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Detection of neovascularisation using K-means clustering through registration of peripapillary OCT and fundus retinal images

机译:通过普普宫崎和眼底图像的登记使用K-Means聚类检测新生血管分析

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This paper focuses on quantitatively assessing the presence of neovascularization by registration of peripapillary Optical Coherence Tomography (OCT) and fundus images of Diabetic Retinopathy patients. Here in this present work, the two intra-patient images acquired by spectral domain OCT modality and fundus camera are enhanced and the blood vessels are extracted using kirsch template. Then the two images are fused by similarity measure based registration. The automatic algorithm for extraction of neovascularization features using k-means clustering is proposed to quantify and detect normal and abnormal blood vessels. Results shows that the proposed method produces accurate results for all the input real time sample images and the results are validated with experts clinical findings.
机译:本文侧重于定量评估通过登记围毛绒光学相干断层扫描(OCT)和糖尿病视网膜病变患者的眼底图像的新血管化的存在。在此,在本作中,增强了由光谱域OCT模态和眼底照相机获取的两个患有患者内部图像,并且使用Kirsch模板提取血管。然后通过基于相似度量的登记融合这两个图像。提出了使用K-Means聚类提取新血管形成特征的自动算法,以量化和检测正常和异常血管。结果表明,该方法为所有输入实时样本图像产生了准确的结果,结果与专家临床调查结果验证。

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