• James W Napier, Sontje Ihler, Max-Heinrich Laves, Miroslav Zabic, Alexander Heisterkamp, Walter Neu (2020): Design of a novel MEMS based laser scanning laryngoscope to combine high precision laser cuts with simultaneous MHz OCT and stereo camera feedbackImaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology, International Society for Optics and Photonics
  • Max-Heinrich Laves, Sontje Ihler, Jacob F Fast, Lüder A Kahrs, Tobias Ortmaier (2020): Well-calibrated regression uncertainty in medical imaging with deep learningMedical Imaging with Deep Learning (MIDL), PMLR
  • Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier (2020): Calibration of Model Uncertainty for Dropout Variational Inference
    arXiv: arXiv:2006.11584
  • Sontje Ihler, Felix Kuhnke, Max-Heinrich Laves, Tobias Ortmaier (2020): Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue TrackingInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Springer
  • Sontje Ihler, Max-Heinrich Laves, Tobias Ortmaier (2020): Patient-specific domain adaptation for fast optical flow based on teacher-student knowledge transfer
    arXiv: arXiv:2007.04928
  • Ihler, S.; Laves, MH.; Ortmaier, T. (2019): Towards Manifold Learning of Image-Based Motion Models for Oscillating Vocal FoldsMedical Imaging with Deep Learning
  • Ihler, S.; Schulz, JP., Laves MH.; Kahrs, LA; Ortmaier, T. (2019): Towards Patient-Specific Neural Networks for Image-Based Motion EstimationComputer-Assisted Radiology and Surgery (CARS)
  • Ihler, S.; Seifert, J.; Laves, MH., Kahrs, LA.; Ptok, M.; Ortmaier, T. (2019): Vergleichsstudie von objektbasiertem Hochgeschwindigkeits-Tracking der GlottisComputer- und Roboter-Assistierte Chirurgie (CURAC)
  • Laves, MH.; Ihler, S.; Kahrs, LA.; Ortmaier, T. (2019): Semantic denoising autoencoders for retinal optical coherence tomographyEuropean Conferences on Biomedical Optics
    DOI: 10.1117/12.2526936
    arXiv: 1903.09809
  • Laves, MH.; Ihler, S.; Kahrs, LA.; Ortmaier, T. (2019): Quantifying the uncertainty of deep learning-based computer-aided diagnosis for patient safetyCurrent Directions in Biomedical Engineering
    DOI: 10.1515/cdbme-2019-0057
  • Laves, MH.; Ihler, S.; Kahrs, LA.; Ortmaier, T. (2019): Deep-learning-based 2.5 D flow field estimation for maximum intensity projections of 4D optical coherence tomographySPIE Medical Imaging
    DOI: 10.1117/12.2512952
  • Laves, MH.; Ihler, S.; Kortmann, KP.; Ortmaier, T. (2019): Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference4th workshop on Bayesian Deep Learning (NeurIPS 2019), Vancouver, Canada.
    arXiv: 1909.13550
  • Laves, MH.; Ihler, S.; Ortmaier, T. (2019): Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don’t know" for Ambiguous CasesMedical Imaging with Deep Learning
  • Laves, MH.; Ihler, S.; Ortmaier, T. (2019): Retinal OCT disease classification with variational autoencoder regularizationComputer Assisted Radiology and Surgery
    DOI: 10.1007/s11548-019-01969-3
    arXiv: 1904.00790
  • Laves, MH.; Ihler, S.; Ortmaier, T. (2019): Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization PriorMedical Imaging with Deep Learning
  • Modes, V.; Ihler, S.; Ortmaier, T.; Nabavi, A.; Kahrs, L. A.; Burgner-Kahrs, J. (2018): Towards Concentric Tube Robots for Microsurgery: First Results in Eye-to-hand Visual ServoingProceedings of The Hamlyn Symposium on Medical Robotics 2018, London, England