pneumonia_mnist

  • 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.

Split Examples
  • 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 
@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}
}