视网膜
人工智能
分割
眼底(子宫)
计算机科学
计算机视觉
特征提取
模式识别(心理学)
图像分割
眼科
医学
作者
Tao Deng,Yi Huang,Junfeng Zhang
出处
期刊:Communications in computer and information science
日期:2022-01-01
卷期号:: 271-281
被引量:1
标识
DOI:10.1007/978-981-19-1253-5_20
摘要
Imaging is increasingly used for the diagnosis of retinal normality and the monitoring of retinal abnormalities. Many retinal vessel properties, such as small artery aneurysms, narrowing of incisions, etc., are related to systemic diseases. The morphology of retinal blood vessels themselves is related to cardiovascular disease and coronary artery disease in adults. The fundus image can intuitively reflect the retinal vessel lesions, and the computer-based image processing method can be used for auxiliary medical diagnosis. In this paper, a retinal vessel segmentation model, named as MLFF, is proposed to effectively extract and fuse multiple low-level features. Firstly, there are 25 low-level feature maps of fundus retinal vessel images that are analyzed and extracted. Then, the feature maps are fused by an AdaBoost classifier. Finally, the MLFF is trained and evaluated on public fundus images for vessel extraction dataset (DRIVE). The qualitative and quantitative experimental results show that our model can effectively detect the retinal vessels and outperforms other models including deep learning-based models.
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