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license: cc-by-4.0 |
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This model is trained on the CAMUS dataset: S. Leclerc, E. Smistad, J. Pedrosa, A. Ostvik, et al. |
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"Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography" |
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in IEEE Transactions on Medical Imaging, vol. 38, no. 9, pp. 2198-2210, Sept. 2019. doi: 10.1109/TMI.2019.2900516 |
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This model uses the nnU-Net architecture: Isensee, F., Jaeger, P.F., Kohl, S.A.A. et al. nnU-Net: |
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a self-configuring method for deep learning-based biomedical image segmentation. |
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Nat Methods 18, 203–211 (2021). https://doi.org/10.1038/s41592-020-01008-z |
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This model is part of the following work. You must cite this paper for any use of the model: |
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G.Van De Vyver, S. Thomas, G. Ben-Yosef, S. H. Olaisen, H. Dalen, L. Løvstakken, and E. Smistad: |
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“Towards Robust Cardiac Segmentation using Graph Convolutional Networks” |
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in arXiv preprint arXiv:2310.01210, 2023, https://github.com/gillesvntnu/GCN_multistructure.git |
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The model is the .pth version of the nnU-Net model as described in the work mentioned above. |
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It is trained on the first split of the CAMUS dataset. |
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The model can be directly used in the framework provided at |
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https://github.com/gillesvntnu/GCN_multistructure.git |
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Information on the splits of the CAMUS dataset can be found at: |
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https://github.com/gillesvntnu/GCN_multistructure/tree/main/files/subgroups_CAMUS |
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For the corresponding version in .onnx format, see |
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https://huggingface.co/gillesvdv/nnunet_camus_cv1_onnx |
