Using a Deep Learning System That Classifies Hypertensive Retinopathy Based on the Fundus Images of Patients of Wide Age
Yazarlar (4)
Süleyman Burçin Şüyun Selçuk Üniversitesi, Türkiye
Prof. Dr. Şakir TAŞDEMİR Selçuk Üniversitesi, Türkiye
Serkan Biliş
Selçuk Üniversitesi, Türkiye
Selçuk Üniversitesi, Türkiye
Alexandru Milea
Selçuk Üniversitesi, Türkiye
Selçuk Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Traitement Du Signal (Q3) | ||
| Dergi ISSN | 0765-0019 Dergi Bilgileri (2021) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2021 |
| Cilt / Sayı / Sayfa | 38 / 1 / 207–213 | DOI | 10.18280/TS.380122 |
| Makale Linki | http://dx.doi.org/10.18280/ts.380122 | ||
| UAK Araştırma Alanları |
Yapay Zeka
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| Özet |
| Accepted: 2 February 2021 Range throughout Turkey in this paper, the author trained the continuous neural networks, and used a total of 4,000 fundus images, including images with different degrees of fundus disorders and images without disorders, so that CNN can detect whether the patient has hypertension and arteriosclerosis according to macular degeneration in the fundus images. In order to obtain more effective results from the deep learning structure using convolutional neural network, this paper prepared more data sets on the basis of Turkey, combined with the local data sets to educate the deep learning model, so as to integrate the data globally, which can help standardize the results and improve the accuracy. The system is used to diagnose retinal vascular degeneration, such as fundus vascular disease and macular edema disease. Based on this basic understanding, the research has been used for the detection and classification of hypertensive retinopathy that has similar causes. The author also points out the limitations of the system. Among them, the most important limitation is the need for long-term financial sustainability. |
| Anahtar Kelimeler |
| Convolutional neural networks | Deep learning | Eye diseases | Fundus images | Hypertensive retinopathy | Macular degeneration |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 2 |
| Scopus | 8 |
| Google Scholar | 8 |