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首页> 外文会议>International Conference on Engineering Technology >Detection of abnormal blood vessels in diabetic retinopathy based on brightness variations in SDOCT retinal images
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Detection of abnormal blood vessels in diabetic retinopathy based on brightness variations in SDOCT retinal images

机译：基于SDOCT视网膜图像亮度变化的糖尿病视网膜病变异常血管检测

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摘要

Diabetic retinopathy(DR) is the most common diabetic eye disease, which occurs due to damage in the blood vessels of the retina. Sometimes these vessels swell and leak fluid or even close off completely; abnormal new blood vessels grow on the surface of the retina during proliferative stage which leads to loss of vision. Spectral Domain Optical Coherence Tomography (SDOCT) is a well accepted clinical standard for diagnosing the pathological changes in optic disc and retinal layers. In this proposed work retinal layer is segmented and the abnormal blood vessels are located at the proliferative stage of DR based on brightness variations of OCT layers. Retinal Nerve Fiber layer (RNFL) thickening shows the presence of blood vessels and shadows at the boundary of retinal pigment epithelium (RPE) layer shows the location of the blood vessels. To segment the abnormal blood vessels in the SDOCT retinal images MATLAB? software image processing tool is used.
机译：糖尿病视网膜病变（DR）是最常见的糖尿病眼病，由于视网膜的血管损伤而发生。有时这些血管膨胀并泄漏液体甚至完全关闭;在增殖阶段期间，在视网膜的表面上生长异常新血管，导致视力丧失。光谱域光学相干断层扫描（SDOCT）是可接受的临床标准，用于诊断光盘和视网膜层中的病理变化。在该提出的工作视网膜层中，分段，异常血管基于10元层的亮度变化位于DR的增殖阶段。视网膜神经纤维层（RNFL）增厚表明，视网膜颜料上皮（RPE）层的边界处存在血管和阴影，显示出血管的位置。在SDOCT视网膜图像MATLAB中分割异常血管？使用软件图像处理工具。

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