Aufsatz(elektronisch)28. Oktober 2019
Semantic Segmentation of Eye Fundus Images Using Convolutional Neural Networks; Akies dugno nuotraukų semantinis segmentavimas naudojant konvoliucinius neuroninius tinklus
In: Information & Media, Band 85, S. 135-147
Verfügbarkeit an Ihrem Standort wird überprüft
Dieser Artikel ist auch in Ihrer Bibliothek verfügbar: |
elektronisch
gedruckt
Abstract
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.
Problem melden