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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 feedback,
Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology, International Society for Optics and Photonics
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Max-Heinrich Laves, Sontje Ihler, Jacob F Fast, Lüder A Kahrs, Tobias Ortmaier
(2020):
Well-calibrated regression uncertainty in medical imaging with deep learning,
Medical Imaging with Deep Learning (MIDL), PMLR
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Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier
(2020):
Calibration of Model Uncertainty for Dropout Variational Inference
arXiv:
arXiv:2006.11584
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Sontje Ihler, Felix Kuhnke, Max-Heinrich Laves, Tobias Ortmaier
(2020):
Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking,
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Springer
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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
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Ihler, S.; Laves, MH.; Ortmaier, T.
(2019):
Towards Manifold Learning of Image-Based Motion Models for Oscillating Vocal Folds,
Medical Imaging with Deep Learning
arXiv:
https://openreview.net/forum?id=S1xTGVhE5N
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Ihler, S.; Schulz, JP., Laves MH.; Kahrs, LA; Ortmaier, T.
(2019):
Towards Patient-Specific Neural Networks for Image-Based Motion Estimation,
Computer-Assisted Radiology and Surgery (CARS)
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Ihler, S.; Seifert, J.; Laves, MH., Kahrs, LA.; Ptok, M.; Ortmaier, T.
(2019):
Vergleichsstudie von objektbasiertem Hochgeschwindigkeits-Tracking der Glottis,
Computer- und Roboter-Assistierte Chirurgie (CURAC)
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Laves, MH.; Ihler, S.; Kahrs, LA.; Ortmaier, T.
(2019):
Semantic denoising autoencoders for retinal optical coherence tomography,
European Conferences on Biomedical Optics
DOI:
10.1117/12.2526936
arXiv:
1903.09809
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Laves, MH.; Ihler, S.; Kahrs, LA.; Ortmaier, T.
(2019):
Quantifying the uncertainty of deep learning-based computer-aided diagnosis for patient safety,
Current Directions in Biomedical Engineering
DOI:
10.1515/cdbme-2019-0057
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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 tomography,
SPIE Medical Imaging
DOI:
10.1117/12.2512952
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Laves, MH.; Ihler, S.; Kortmann, KP.; Ortmaier, T.
(2019):
Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference,
4th workshop on Bayesian Deep Learning (NeurIPS 2019), Vancouver, Canada.
arXiv:
1909.13550
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Laves, MH.; Ihler, S.; Ortmaier, T.
(2019):
Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don’t know" for Ambiguous Cases,
Medical Imaging with Deep Learning
arXiv:
https://openreview.net/pdf?id=rJevPsX854
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Laves, MH.; Ihler, S.; Ortmaier, T.
(2019):
Retinal OCT disease classification with variational autoencoder regularization,
Computer Assisted Radiology and Surgery
DOI:
10.1007/s11548-019-01969-3
arXiv:
1904.00790
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Laves, MH.; Ihler, S.; Ortmaier, T.
(2019):
Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior,
Medical Imaging with Deep Learning
arXiv:
https://openreview.net/forum?id=S1ehZFQ15E
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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 Servoing,
Proceedings of The Hamlyn Symposium on Medical Robotics 2018, London, England
