Development of a Fundus Image-Based Deep Learning Diagnostic Tool for Various Retinal Diseases
- Abstract
- Artificial intelligence (AI)-based diagnostic tools have been accepted in ophthalmology. The use of retinal images, such as fundus photographs, is a promising approach for the development of AI-based diagnostic platforms. Retinal pathologies usually occur in a broad spectrum of eye diseases, including neovascular or dry age-related macular degeneration, epiretinal membrane, rhegmatogenous retinal detachment, retinitis pigmentosa, macular hole, retinal vein occlusions, and diabetic retinopathy. Here, we report a fundus image-based AI model for differential diagnosis of retinal diseases. We classified retinal images with three convolutional neural network models: ResNet50, VGG19, and Inception v3. Furthermore, the performance of several dense (fully connected) layers was compared. The prediction accuracy for diagnosis of nine classes of eight retinal diseases and normal control was 87.42% in the ResNet50 model, which added a dense layer with 128 nodes. Furthermore, our AI tool augments ophthalmologist's performance in the diagnosis of retinal disease. These results suggested that the fundus image-based AI tool is applicable for the medical diagnosis process of retinal diseases.
- Author(s)
- 김경민; 허태영; 김애슬; 김주희; 한규진; 윤재석; 민정기
- Issued Date
- 2021
- Type
- Article
- Keyword
- artificial intelligence; class activation map; convolutional neural network; fundus photograph; retinal diseases
- DOI
- 10.3390/jpm11050321
- URI
- https://oak.ulsan.ac.kr/handle/2021.oak/7652
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_doaj_primary_oai_doaj_org_article_92a804e4c87d4b6e890c147c11d5c5fc&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,Development%20of%20a%20Fundus%20Image-Based%20Deep%20Learning%20Diagnostic%20Tool%20for%20Various%20Retinal%20Diseases&offset=0&pcAvailability=true
- Publisher
- JOURNAL OF PERSONALIZED MEDICINE
- Location
- 스위스
- Language
- 영어
- ISSN
- 2075-4426
- Citation Volume
- 11
- Citation Number
- 5
- Citation Start Page
- 0
- Citation End Page
- 0
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- Medicine > Medicine
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