Large Dataset of Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images

Published: 1 Jun 2018 | Version 3 | DOI: 10.17632/rscbjbr9sj.3
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Description of this data

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This dataset contains thousands of validated OCT and Chest X-Ray images described and analyzed in "Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning". The images are split into a training set and a testing set of independent patients. Images are labeled as (disease)-(randomized patient ID)-(image number by this patient) and split into 4 directories: CNV, DME, DRUSEN, and NORMAL.

This repository of images is made available for use in research only.
How to cite this data:
Kermany D, Goldbaum M, Cai W et al. Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning. Cell. 2018; 172(5):1122-1131. doi:10.1016/j.cell.2018.02.010.

Experiment data files

Steps to reproduce

Instructions found in README

Related links

This data is associated with the following publication:

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

Published in: Cell

Latest version

  • Version 3

    2018-06-01

    Published: 2018-06-01

    DOI: 10.17632/rscbjbr9sj.3

    Cite this dataset

    Kermany, Daniel; Zhang, Kang; Goldbaum, Michael (2018), “Large Dataset of Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images”, Mendeley Data, v3 http://dx.doi.org/10.17632/rscbjbr9sj.3

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Institutions

University of California San Diego, Guangzhou Women and Children's Medical Center

Categories

Applied Sciences, Medicine, Ophthalmology, Retina, Deep Learning

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?

This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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