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2019


Laves, M. H., Bicker, J., Kahrs, L. A., & Ortmaier, T. (2019). A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation. International journal of computer assisted radiology and surgery, 14(3), 483-492.

doi.org/10.48550/arXiv.1807.06081

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doi.org/10.1007/s11548-018-01910-0

Laves, M. H., Ihler, S., Kahrs, L. A., & Ortmaier, T. (2019). Deep-learning-based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography. in B. Fei, & C. A. Linte (Hrsg.), Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling [109510R] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Band 10951). SPIE.

doi.org/10.1117/12.2512952

Laves, M-H., Ihler, S., & Ortmaier, T. (2019). Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior.

Laves, M-H., Latus, S., Bergmeier, J., Ortmaier, T., Kahrs, L. A., & Schlaefer, A. (2019). Endoscopic vs. volumetric OCT imaging of mastoid bone structure for pose estimation in minimally invasive cochlear implant surgery.

Laves, M. H., Ihler, S., Ortmaier, T., & Kahrs, L. A. (2019). Quantifying the uncertainty of deep learning-based computer-aided diagnosis for patient safety. Current Directions in Biomedical Engineering, 5(1), 223-226.

doi.org/10.1515/cdbme-2019-0057

Laves, M-H., Ihler, S., Kahrs, L. A., & Ortmaier, T. (2019). Retinal OCT disease classification with variational autoencoder regularization.

Laves, M. H., Ihler, S., Kahrs, L. A., & Ortmaier, T. (2019). Semantic denoising autoencoders for retinal optical coherence tomography. in European Conference on Biomedical Optics, ECBO_2019 (Optics InfoBase Conference Papers; Band Part F142-ECBO 2019). OSA - The Optical Society.

doi.org/10.1117/12.2526936

Laves, M-H., Ihler, S., & Ortmaier, T. (2019). Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases.

Laves, M-H., Ihler, S., Kortmann, K-P., & Ortmaier, T. (2019). Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference. Beitrag in 4th workshop on Bayesian Deep Learning, Vancouver, Kanada.

Mannel, A., Tappe, S., Knöchelmann, E., & Ortmaier, T. (2019). Investigation on an AC grid failure handling of industrial dc microgrids with an energy storage. in Proceedings - 2019 IEEE International Conference on Industrial Technology, ICIT 2019 (S. 1710-1716). [8755017] (Proceedings of the IEEE International Conference on Industrial Technology; Band 2019-February). Institute of Electrical and Electronics Engineers Inc..

doi.org/10.1109/ICIT.2019.8755017

Männel, A., Knöchelmann, E., Tappe, S., & Ortmaier, T. (2019). State of Charge Based Characteristic Diagram Control for Energy Storage Systems within Industrial DC Microgrids. in 2019 IEEE Third International Conference on DC Microgrids (ICDCM) [9232876] Institute of Electrical and Electronics Engineers Inc..

doi.org/10.15488/10382

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doi.org/10.1109/ICDCM45535.2019.9232876

Meisoll, F. J., Jungheim, M., Fast, J. F., Ortmaier, T., & Ptok, M. (2019). Hochauflösungsmanometrische Beurteilung des Muskeltonus im oberen Ösophagussphinkter bei Aktivierung des laryngealen Adduktionsreflexes. Beitrag in 36. Wissenschaftliche Jahrestagung der Deutschen Gesellschaft für Phoniatrie und Pädaudiologie, Göttingen, Niedersachsen, Deutschland.

doi.org/10.3205/19DGPP64

Modes, V., & Burgner-Kahrs, J. (2019). Calibration of Concentric Tube Continuum Robots: Automatic Alignment of Precurved Elastic Tubes. IEEE Robotics and Automation Letters, 5(1), 103-110. [8861354].

doi.org/10.1109/LRA.2019.2946060

Müller, S., Kahrs, L. A., Gaa, J., Tauscher, S., Kluge, M., John, S., Rau, T. S., Lenarz, T., Ortmaier, T., & Majdani, O. (2019). Workflow assessment as a preclinical development tool: Surgical process models of three techniques for minimally invasive cochlear implantation. International journal of computer assisted radiology and surgery, 14, 1389-1401.

doi.org/10.1007/s11548-019-02002-3

Öltjen, J. (2019). Ein adaptives Steuerungskonzept für schwingungsfähige Robotersysteme. TEWISS Verlag.

Osorio, J. D. M., Allmendinger, F., Fiore, M. D., Zimmermann, U. E., & Ortmaier, T. (2019). Physical Human-Robot Interaction under Joint and Cartesian Constraints. in 2019 19th International Conference on Advanced Robotics, ICAR 2019 (S. 185-191). [8981579] Institute of Electrical and Electronics Engineers Inc..

doi.org/10.1109/icar46387.2019.8981579

Popp, E., Tantau, M., Wielitzka, M., Ortmaier, T., & Giebert, D. (2019). Frequency domain identification and identifiability analysis of a nonlinear vehicle drivetrain model. in 2019 18th European Control Conference, ECC 2019 (S. 237-242). [8795688] Institute of Electrical and Electronics Engineers Inc..

doi.org/10.15488/10817

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doi.org/10.23919/ecc.2019.8795688

Schappler, M., Tappe, S., & Ortmaier, T. (2019). Exploiting Dynamics Parameter Linearity for Design Optimization in Combined Structural and Dimensional Robot Synthesis. in Mechanisms and Machine Science (S. 1949-1958). (Mechanisms and Machine Science; Band 73). Springer Netherlands.

doi.org/10.15488/10211

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doi.org/10.1007/978-3-030-20131-9_193

Schappler, M., Lilge, T., & Haddadin, S. (2019). Kinematics and Dynamics Model via Explicit Direct and Trigonometric Elimination of Kinematic Constraints. in T. Uhl (Hrsg.), Mechanisms and Machine Science (Band 73, S. 3157-3166). (Mechanisms and Machine Science; Band 73). Springer, Cham.

doi.org/10.15488/10212

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doi.org/10.1007/978-3-030-20131-9_311

Schappler, M., Tappe, S., & Ortmaier, T. (2019). Modeling Parallel Robot Kinematics for 3T2R and 3T3R Tasks Using Reciprocal Sets of Euler Angles. Robotics, 8(3), [68].

doi.org/10.3390/robotics8030068

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doi.org/10.15488/9291


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