Name | DL | Torrents | Total Size | Joe's Recommended Mirror List [edit] | 233 | 8.28TB | 2303 | 0 | Medical [edit] | 87 | 2.20TB | 863 | 0 | Optical Coherence Tomography [edit] | 1 | 5.79GB | 10 | 0 |
OCT2017.tar.gz | 5.79GB |
Type: Dataset
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Bibtex:
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Bibtex:
@article{, title= {Labeled Optical Coherence Tomography (OCT)}, keywords= {}, author= {}, abstract= {Dataset of validated OCT images described and analyzed in "Deep learning-based classification and referral of treatable human diseases". The OCT Images are split into a training set and a testing set of independent patients. OCT Images are labeled as (disease)-(randomized patient ID)-(image number by this patient) and split into 4 directories: CNV, DME, DRUSEN, and NORMAL. ``` 250 files in directory ./test/CNV 250 files in directory ./test/DME 250 files in directory ./test/DRUSEN 250 files in directory ./test/NORMAL 37205 files in directory ./train/CNV 11348 files in directory ./train/DME 8616 files in directory ./train/DRUSEN 26315 files in directory ./train/NORMAL ``` https://i.imgur.com/tsAGf0V.png ## Acknowledgements Data: https://data.mendeley.com/datasets/rscbjbr9sj/2 License: CC BY 4.0 ## Citation: 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. http://www.cell.com/cell/fulltext/S0092-8674(18)30154-5}, terms= {}, license= {CC BY 4.0}, superseded= {}, url= {https://data.mendeley.com/datasets/rscbjbr9sj/3} }