Datasets:
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---
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")
``` |