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Max-Heinrich Laves
Max-Heinrich Laves
ImFusion GmbH, Munich
Verified email at imfusion.com - Homepage
Title
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Cited by
Year
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
912019
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
732020
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
502019
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
392020
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
272021
Calibration of model uncertainty for dropout variational inference
MH Laves, S Ihler, KP Kortmann, T Ortmaier
arXiv preprint arXiv:2006.11584, 2020
202020
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
172019
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
162016
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
142021
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
142019
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
132019
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
132017
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
122020
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
102020
Volumetric 3D stitching of optical coherence tomography volumes
MH Laves, LA Kahrs, T Ortmaier
Current Directions in Biomedical Engineering 4 (1), 327-330, 2018
102018
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
92022
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
82022
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
82019
Semantic denoising autoencoders for retinal optical coherence tomography
MH Laves, S Ihler, LA Kahrs, T Ortmaier
European Conference on Biomedical Optics, 11078_43, 2019
72019
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
52022
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