Retinal vessel segmentation using convolutional neural networks
Retinal vessel segmentation using convolutional neural networks
复制标题
使用卷积神经网络进行视网膜血管分割
DOI：
10.1109/siu.2018.8404262
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
ilkay Ulusoy
中科院分区：
文献类型：
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作者：
Mehmet Sefik Guleryuz;ilkay Ulusoy
视网膜血管的分割和提取与血管相关的弯曲度、宽度、长度等特征可以用于早产儿视网膜病变、高血压、糖尿病等疾病的诊断、治疗和筛查。因此，通过计算机自动分割血管将使这些疾病的分析更容易，并将有助于在筛查，诊断和治疗过程中。在这项研究中，提出了一种基于卷积神经网络（CNN）的解决方案，用于视网膜血管的自动分割。在DRIVE数据集上对提出的CNN模型进行了测试，取得了比文献更好的性能。
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.