Retinal Vessel Segmentation Using Convolutional Neural Networks

被引：0

作者：

Guleryuz, Mehmet Sefik ^{[1
]}

Ulusoy, Ilkay ^{[1
]}

机构：

[1] Orta Dogu Tekn Univ, Elekt Elekt Muhendisligi Bolumu, Ankara, Turkey

来源：

2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2018年

关键词：

retina; vessels; segmentation; convolutional neural networks; deep learning; BLOOD-VESSELS; IMAGES; MODEL;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Retinal vessel segmentation and extracting features such as tortuosity, width, length related to those vessels can be used in diagnosis, treatment and screening of many diseases such as retinopathy of prematurity, hypertension and diabetes. Therefore, automatic segmentation of vessels by computers will make the analysis of those diseases easier and will help during the screening, diagnosis and treatment processes. In this study, a solution based on convolutional neural networks (CNN) is proposed for automatic segmentation of retinal vessels. The proposed CNN model is tested on DRIVE dataset and a better performance than literature is achieved.

引用

页数：4

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