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视网膜微血管形态的分形分析与人口统计学和诊断参数的关系。

Relationship of fractal analysis in retinal microvascularity with demographic and diagnostic parameters.

机构信息

Anna University, Chennai, India.

Anna University, Chennai, India.

出版信息

Microvasc Res. 2022 Jan;139:104237. doi: 10.1016/j.mvr.2021.104237. Epub 2021 Sep 3.

Abstract

Problems and diseases with eye are common in diabetic patients. Early diagnosis and detection of various diseases like retinopathy, neuropathy and nephropathy is crucial in diabetic patients. Certain demographic and diagnostic parameters play a significant role in predicting diseases related to diabetes. Development of a novel diagnostic method which helps to predict the disease by establishing a significant correlation with the demographic and diagnostic parameters is of prime importance. This study proposes a new methodology in which retinal fractals are obtained for the images and the derived retinal fractals are analysed to aid in disease prediction. This study comprises of images from patients with retinopathy, non retinopathy, neuropathy, nephropathy and hypertension. The proposed research is carried out in two aspects: 1) to correlate the retinal fractals of retinopathy and non retinopathy images with certain demographic and diagnostic parameters and interpret its significance, and 2) to exhibit a relationship between the retinal fractals and various diseases/addictive habit to facilitate the prediction of the disease/addictive habit. Hausdorff fractal dimension (HFD) was applied and higher fractal dimension was obtained for healthy cases. Then using Statistical Package for the Social Sciences (SPSS) various statistical parameters and significance were calculated to analyse the relationship. Analysis results showed that fractal value helped in distinguishing between the retinopathy and non retinopathy conditions. It also helped in diagnosing the presence and absence of hypertension. Correlation analysis between certain demographic parameters and fractal value showed a positive correlation whereas few exhibited negative correlation.

摘要

糖尿病患者常出现眼部问题和疾病。早期诊断和检测各种疾病,如视网膜病变、神经病变和肾病,对糖尿病患者至关重要。某些人口统计学和诊断参数在预测与糖尿病相关的疾病方面起着重要作用。开发一种新的诊断方法,通过与人口统计学和诊断参数建立显著相关性来帮助预测疾病,这一点非常重要。本研究提出了一种新的方法,该方法获取视网膜图像的分形,并分析所得的视网膜分形,以帮助进行疾病预测。本研究包括来自患有视网膜病变、非视网膜病变、神经病变、肾病和高血压的患者的图像。该研究从两个方面进行:1)将视网膜病变和非视网膜病变图像的视网膜分形与某些人口统计学和诊断参数相关联,并解释其意义;2)展示视网膜分形与各种疾病/成瘾习惯之间的关系,以促进疾病/成瘾习惯的预测。应用豪斯多夫分形维数(HFD),并为健康病例获得更高的分形维数。然后使用社会科学统计软件包(SPSS)计算各种统计参数和显著性,以分析关系。分析结果表明,分形值有助于区分视网膜病变和非视网膜病变情况。它还有助于诊断高血压的存在和不存在。某些人口统计学参数与分形值之间的相关分析显示出正相关,而少数则表现出负相关。

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