fix-volume
#6
by eigenvivek - opened
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- .gitattributes +0 -1
- README.md +25 -41
- deepfluoro/LICENSE +0 -407
- deepfluoro/README.md +1 -10
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.gitattributes
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deepfluoro/subject06/xrays/021.dcm filter=lfs diff=lfs merge=lfs -text
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*.dcm filter=lfs diff=lfs merge=lfs -text
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deepfluoro/subject06/xrays/021.dcm filter=lfs diff=lfs merge=lfs -text
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README.md
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license: cc-by-nc-nd-4.0
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task_categories:
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- image-to-image
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pretty_name: xvr datasets
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---
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- Paper: [Rapid patient-specific neural networks for intraoperative X-ray to volume registration](https://huggingface.co/papers/2503.16309)
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- Code: https://github.com/eigenvivek/xvr
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## Citation
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If you use
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If you use the [`Femur`](https://rflepp.github.io/BoneSubstructureContours2D3DRegistration/) dataset (CC BY-NC-ND 4.0; remixed version hosted with permission from original authors), please cite:
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@article{flepp2025automatic,
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title={Automatic multi-view X-ray/CT registration using bone substructure contours},
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author={Flepp, Roman and Nissen, Leon and Sigrist, Bastian and Nieuwland, Arend and Cavalcanti, Nicola and F{\"u}rnstahl, Philipp and Dreher, Thomas and Calvet, Lilian},
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journal={International Journal of Computer Assisted Radiology and Surgery},
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volume={20},
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number={7},
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pages={1401--1408},
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year={2025},
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publisher={Springer}
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}
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}
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license: cc-by-nc-nd-4.0
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task_categories:
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- image-to-image
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---
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`xvr-data` contains DICOM/NIfTI versions of the `DeepFluoro` and `Ljubljana` datasets.
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Paper: [Rapid patient-specific neural networks for intraoperative X-ray to volume registration](https://huggingface.co/papers/2503.16309)
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Code: https://github.com/eigenvivek/xvr
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## Citation
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If you use either of these datasets, please cite the original papers.
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```bibtex
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@article{grupp2020automatic,
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title={Automatic annotation of hip anatomy in fluoroscopy for robust and efficient 2D/3D registration},
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author={Grupp, Robert B and Unberath, Mathias and Gao, Cong and Hegeman, Rachel A and Murphy, Ryan J and Alexander, Clayton P and Otake, Yoshito and McArthur, Benjamin A and Armand, Mehran and Taylor, Russell H},
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journal={International journal of computer assisted radiology and surgery},
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volume={15},
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pages={759--769},
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year={2020},
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publisher={Springer}
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}
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@article{pernus20133d,
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title={3D-2D registration of cerebral angiograms: A method and evaluation on clinical images},
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author={Mitrović, Uros˘ and S˘piclin, Z˘iga and Likar, Bos˘tjan and Pernus˘, Franjo},
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journal={IEEE transactions on medical imaging},
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volume={32},
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number={8},
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pages={1550--1563},
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year={2013},
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publisher={IEEE}
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}
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```
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deepfluoro/LICENSE
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|
deepfluoro/README.md
CHANGED
|
@@ -10,13 +10,4 @@
|
|
| 10 |
pages={759--769},
|
| 11 |
year={2020},
|
| 12 |
publisher={Springer}
|
| 13 |
-
}
|
| 14 |
-
|
| 15 |
-
## `segmentations_multichannel/`
|
| 16 |
-
|
| 17 |
-
Packed 7-channel masks, one `.pt` per X-ray. Each is a `(1536, 1536)` `uint8` array where bit `i` is label `i+1` (0: L-hemipelvis, 1: R-hemipelvis, 2: vertebrae, 3: upper sacrum, 4: L-femur, 5: R-femur, 6: lower sacrum).
|
| 18 |
-
|
| 19 |
-
```python
|
| 20 |
-
packed = torch.load(path) # (1536, 1536) uint8
|
| 21 |
-
masks = (packed[None] >> torch.arange(7)[:, None, None]) & 1 # (7, 1536, 1536) bool
|
| 22 |
-
```
|
|
|
|
| 10 |
pages={759--769},
|
| 11 |
year={2020},
|
| 12 |
publisher={Springer}
|
| 13 |
+
}
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|
deepfluoro/subject01/fiducials.pt
CHANGED
|
Binary files a/deepfluoro/subject01/fiducials.pt and b/deepfluoro/subject01/fiducials.pt differ
|
|
|
deepfluoro/subject01/segmentations_multichannel/000.pt
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:8887e702a6b485ab30c4d3d93fe275b1acac507c5b5472054e740f256c77ce9f
|
| 3 |
-
size 2360781
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