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frac-atlas

FracAtlas: A Dataset for Fracture Classification, Localization and Segmentation of Musculoskeletal Radiographs

https://github.com/dataset-ninja/frac-atlas

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (0.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

FracAtlas: A Dataset for Fracture Classification, Localization and Segmentation of Musculoskeletal Radiographs

Basic Info
  • Host: GitHub
  • Owner: dataset-ninja
  • License: other
  • Language: Python
  • Default Branch: main
  • Size: 3.76 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

FracAtlas: A Dataset for Fracture Classification, Localization and Segmentation of Musculoskeletal Radiographs

FracAtlas is a dataset for instance segmentation, semantic segmentation, object detection, and classification tasks.

Owner

  • Name: dataset-ninja
  • Login: dataset-ninja
  • Kind: organization

Citation (CITATION.md) 

If you make use of the FracAtlas data, please cite the following reference:

```bibtex
@article{Abedeen_2023,
  title        = {{FracAtlas}: A Dataset for Fracture Classification, Localization and Segmentation of Musculoskeletal Radiographs},
  author       = {Iftekharul Abedeen and Md. Ashiqur Rahman and Fatema Zohra Prottyasha and Tasnim Ahmed and Tareque Mohmud Chowdhury and Swakkhar Shatabda},
  year         = 2023,
  month        = {aug},
  journal      = {Scientific Data},
  publisher    = {Springer Science and Business Media {LLC}},
  volume       = 10,
  number       = 1,
  doi          = {10.1038/s41597-023-02432-4},
  url          = {https://doi.org/10.1038%2Fs41597-023-02432-4}
}
```

[Source](https://figshare.com/articles/dataset/The_dataset/22363012)

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Dependencies

requirements.txt pypi