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LUMID: Large-scale Unlabled Medical Imaging Dataset for Unsupervised and Self-supervised Learning
| Description: | LUMID is a large-scale, unlabeled collection of over 2 million medical images spanning multiple imaging modalities, including CT scans, X-rays, MRIs, and more. This dataset has been meticulously curated from publicly available medical imaging repositories, addressing the critical challenge of limited scale in existing public datasets and the inaccessibility of high-quality private datasets. The primary motivation behind creating this dataset is to empower the medical imaging community with a resource suited for developing and training advanced deep learning models. By enabling the use of unsupervised and self-supervised learning approaches, this dataset facilitates the learning of rich, transferable representations that can significantly enhance performance across various medical imaging tasks, including classification, segmentation, and anomaly detection. Key Features: 1) Diversity: Comprising images from multiple modalities and a wide range of medical imaging scenarios. 2) Scalability: A dataset of unprecedented size, providing a robust foundation for training deep neural networks. 3) Versatility: Specifically designed for unsupervised and self-supervised learning methods, fostering innovation in representation learning for medical imaging. 4) Open Access: Built entirely from public datasets, ensuring transparency and reproducibility. This dataset is intended to serve as a cornerstone for advancing research in medical AI, fostering the development of models capable of generalizing across diverse imaging types and clinical conditions. |
| Authors: | Osman, Islam; University of British Columbia;  0000-0001-9935-2417Gupta, Anubhav; University of British Columbia Shehata, Mohamed S.; University of British Columbia Braun, John W.; University of British Columbia |
| Keywords: | Medical imaging CT MRI X-rays |
| Field of Research: | Computer and information sciences > Artificial intelligence (AI) > Computer vision in artificial intelligence
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| Publication Date: | 2024-12-04 |
| Publisher: | Federated Research Data Repository / dépôt fédéré de données de recherche |
| URI: | https://doi.org/10.20383/103.01017 |
| Related Identifiers: |
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This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
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Access to this dataset is subject to the following terms:
Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Citation
Osman, I., Gupta, A., Shehata, M., Braun, J. (2024). LUMID: Large-scale Unlabled Medical Imaging Dataset for Unsupervised and Self-supervised Learning. Federated Research Data Repository. https://doi.org/10.20383/103.01017
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