metadata

annotations_creators: []
language: en
size_categories:
  - 1K<n<10K
task_categories:
  - object-detection
task_ids: []
pretty_name: deeplesion_balanced
tags:
  - fiftyone
  - image
  - object-detection
dataset_summary: >




  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2161
  samples.


  ## Installation


  If you haven't already, install FiftyOne:


  ```bash

  pip install -U fiftyone

  ```


  ## Usage


  ```python

  import fiftyone as fo

  from fiftyone.utils.huggingface import load_from_hub


  # Load the dataset

  # Note: other available arguments include 'max_samples', etc

  dataset = load_from_hub("pjramg/deeplesion_balanced_fiftyone")


  # Launch the App

  session = fo.launch_app(dataset)

  ```

DeepLesion Benchmark Subset (Balanced 2K)

This dataset is a curated subset of the DeepLesion dataset, prepared for demonstration and benchmarking purposes. It consists of 2,000 CT lesion samples, balanced across 8 coarse lesion types, and filtered to include lesions with a short diameter > 10mm.

Dataset Details

Source: DeepLesion
Institution: National Institutes of Health (NIH) Clinical Center
Subset size: 2,000 images
Lesion types: lung, abdomen, mediastinum, liver, pelvis, soft tissue, kidney, bone
Selection criteria:
- Short diameter > 10mm
- Balanced sampling across all types
Windowing: All slices were windowed using DICOM parameters and converted to 8-bit PNG format

License

This dataset is shared under the CC BY-NC-SA 4.0 License, as specified by the NIH DeepLesion dataset creators.

This dataset is intended only for non-commercial research and educational use.
You must credit the original authors and the NIH Clinical Center when using this data.

Citation

If you use this data, please cite:

@article{yan2018deeplesion,
title={DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning},
author={Yan, Ke and Zhang, Yao and Wang, Le Lu and Huang, Xuejun and Summers, Ronald M},
journal={Journal of medical imaging},
volume={5},
number={3},
pages={036501},
year={2018},
publisher={SPIE}
}

Curation done by FiftyOne.
@article{moore2020fiftyone,
  title={FiftyOne},
  author={Moore, B. E. and Corso, J. J.},
  journal={GitHub. Note: https://github.com/voxel51/fiftyone},
  year={2020}
}

Intended Uses

Embedding demos
Lesion similarity and retrieval
Benchmarking medical image models
Few-shot learning on lesion types

Limitations

This is a small subset of the full DeepLesion dataset
Not suitable for training full detection models
Labels are coarse and may contain inconsistencies

Contact

Created by Paula Ramos for demo purposes using FiftyOne and the DeepLesion public metadata.