2025
Comparative benchmarking of failure detection methods in medical image segmentation: Unveiling the role of confidence aggregation.
Medical Image Anal., 2025
2024
Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024
SURE-VQA: Systematic Understanding of Robustness Evaluation in Medical VQA Tasks.
CoRR, 2024
RadioActive: 3D Radiological Interactive Segmentation Benchmark.
CoRR, 2024
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
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CoRR, 2024
Revisiting MAE pre-training for 3D medical image segmentation.
CoRR, 2024
Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities.
CoRR, 2024
Visual Prompt Engineering for Medical Vision Language Models in Radiology.
CoRR, 2024
Enhancing predictive imaging biomarker discovery through treatment effect analysis.
CoRR, 2024
Embarrassingly Simple Scribble Supervision for 3D Medical Segmentation.
CoRR, 2024
Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology.
CoRR, 2024
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Overcoming Common Flaws in the Evaluation of Selective Classification Systems.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI?
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Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Abstract: 3D Medical Image Segmentation with Transformer-based Scaling of ConvNets - MedNeXt.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
Abstract: Anatomy-informed Data Augmentation for Enhanced Prostate Cancer Detection.
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Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
Abstract: RecycleNet - Latent Feature Recycling Leads to Iterative Decision Refinement.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
Abstract: Understanding Silent Failures in Medical Image Classification.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
Abstract: Object Detection for Breast Diffusion-weighted Imaging.
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Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
Abstract: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection using Contrastive Representations - cOOpD.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
2023
The Liver Tumor Segmentation Benchmark (LiTS).
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Medical Image Anal., 2023
Application-driven Validation of Posteriors in Inverse Problems.
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CoRR, 2023
Understanding metric-related pitfalls in image analysis validation.
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CoRR, 2023
Toward Realistic Evaluation of Deep Active Learning Algorithms in Image Classification.
CoRR, 2023
CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization.
CoRR, 2023
Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
MedNeXt: Transformer-Driven Scaling of ConvNets for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Anatomy-Informed Data Augmentation for Enhanced Prostate Cancer Detection.
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Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Deployment of Image Analysis Algorithms Under Prevalence Shifts.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Understanding Silent Failures in Medical Image Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
cOOpD: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection Using Contrastive Representations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Abstract: MOOD 2020 - A Public Benchmark for Out-of-distribution Detection and Localization on Medical Images.
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Proceedings of the Bildverarbeitung für die Medizin 2023, 2023
Contrastive Representations for Unsupervised Anomaly Detection and Localization.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023
2022
MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.
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IEEE Trans. Medical Imaging, 2022
MONAI: An open-source framework for deep learning in healthcare.
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CoRR, 2022
From Correlation to Causation: Formalizing Interpretable Machine Learning as a Statistical Process.
CoRR, 2022
Metrics reloaded: Pitfalls and recommendations for image analysis validation.
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CoRR, 2022
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Heterogeneous Model Ensemble For Automatic Polyp Detection and Tracking In Colonoscopy.
Proceedings of the 4th International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2022) co-located with the 19th IEEE International Symposium on Biomedical Imaging (ISBI 2022), 2022
Realistic Evaluation of FixMatch on Imbalanced Medical Image Classification Tasks.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022
Abstract: nnDetection - A Self-configuring Method for Medical Object Detection.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022
2021
Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge.
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NeuroImage, 2021
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data.
CoRR, 2021
Common Limitations of Image Processing Metrics: A Picture Story.
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CoRR, 2021
GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Continuous-Time Deep Glioma Growth Models.
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Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
nnDetection: A Self-configuring Method for Medical Object Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Abstract: Studying Robustness of Semantic Segmentation under Domain Shift in Cardiac MRI.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021
2020
Challenges and Opportunities of End-to-End Learning in Medical Image Classification
PhD thesis, 2020
Studying Robustness of Semantic Segmentation Under Domain Shift in Cardiac MRI.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020
nnU-Net for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020
Abstract: Deep Probabilistic Modeling of Glioma Growth.
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Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020
2019
nnU-Net: Breaking the Spell on Successful Medical Image Segmentation.
CoRR, 2019
Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection.
Proceedings of the Machine Learning for Health Workshop, 2019
Reg R-CNN: Lesion Detection and Grading Under Noisy Labels.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures, 2019
Deep Probabilistic Modeling of Glioma Growth.
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Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.
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Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019
2018
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
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IEEE Trans. Medical Imaging, 2018
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.
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CoRR, 2018
Domain Adaptation for Deviating Acquisition Protocols in CNN-Based Lesion Classification on Diffusion-Weighted MR Images.
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Proceedings of the Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018
Advanced Deep Learning Methods.
Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018
Abstract: Revealing Hidden Potentials of the q-Space Signal in Breast Cancer.
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Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018
2017
Revealing Hidden Potentials of q-Space Imaging in Breast Cancer.
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CoRR, 2017
Revealing Hidden Potentials of the q-Space Signal in Breast Cancer.
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Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features.
Proceedings of the Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, 2017