mimic-cxr-jpg-loader 0.0.4

A package which facilitates loading data from the MIMIC-CXR-JPG dataset

mimic-cxr-jpg-loader

mimic-cxr-jpg-loader is a Python package that provides utilities to easily load the MIMIC-CXR-JPG Dataset [1], [2] which is available on Physionet [3]. This dataset contains chest X-ray images in JPG format from the MIMIC-CXR dataset, which is a large publicly available dataset of chest radiographs in DICOM format.

Installation

You can install mimic-cxr-jpg-loader via pip:

pip install mimic-cxr-jpg-loader

Usage

To use this package simply create a new Dataset by providing the required filepaths and, optionally, a list of modifiers.

from mimic_cxr_jpg_loader.dataset import MIMICDataset
from mimic_cxr_jpg_loader.modifiers import *

dataset = MIMICDataset(
    root="/example/datasets/MIMIC-CXR-JPG",
    split_path="/example/datasets/MIMIC-CXR-JPG/mimic-cxr-2.0.0-split.csv",
    modifiers=[
        FilterByViewPosition(ViewPosition.PA),
        FilterBySplit(Split.TRAIN),
        BinarizePathology(Pathology.CARDIOMEGALY),
    ],
)

Afterwards simply access the dataset like a regular Pytorch Dataset, e.g. dataset[idx] which will return a tuple in the format (img, labels) where img is a Pillow Image object and labels a Pandas Series object containing all data pertaining to it.

Requirements

• Python >= 3.8
• Pandas
• Pillow

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contribution

Contributions are welcome! Please feel free to open a pull request.

Issues

If you encounter any issues or have suggestions, please feel free to open an issue.

Acknowledgments

• The MIMIC-CXR-JPG dataset was made available by the MIT Laboratory for Computational Physiology.
• This package is inspired by the need for simplified access to the MIMIC-CXR-JPG dataset.

References

[1] Johnson, A., Lungren, M., Peng, Y., Lu, Z., Mark, R., Berkowitz, S., & Horng, S. (2024). MIMIC-CXR-JPG - chest radiographs with structured labels (version 2.1.0). PhysioNet. https://doi.org/10.13026/jsn5-t979. Additionally, please cite the original publication:

[2] Johnson AE, Pollard TJ, Berkowitz S, Greenbaum NR, Lungren MP, Deng CY, Mark RG, Horng S. MIMIC-CXR: A large publicly available database of labeled chest radiographs. arXiv preprint arXiv:1901.07042. 2019 Jan 21.

[3] Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220