Sontje Ihler

According to our database, Sontje Ihler authored at least 17 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Distribution-Aware Multi-Label FixMatch for Semi-Supervised Learning on CheXpert.

Sontje Ihler, Felix Kuhnke, Timo Kuhlgatz, Thomas Seel

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Improving instrument detection for a robotic scrub nurse using multi-view voting.

Jorge Badilla-Solórzano, Sontje Ihler, Nils-Claudius Gellrich, Simon Spalthoff

Int. J. Comput. Assist. Radiol. Surg., November, 2023

Modular, Label-Efficient Dataset Generation for Instrument Detection for Robotic Scrub Nurses.

Jorge Badilla-Solórzano, Nils-Claudius Gellrich, Thomas Seel, Sontje Ihler

Proceedings of the Data Augmentation, Labelling, and Imperfections - Third MICCAI Workshop, 2023

2022

Deep-learning-based instrument detection for intra-operative robotic assistance.

Jorge Badilla-Solórzano, Svenja Spindeldreier, Sontje Ihler, Nils-Claudius Gellrich, Simon Spalthoff

Int. J. Comput. Assist. Radiol. Surg., 2022

A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000.

Sontje Ihler, Felix Kuhnke, Svenja Spindeldreier

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging.

Max-Heinrich Laves, Sontje Ihler, Jacob Friedemann Fast, Lüder A. Kahrs, Tobias Ortmaier

CoRR, 2021

Relative Pose Consistency for Semi-Supervised Head Pose Estimation.

Felix Kuhnke, Sontje Ihler, Jörn Ostermann

Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021

2020

Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer.

Sontje Ihler, Max-Heinrich Laves, Tobias Ortmaier

CoRR, 2020

Calibration of Model Uncertainty for Dropout Variational Inference.

Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier

CoRR, 2020

Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning.

Max-Heinrich Laves, Sontje Ihler, Jacob Friedemann Fast, Lüder A. Kahrs, Tobias Ortmaier

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking.

Sontje Ihler, Felix Kuhnke, Max-Heinrich Laves, Tobias Ortmaier

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference.

Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier

CoRR, 2019

Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases.

Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier

CoRR, 2019

Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior.

Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier

CoRR, 2019

Retinal OCT disease classification with variational autoencoder regularization.

Max-Heinrich Laves, Sontje Ihler, Lüder A. Kahrs, Tobias Ortmaier

CoRR, 2019

Semantic denoising autoencoders for retinal optical coherence tomography.

Max-Heinrich Laves, Sontje Ihler, Lüder Alexander Kahrs, Tobias Ortmaier

CoRR, 2019

Deep-learning-based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography.

Max-Heinrich Laves, Sontje Ihler, Lüder A. Kahrs, Tobias Ortmaier

Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019