size_categories:1K<n<10K format:parquet modality:image library:datasets library:dask library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: label
    dtype: image
  splits:
  - name: train
    num_bytes: 1269680775.5
    num_examples: 3025
  - name: test
    num_bytes: 229042164.0
    num_examples: 553
  download_size: 1464680989
  dataset_size: 1498722939.5
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---

ChestX-Det is a chest X-Ray dataset with instance-level annotations (boxes and masks). ChestX-Det is a subset of the public dataset NIH ChestX-ray14. It contains ~3500 images of 13 common disease categories labeled by three board-certified radiologists.

I created segmentation masks for each image in the dataset. Each image is mapped to a unique RGB value.

The repository from Deepwise AILab can be found at: https://github.com/Deepwise-AILab/ChestX-Det-Dataset.

More information at: https://paperswithcode.com/dataset/chestx-det.