Constantin Seibold
Orcid: 0000-0001-6042-8437
According to our database1,
Constantin Seibold
authored at least 34 papers
between 2019 and 2024.
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Bibliography
2024
Medical Image Anal., 2024
Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data.
CoRR, 2024
Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient Constraints.
CoRR, 2024
Autopet III challenge: Incorporating anatomical knowledge into nnUNet for lesion segmentation in PET/CT.
CoRR, 2024
CoRR, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Style Transfer and Pseudo-Label Filtering Improve Transferability in Cell Organelle Segmentation Scenarios.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Enhancing Contrastive Training for Semi-Supervised Chest X-Ray Analysis Through Gaussian Mixture Models.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
IKIM at MEDIQA-M3G 2024: Multilingual Visual Question-Answering for Dermatology through VLM Fine-tuning and LLM Translations.
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024
2023
PhD thesis, 2023
Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines.
CoRR, 2023
Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries.
CoRR, 2023
Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling.
CoRR, 2023
Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology.
Comput. Medical Imaging Graph., 2023
Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images Based on Physiological and Anatomical Cues.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Decoupled Semantic Prototypes enable learning from diverse annotation types for semi-weakly segmentation in expert-driven domains.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Breaking with Fixed Set Pathology Recognition Through Report-Guided Contrastive Training.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
A Comparative Analysis of Decision-Level Fusion for Multimodal Driver Behaviour Understanding.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022
Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data.
Proceedings of the 26th International Conference on Pattern Recognition, 2022
Graph-Constrained Contrastive Regularization for Semi-weakly Volumetric Segmentation.
Proceedings of the Computer Vision - ECCV 2022, 2022
Hierarchical Nearest Neighbor Graph Embedding for Efficient Dimensionality Reduction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the 33rd British Machine Vision Conference 2022, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.
npj Digit. Medicine, 2021
Flying Guide Dog: Walkable Path Discovery for the Visually Impaired Utilizing Drones and Transformer-based Semantic Segmentation.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2021
Prediction of Low-Kev Monochromatic Images From Polyenergetic CT Scans For Improved Automatic Detection of Pulmonary Embolism.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
Let's Play for Action: Recognizing Activities of Daily Living by Learning from Life Simulation Video Games.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
Proceedings of the 29th European Signal Processing Conference, 2021
Every Annotation Counts: Multi-Label Deep Supervision for Medical Image Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
Self-guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020
2019
Content and Colour Distillation for Learning Image Translations with the Spatial Profile Loss.
Proceedings of the 30th British Machine Vision Conference 2019, 2019