supervoxels

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AllenNeuralDynamics / supervoxel-loss

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Efficient connectivity-preserving loss function for training neural networks to perform instance segmentation.

computer-vision deep-learning neuron-segmentation digital-topology topological-loss-function supervoxels

Updated Apr 21, 2026
Python

albertovalerio / multimetric-framework-for-gnn-explanations

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Multi-metric framework for quantitatively validating GNN explanations in brain tumor segmentation. It evaluates GraphSAGE, GAT, and ChebNet with Integrated Gradients, GraphLIME, and GNNExplainer on BraTS 2023 supervoxel graphs.

medical-imaging supervoxel brats explainable-ai graph-neural-networks brain-tumor-segmentation integrated-gradients xai-evaluation brats2023 supervoxels gnnexplainer graphlime gnn-explainability supervoxel-graphs

Updated Jul 31, 2026
Jupyter Notebook

marvelpokemaster / BRATS

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QoS-HRGN: Heterogeneous Multimodal Graph Learning with Heterogeneous Graph Transformers (HGT) and Adaptive Multi-Hop Propagation for 3D BraTS Segmentation

deep-learning medical-imaging hgt brats graph-neural-networks brain-tumor-segmentation mri-segmentation pytorch-geometric heterogeneous-graphs supervoxels

Updated Sep 12, 2026
Jupyter Notebook

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