Paul Jaeger

Orcid: 0000-0002-6243-2568

According to our database1, Paul Jaeger authored at least 58 papers between 2017 and 2024.

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Bibliography

2024
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation.
CoRR, 2024

Abstract: 3D Medical Image Segmentation with Transformer-based Scaling of ConvNets - MedNeXt.
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.
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
Wearable based monitoring and self-supervised contrastive learning detect clinical complications during treatment of Hematologic malignancies.
npj Digit. Medicine, 2023

The Liver Tumor Segmentation Benchmark (LiTS).
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Medical Image Anal., 2023

Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy.
CoRR, 2023

Application-driven Validation of Posteriors in Inverse Problems.
CoRR, 2023

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement.
CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.
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.
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

Evaluating the Accessibility of Digital Government Services for Family Law in the U.S. during the COVID-19 Pandemic.
Proceedings of the 56th Hawaii International Conference on System Sciences, 2023

Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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.
IEEE Trans. Medical Imaging, 2022

MONAI: An open-source framework for deep learning in healthcare.
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.
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.
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.
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.
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.
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.
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.
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?
IEEE Trans. Medical Imaging, 2018

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.
CoRR, 2018

Domain Adaptation for Deviating Acquisition Protocols in CNN-Based Lesion Classification on Diffusion-Weighted MR Images.
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.
Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017
Revealing Hidden Potentials of q-Space Imaging in Breast Cancer.
CoRR, 2017

Revealing Hidden Potentials of the q-Space Signal in Breast Cancer.
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


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