- Description:
MedMNIST Pneumonia Dataset
The PneumoniaMNIST is based on a prior dataset of 5,856 pediatric chest X-Ray images. The task is binary-class classification of pneumonia against normal. The source training set is split with a ratio of 9:1 into training and validation set, and use its source validation set as the test set. The source images are gray-scale, and their sizes are (384–2,916) × (127–2,713). The images are center-cropped with a window size of length of the short edge and resized into 1 × 28 × 28.
Homepage: https://medmnist.com//
Source code:
tfds.datasets.pneumonia_mnist.BuilderVersions:
1.0.0(default): Initial release.
Download size:
Unknown sizeDataset size:
3.66 MiBAuto-cached (documentation): Yes
Splits:
| Split | Examples |
|---|---|
'test' |
624 |
'train' |
4,708 |
'val' |
524 |
- Feature structure:
FeaturesDict({
'image': Image(shape=(28, 28, 1), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
})
- Feature documentation:
| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
| FeaturesDict | ||||
| image | Image | (28, 28, 1) | uint8 | |
| label | ClassLabel | int64 |
Supervised keys (See
as_superviseddoc):('image', 'label')Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
@article{yang2023medmnist,
title={Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification},
author={Yang, Jiancheng and Shi, Rui and Wei, Donglai and Liu, Zequan and Zhao, Lin and Ke, Bilian and Pfister, Hanspeter and Ni, Bingbing},
journal={Scientific Data},
volume={10},
number={1},
pages={41},
year={2023},
publisher={Nature Publishing Group UK London}
}