In order to discuss the segmentation effect of the magnetic resonance angiography (MRA) image segmentation algorithm based on the fuzzy clustering algorithm and DR-CV model and the prognostic value of glomerular filtration rate (GFR) in the ischemic cerebrovascular disease (ICVD), a total of 178 patients who were admitted to the hospital and received MRA due to ICVD were selected as the research objects of this study. Blood vessel segmentation was performed on the MRA image by fuzzy clustering algorithm and DR-CV model, and all patients were divided into a control group (group A), a single-vessel stenosis group (group B), a two-vessel stenosis group (group C), and a multiple-vessel stenosis group (group D). The GFR was estimated by using the dietary modification equation for kidney disease, and the correlation between GFR and the severity of arterial stenosis in patients with ICVD was analyzed. It was found that the results of the Dice similarity index (DSI) of the MRA image blood vessel segmentation algorithm based on the fuzzy clustering algorithm and the integrated model of boundary and regional information (DR-CV model) were all above 85%. The age and GFR values of the four groups of patients were significantly different ( < 0.05). The proportions of patients in groups C and D in the group with low DFR were significantly different from those in groups A and B ( < 0.01); the proportions of patients in groups A and B in the high-level GFR group had extremely significant differences compared with group D ( < 0.01). Age, GFR, total cholesterol (TC), and high-density lipoprotein-C (HDL-C) were correlated with the degree of arterial stenosis ( < 0.05). It showed that the segmentation effect of MRA image blood vessel segmentation algorithm based on the fuzzy clustering algorithm and DR-CV model was better, and the GFR level can be used as an independent risk factor for the ICVD.

中文翻译：

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磁共振血管造影图像分割算法下缺血性脑血管病肾小球滤过率分析

为探讨基于模糊聚类算法和 DR-CV 模型的磁共振血管造影 (MRA) 图像分割算法的分割效果以及肾小球滤过率 (GFR) 在缺血性脑血管病 (ICVD) 中的预后价值，采用共178例因ICVD入院并接受MRA的患者作为本研究的研究对象。通过模糊聚类算法和DR-CV模型对MRA图像进行血管分割，将所有患者分为对照组（A组）、单支血管狭窄组（B组）、两支血管狭窄组（C组）和多支血管狭窄组（D组）。GFR 是通过使用肾脏疾病的饮食调整方程来估计的，分析GFR与ICVD患者动脉狭窄程度的相关性。发现基于模糊聚类算法和边界与区域信息集成模型（DR-CV模型）的MRA图像血管分割算法的Dice相似指数（DSI）结果均在85%以上。四组患者的年龄和GFR值有显着差异（ < 0.05)。低DFR组C、D组患者比例与A、B组有显着差异（ < 0.01）；高水平 GFR 组 A、B 组患者比例与 D 组比较差异极显着（ < 0.01）。年龄、GFR、总胆固醇（TC）和高密度脂蛋白-C（HDL-C）与动脉狭窄程度相关（ <0.05）。表明基于模糊聚类算法和DR-CV模型的MRA图像血管分割算法分割效果较好，GFR水平可作为ICVD的独立危险因素。