A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation MH Laves, J Bicker, LA Kahrs, T Ortmaier International Journal of Computer Assisted Radiology and Surgery 14 (3), 483-492, 2019 | 101 | 2019 |
Well-calibrated regression uncertainty in medical imaging with deep learning MH Laves, S Ihler, JF Fast, LA Kahrs, T Ortmaier Medical imaging with deep learning, 393-412, 2020 | 79 | 2020 |
Well-calibrated model uncertainty with temperature scaling for dropout variational inference MH Laves, S Ihler, KP Kortmann, T Ortmaier 4th Bayesian Deep Learning Workshop (NeurIPS), 2019 | 55 | 2019 |
Uncertainty estimation in medical image denoising with bayesian deep image prior MH Laves, M Tölle, T Ortmaier Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2020 | 43 | 2020 |
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging MH Laves, S Ihler, JF Fast, LA Kahrs, T Ortmaier Journal of Machine Learning for Biomedical Imaging, 2021 | 32 | 2021 |
Calibration of model uncertainty for dropout variational inference MH Laves, S Ihler, KP Kortmann, T Ortmaier arXiv preprint arXiv:2006.11584, 2020 | 22 | 2020 |
A Mean-Field Variational Inference Approach to Deep Image Prior for Inverse Problems in Medical Imaging M Tölle*, MH Laves*, A Schlaefer Medical Imaging with Deep Learning, 2021 | 17 | 2021 |
Quantifying the uncertainty of deep learning-based computer-aided diagnosis for patient safety MH Laves, S Ihler, T Ortmaier, LA Kahrs Current Directions in Biomedical Engineering 5 (1), 223-226, 2019 | 17 | 2019 |
Soft tissue motion tracking with application to tablet-based incision planning in laser surgery A Schoob, MH Laves, LA Kahrs, T Ortmaier International Journal of Computer Assisted Radiology and Surgery 11 (12 …, 2016 | 16 | 2016 |
Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say" I don't know" for Ambiguous Cases MH Laves, S Ihler, T Ortmaier Medical Imaging with Deep Learning--Extended Abstract Track, 2019 | 15 | 2019 |
Classification of road surface and weather-related condition using deep convolutional neural networks A Busch, D Fink, MH Laves, Z Ziaukas, M Wielitzka, T Ortmaier Advances in Dynamics of Vehicles on Roads and Tracks: Proceedings of the …, 2020 | 13 | 2020 |
Feature tracking for automated volume of interest stabilization on 4D-OCT images MH Laves, A Schoob, LA Kahrs, T Pfeiffer, R Huber, T Ortmaier Medical imaging 2017: image-guided procedures, robotic interventions, and …, 2017 | 13 | 2017 |
Self-supervised domain adaptation for patient-specific, real-time tissue tracking S Ihler, F Kuhnke, MH Laves, T Ortmaier Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 12 | 2020 |
Deformable medical image registration using a randomly-initialized CNN as regularization prior MH Laves, S Ihler, T Ortmaier Medical Imaging with Deep Learning--Extended Abstract Track, 2019 | 12 | 2019 |
Volumetric 3D stitching of optical coherence tomography volumes MH Laves, LA Kahrs, T Ortmaier Current Directions in Biomedical Engineering 4 (1), 327-330, 2018 | 10 | 2018 |
Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction M Bengs, F Behrendt, MH Laves, J Krüger, R Opfer, A Schlaefer Medical Imaging 2022: Computer-Aided Diagnosis 12033, 305-309, 2022 | 9 | 2022 |
Robotic tissue sampling for safe post-mortem biopsy in infectious corpses M Neidhardt, S Gerlach, R Mieling, MH Laves, T Weiß, M Gromniak, ... IEEE transactions on medical robotics and bionics 4 (1), 94-105, 2022 | 9 | 2022 |
Deep-learning-based 2.5 D flow field estimation for maximum intensity projections of 4D optical coherence tomography MH Laves, S Ihler, LA Kahrs, T Ortmaier Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and …, 2019 | 8 | 2019 |
Posterior temperature optimized Bayesian models for inverse problems in medical imaging MH Laves, M Tölle, A Schlaefer, S Engelhardt Medical image analysis 78, 102382, 2022 | 7 | 2022 |
Semantic denoising autoencoders for retinal optical coherence tomography MH Laves, S Ihler, LA Kahrs, T Ortmaier European Conference on Biomedical Optics, 11078_43, 2019 | 7 | 2019 |