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Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images
- Source :
- Journal of Ophthalmology, Journal of Ophthalmology, Vol 2019 (2019)
- Publication Year :
- 2019
-
Abstract
- Purpose. Although optical coherence tomography (OCT) is essential for ophthalmologists, reading of findings requires expertise. The purpose of this study is to test deep learning with image augmentation for automated detection of chorioretinal diseases. Methods. A retina specialist diagnosed 1,200 OCT images. The diagnoses involved normal eyes (n=570) and those with wet age-related macular degeneration (AMD) (n=136), diabetic retinopathy (DR) (n=104), epiretinal membranes (ERMs) (n=90), and another 19 diseases. Among them, 1,100 images were used for deep learning training, augmented to 59,400 by horizontal flipping, rotation, and translation. The remaining 100 images were used to evaluate the trained convolutional neural network (CNN) model. Results. Automated disease detection showed that the first candidate disease corresponded to the doctor’s decision in 83 (83%) images and the second candidate disease in seven (7%) images. The precision and recall of the CNN model were 0.85 and 0.97 for normal eyes, 1.00 and 0.77 for wet AMD, 0.78 and 1.00 for DR, and 0.75 and 0.75 for ERMs, respectively. Some of rare diseases such as Vogt–Koyanagi–Harada disease were correctly detected by image augmentation in the CNN training. Conclusion. Automated detection of macular diseases from OCT images might be feasible using the CNN model. Image augmentation might be effective to compensate for a small image number for training.
- Subjects :
- Article Subject
medicine.diagnostic_test
Disease detection
genetic structures
business.industry
Deep learning
Diabetic retinopathy
Macular degeneration
medicine.disease
Convolutional neural network
eye diseases
Ophthalmology
lcsh:Ophthalmology
Optical coherence tomography
lcsh:RE1-994
medicine
Computer vision
Artificial intelligence
sense organs
Medical diagnosis
business
Precision and recall
Research Article
Subjects
Details
- ISSN :
- 2090004X
- Volume :
- 2019
- Database :
- OpenAIRE
- Journal :
- Journal of ophthalmology
- Accession number :
- edsair.doi.dedup.....32e9520e9d457ebe271b2b0e314fa18a