineering, 7(1). https://doi.org/10.1515/cdbme-2021-1013
• Marzi, C., Prinzen, T., Haag, J., Klenzner, T., & Mathis-Ullrich, F. (2021). Continuous Feature-Based Tracking of the Inner Ear for Robot-Assisted Microsurgery. Frontiers in Surgery, 8. https://doi.org/10.3389/fsurg.2021.742160
• Mathis-Ullrich, F., & Scheikl, P.M. (2021). Robots in the operating room—(co)operation during surgery Robotik im Operationssaal – (Ko‑)Operieren mit Kollege Roboter. Gastroenterologe, 16(1), 25-34. https://doi.org/10.1007/s11377-020-00496-x
• Philipp, M., Bacher, N., Nienhaus, J., Hauptmann, L., Lang, L., Alperovich, A.,... Mathis-Ullrich, F. (2021). Synthetic data generation for optical flow evaluation in the neurosurgical domain. Current Directions in Biomedical Engineering, 7(1), 67-71. https://doi.org/10.1515/cdbme-2021-1015
• Scheikl, P.M., Gyenes, B., Davitashvili, T., Younis, R., Schulze, A., Mueller-Stich, B.P.,... Mathis-Ullrich, F. (2021). Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning. In IEEE International Conference on Intelligent Robots and Systems (pp. 1859-1864). Prague, CZE: Institute of Electrical and Electronics Engineers Inc..
• Schneider, M., Kunz, C., Pal'a, A., Wirtz, C.R., Mathis-Ullrich, F., & Hlavac, M. (2021). Augmented reality–assisted ventriculostomy. Neurosurgical Focus, 50(1), 1-7. https://doi.org/10.3171/2020.10.FOCUS20779
• Wagner, M., Bihlmaier, A., Kenngott, H.G., Mietkowski, P., Scheikl, P.M., Bodenstedt, S.,... Mueller-Stich, B.P. (2021). A learning robot for cognitive camera control in minimally invasive surgery. Surgical Endoscopy, 35(9), 5365-5374. https://doi.org/10.1007/s00464-021-08509-8
• Zeineldin, R.A., Karar, M.E., Elshaer, Z., Schmidhammer, M., Coburger, J., Wirtz, C.R.,... Mathis-Ullrich, F. (2021). IRegNet: Non-rigid registration of MRI to interventional US for brain-shift compensation using convolutional neural networks. IEEE Access, 9, 147579-147590. https://doi.org/10.1109/ACCESS.2021.3120306
• Zeineldin, R.A., Karar, M.E., Mathis-Ullrich, F., & Burgert, O. (2021). A Hybrid Deep Registration of MR Scans to Interventional Ultrasound for Neurosurgical Guidance. In Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 586-595). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
• Zeineldin, R.A., Weimann, P., Karar, M.E., Mathis-Ullrich, F., & Burgert, O. (2021). Slicer-DeepSeg: Open-Source Deep Learning Toolkit for Brain Tumour Segmentation. Current Directions in Biomedical Engineering, 7(1). https://doi.org/10.1515/cdbme-2021-1007

2020

• Karstensen, L., Behr, T., Pusch, T.P., Mathis-Ullrich, F., & Stallkamp, J. (2020). Autonomous guidewire navigation in a two dimensional vascular phantom. Current Directions in Biomedical Engineering, 6(1). https://doi.org/10.1515/cdbme-2020-0007
• Kunz, C., Maurer, P., Kees, F., Henrich, P., Marzi, C., Hlaváč, M.,... Mathis-Ullrich, F. (2020). Infrared marker tracking with the HoloLens for neurosurgical interventions. Current Directions in Biomedical Engineering, 6(1). https://doi.org/10.1515/cdbme-2020-0027
• Scheikl, P.M., Laschewski, S., Kisilenko, A., Davitashvili, T., Müller, B., Capek, M.,... Mathis-Ullrich, F. (2020). Deep learning for semantic segmentation of organs and tissues in laparoscopic surgery. Current Directions in Biomedical Engineering, 6(1). https://doi.org/10.1515/cdbme-2020-0016