Constantin Ulrich

Orcid: 0000-0003-3002-8170

According to our database1, Constantin Ulrich authored at least 42 papers between 2023 and 2025.

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Bibliography

2025
Large Scale Supervised Pretraining For Traumatic Brain Injury Segmentation.
CoRR, April, 2025

nnInteractive: Redefining 3D Promptable Segmentation.
CoRR, March, 2025

Primus: Enforcing Attention Usage for 3D Medical Image Segmentation.
CoRR, March, 2025

ScaleMAI: Accelerating the Development of Trusted Datasets and AI Models.
CoRR, January, 2025

SegRap2023: A benchmark of organs-at-risk and gross tumor volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma.
Medical Image Anal., 2025

Revisiting MAE Pre-training for 3D Medical Image Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body Imaging.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Abstract: Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Unified Framework for Foreground and Anonymization Area Segmentation in CT and MRI Data.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Abstract: Skeleton Recall Loss - Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Abstract: nnU-Net Revisited - Call for Rigorous Validation in 3D Medical Image Segmentation.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Abstract: Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

2024
An OpenMind for 3D medical vision self-supervised learning.
CoRR, 2024

Unlocking the Potential of Digital Pathology: Novel Baselines for Compression.
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?
CoRR, 2024

Revisiting MAE pre-training for 3D medical image segmentation.
CoRR, 2024

Data-Centric Strategies for Overcoming PET/CT Heterogeneity: Insights from the AutoPET III Lesion Segmentation Challenge.
CoRR, 2024

From FDG to PSMA: A Hitchhiker's Guide to Multitracer, Multicenter Lesion Segmentation in PET/CT Imaging.
CoRR, 2024

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024


Mitigating False Predictions in Unreasonable Body Regions.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024

Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops, 2024

Optimizing nnU-Net with OpenVINO for Fast CPU Inference in Abdominal Organ Segmentation.
Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Efficient Cross-Modality Abdominal Organ Segmentation Using nnU-Net and MIND Descriptors.
Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Efficient Pan-Cancer Lesion Segmentation from Partially Labeled Data with nnU-Net.
Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Enhanced nnU-Net Architectures for Automated MRI Segmentation of Head and Neck Tumors in Adaptive Radiation Therapy.
Proceedings of the Head and Neck Tumor Segmentation for MR-Guided Applications, 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

Scaling nnU-Net for CBCT Segmentation.
Proceedings of the Supervised and Semi-supervised Multi-structure Segmentation and Landmark Detection in Dental Data, 2024

Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops, 2024

Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures.
Proceedings of the Computer Vision - ECCV 2024, 2024

Abstract: Multi-dataset Approach to Medical Image Segmentation - MultiTalent.
Proceedings of the Bildverarbeitung für die Medizin 2024, 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: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency.
CoRR, 2023

Transformer Utilization in Medical Image Segmentation Networks.
CoRR, 2023

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

MultiTalent: A Multi-dataset Approach to Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 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

Extending nnU-Net Is All You Need.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023


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