---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: pathols
    sequence: uint8
  - name: structs
    sequence:
      sequence:
        sequence: uint8
  splits:
  - name: train
    num_bytes: 17021730614.839962
    num_examples: 23094
  - name: test
    num_bytes: 4255801185.160039
    num_examples: 5774
  download_size: 732030045
  dataset_size: 21277531800
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
license: apache-2.0
task_categories:
- image-classification
- feature-extraction
---

## Dataset Structure
This dataset contains vision data for chest X-ray pathology identification.

### Data Fields
- **image**: The PIL image of the chest X-ray. These images are size (224,224) by default.
- **pathols**: A binary-valued (14)-shaped array that indicates whether each of the 14 pathologies is present.
- **structs**: A binary-valued array of shapes (14,224,224) that gives the segmentation for each of the 14 anatomical structures.

The 14 pathologies are:

  0. Atelectasis
  1. Cardiomegaly
  2. Consolidation
  3. Edema
  4. Effusion
  5. Emphysema
  6. Fibrosis
  7. Hernia
  8. Infiltration
  9. Mass
  10. Nodule
  11. Pleural Thickening
  12. Pneumonia
  13. Pneumothorax

The 14 anatomical structures are:

  0. Left Clavicle
  1. Right Clavicle
  2. Left Scapula
  3. Right Scapula
  4. Left Lung
  5. Right Lung
  6. Left Hilus Pulmonis
  7. Right Hilus Pulmonis
  8. Heart
  9. Aorta
  10. Facies Diaphragmatica
  11. Mediastinum
  12. Weasand
  13. Spine

### Data Splits
- **train**: 23094 samples
- **test**: 5774 samples


## Usage
```
from datasets import load_dataset
train_dataset = load_dataset("BrachioLab/chestx", split="train")
test_dataset = load_dataset("BrachioLab/chestx", split="test")
```