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MECLabTUDA/VoxelSceneGraph

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Voxel Scene Graph

This is our central hub for all our work on Voxel Scene Graph. It is still a WIP and fancy illustrations may come in the future. Anyway here is an overview of the repository that you can find here:

  • pycocotools3d: object detection evaluation for 3d bounding boxes and MS COCO format abstractions
  • scene-graph-api: data structures and abstractions to bridge data annotation and Deep Learning applications
  • scene-graph-prediction: framework for Voxel Scene Graph applications
  • federated-scene-graph-prediction: framework for Voxel Scene Graph applications trained using Federated Learning
  • theoden: our fork of TheODen framework for Federated Learning. Made with love by our colleagues ❤️
  • scene-graph-annotation: tool for Voxel Scene Graph annotation and much more (TBA) 😉
  • scene-graph-data: instructions for downloading our datasets (TBA) 😉

Our Accepted Papers

Federated Voxel Scene Graph for Intracranial Hemorrhage

datasets_WACV2025.png

This paper has been accepted at WACV2025. To the best of our knowledge, this is the first application of Federated Learning to Scene Graph Generation of any kind. For this paper, we had to gather publicly available datasets with head CTs of ICH patients from around the world. We then curated and annotated these, which allowed to have ~450 annotated images (compared to the ~150 from the MICCAI paper). In this paper, we not only show that models trained centrally on a single dataset fail to generalize to other datasets, but that Federated Learning allows bridging this gap without breach of data privacy. You can find the pre-print here:

Sanner, A. P., Stieber, J., Grauhan, N. F., Kim, S., Brockmann, M. A., Othman, A. E., & Mukhopadhyay, A. (2024). 
Federated Voxel Scene Graph for Intracranial Hemorrhage. arXiv [Cs.CV]. Retrieved from https://arxiv.org/abs/2411.00578

method_MICCAI2024.png

This paper has been accepted at MICCAI2024. To the best of our knowledge, this is the first application of Scene Graph to voxel data. In particular, we show how only detecting Intracranial Hemorrhage (ICH) is clinically insufficient, as bleedings interact with neighboring brain structures, potentially causing deadly complications. Scene Graphs can capture the entire clinical cerebral scene and model these complex relations. You can find the pre-print here:

Sanner, A. P., Grauhan, N. F., Brockmann, M. A., Othman, A. E., & Mukhopadhyay, A. (2024). 
Voxel Scene Graph for Intracranial Hemorrhage. arXiv [Cs.CV]. Retrieved from https://arxiv.org/abs/2407.21580

Detection of Intracranial Hemorrhage for Trauma Patients

method_ICPR2024.png

This paper has been accepted at ICPR2024. It focuses on the challenges of Intracranial Hemorrhage detection in voxel data, and introduced the novel VC-IoU loss for bounding box regression. You can find the pre-print here:

Sanner, A. P., Grauhan, N. F., Brockmann, M. A., Othman, A. E., & Mukhopadhyay, A. (2024). 
Detection of Intracranial Hemorrhage for Trauma Patients. arXiv [Cs.CV]. 
Retrieved from https://arxiv.org/abs/2408.10768

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