AnonRes commited on
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48e05f3
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1 Parent(s): fd51bd5

Update CKPT to allow weights_only=True loading and add config.json for download tracking

Browse files
Files changed (3) hide show
  1. adaptation_plan.json +11 -11
  2. checkpoint_final.pth +2 -2
  3. config.json +3 -0
adaptation_plan.json CHANGED
@@ -54,9 +54,9 @@
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  1
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  ],
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  "patch_size": [
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- 64,
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- 64,
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- 64
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  ]
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  }
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  },
@@ -79,29 +79,29 @@
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  {
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  "type": "Architecture",
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  "name": "ResEncL",
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- "bibtex_citations": [
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- "@inproceedings{isensee2024nnu,\n title={nnu-net revisited: A call for rigorous validation in 3d medical image segmentation},\n author={Isensee, Fabian and Wald, Tassilo and Ulrich, Constantin and Baumgartner, Michael and Roy, Saikat and Maier-Hein, Klaus and Jaeger, Paul F},\n booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},\n pages={488--498},\n year={2024},\n organization={Springer}\n }"
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  ]
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  },
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  {
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  "type": "Pretraining Method",
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  "name": "Volume Fusion",
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- "bibtex_citations": [
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- "@article{wang2023mis,\n title={Mis-fm: 3d medical image segmentation using foundation models pretrained on a large-scale unannotated dataset},\n author={Wang, Guotai and Wu, Jianghao and Luo, Xiangde and Liu, Xinglong and Li, Kang and Zhang, Shaoting},\n journal={arXiv preprint arXiv:2306.16925},\n year={2023}\n}"
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  ]
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  },
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  {
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  "type": "Pre-Training Dataset",
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  "name": "OpenMind",
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- "bibtex_citations": [
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- "@article{wald2024openmind,\n title={An OpenMind for 3D medical vision self-supervised learning},\n author={Wald, Tassilo and Ulrich, Constantin and Suprijadi, Jonathan and Ziegler, Sebastian and Nohel, Michal and Peretzke, Robin and K{\"o}hler, Gregor and Maier-Hein, Klaus H},\n journal={arXiv preprint arXiv:2412.17041},\n year={2024}\n }\n "
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  ]
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  },
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  {
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  "type": "Framework",
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  "name": "nnssl",
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- "bibtex_citations": [
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- "@article{wald2024revisiting,\n title={Revisiting MAE pre-training for 3D medical image segmentation},\n author={Wald, Tassilo and Ulrich, Constantin and Lukyanenko, Stanislav and Goncharov, Andrei and Paderno, Alberto and Maerkisch, Leander and J{\"a}ger, Paul F and Maier-Hein, Klaus},\n journal={arXiv preprint arXiv:2410.23132},\n year={2024}\n}"
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  ]
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  }
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  ],
 
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  1
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  ],
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  "patch_size": [
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+ 160,
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+ 160,
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+ 160
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  ]
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  }
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  },
 
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  {
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  "type": "Architecture",
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  "name": "ResEncL",
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+ "apa_citations": [
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+ "Isensee, F., Wald, T., Ulrich, C., Baumgartner, M., Roy, S., Maier-Hein, K., & Jaeger, P. F. (2024, October). nnu-net revisited: A call for rigorous validation in 3d medical image segmentation. MICCAI."
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  ]
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  },
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  {
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  "type": "Pretraining Method",
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  "name": "Volume Fusion",
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+ "apa_citations": [
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+ "Wang, G., Wu, J., Luo, X., Liu, X., Li, K., & Zhang, S. (2023). Mis-fm: 3d medical image segmentation using foundation models pretrained on a large-scale unannotated dataset. arXiv preprint arXiv:2306.16925."
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  ]
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  },
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  {
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  "type": "Pre-Training Dataset",
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  "name": "OpenMind",
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+ "apa_citations": [
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+ "Wald, T., Ulrich, C., Suprijadi, J., Ziegler, S., Nohel, M., Peretzke, R., ... & Maier-Hein, K. H. (2024). An OpenMind for 3D medical vision self-supervised learning. arXiv preprint arXiv:2412.17041."
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  ]
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  },
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  {
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  "type": "Framework",
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  "name": "nnssl",
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+ "apa_citations": [
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+ "Wald, T., Ulrich, C., Lukyanenko, S., Goncharov, A., Paderno, A., Maerkisch, L., ... & Maier-Hein, K. (2024). Revisiting MAE pre-training for 3D medical image segmentation. CVPR."
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  ]
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  }
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  ],
checkpoint_final.pth CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:4ff1855da724cb9ed00eafccc571e6211f998b01c634de17510eea7fb4332b3a
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- size 491211854
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:b067720b1846376e0fa5ebd45a4bb42977ce5fcfec003f848e495715b740d369
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+ size 491210894
config.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ {
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+ "description": "Dummy config to allow tracking HF downloads."
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+ }