| Title |
Akies dugno nuotraukų semantinis segmentavimas naudojant konvoliucinius neuroninius tinklus / |
| Translation of Title |
Semantic segmentation of eye fundus images using convolutional neural networks. |
| Authors |
Toliušis, Ričardas ; Kurasova, Olga ; Bernatavičienė, Jolita |
| DOI |
10.15388/Im.2019.85.20 |
| Full Text |
|
| Is Part of |
Informacijos mokslai.. Vilnius : Vilniaus universiteto leidykla. 2019, t. 85, p. 135-147.. ISSN 1392-0561. eISSN 1392-1487 |
| Keywords [eng] |
U-Net ; deep learning ; artificial neural networks ; semantic segmentation ; eye fundus |
| Abstract [eng] |
This article reviews the problems of eye bottom fundus analysis and semantic segmentation algorithms used to distinguish the eye vessels and the optical disk. Various diseases, such as glaucoma, hypertension, diabetic retinopathy, macular degeneration, etc., can be diagnosed through changes and anomalies of the vesssels and optical disk. Convolutional neural networks, especially the U-Net architecture, are well-suited for semantic segmentation. A number of U-Net modifications have been recently developed that deliver excellent performance results. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Journal article |
| Language |
Lithuanian |
| Publication date |
2019 |
| CC license |
|
