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本文引用的文献

1
Characterization of human retinal vessel arborisation in normal and amblyopic eyes using multifractal analysis.利用多重分形分析对正常眼和弱视眼的人视网膜血管分支进行特征描述。
Int J Ophthalmol. 2015 Oct 18;8(5):996-1002. doi: 10.3980/j.issn.2222-3959.2015.05.26. eCollection 2015.
2
Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis.使用分形分析对人类非增殖性糖尿病视网膜病变进行特征描述。
Int J Ophthalmol. 2015 Aug 18;8(4):770-6. doi: 10.3980/j.issn.2222-3959.2015.04.23. eCollection 2015.
3
The influence of the retinal blood vessels segmentation algoritm on the monofractal.视网膜血管分割算法对单分形的影响。
Oftalmologia. 2012;56(3):73-83.
4
Associations between retinal microvascular changes and dementia, cognitive functioning, and brain imaging abnormalities: a systematic review.视网膜微血管变化与痴呆、认知功能和脑影像学异常的关联:系统评价。
J Cereb Blood Flow Metab. 2013 Jul;33(7):983-95. doi: 10.1038/jcbfm.2013.58. Epub 2013 Apr 17.
5
Structural changes in the retinal microvasculature and renal function.视网膜微血管和肾功能的结构变化。
Invest Ophthalmol Vis Sci. 2013 Apr 26;54(4):2970-6. doi: 10.1167/iovs.13-11941.
6
Multifractal geometry in analysis and processing of digital retinal photographs for early diagnosis of human diabetic macular edema.多尺度几何在分析和处理数字视网膜照片中的应用,用于早期诊断人类糖尿病性黄斑水肿。
Curr Eye Res. 2013 Jul;38(7):781-92. doi: 10.3109/02713683.2013.779722. Epub 2013 Mar 28.
7
[Multifractal characterisation of human retinal blood vessels].[人类视网膜血管的多重分形特征]
Oftalmologia. 2012;56(2):63-71.
8
Fractal analysis of normal retinal vascular network.正常视网膜血管网络的分形分析。
Oftalmologia. 2011;55(4):11-6.
9
Blood vessel segmentation methodologies in retinal images--a survey.视网膜图像中的血管分割方法综述。
Comput Methods Programs Biomed. 2012 Oct;108(1):407-33. doi: 10.1016/j.cmpb.2012.03.009. Epub 2012 Apr 22.
10
Mathematical models of human retina.人类视网膜的数学模型。
Oftalmologia. 2011;55(3):74-81.

利用多重分形几何分析正常人视网膜血管网络结构

Analysis of normal human retinal vascular network architecture using multifractal geometry.

作者信息

Ţălu Ştefan, Stach Sebastian, Călugăru Dan Mihai, Lupaşcu Carmen Alina, Nicoară Simona Delia

机构信息

Discipline of Descriptive Geometry and Engineering Graphics, Department of AET, Faculty of Mechanical Engineering, Technical University of Cluj-Napoca, 103-105 B-dul Muncii St., Cluj-Napoca 400641, Cluj, Romania.

Department of Biomedical Computer Systems, Institute of Informatics, Faculty of Computer Science and Materials Science, University of Silesia, Będzińska 39, 41-205 Sosnowiec, Poland.

出版信息

Int J Ophthalmol. 2017 Mar 18;10(3):434-438. doi: 10.18240/ijo.2017.03.17. eCollection 2017.

DOI:10.18240/ijo.2017.03.17
PMID:28393036
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5360780/
Abstract

AIM

To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.

METHODS

Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software.

RESULTS

The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions ( ) for =0, 1, 2, the width of the multifractal spectrum ( - ) and the spectrum arms' heights difference () of the normal images were expressed as mean±standard deviation (SD): for segmented versions, =1.7014±0.0057; =1.6507±0.0058; =1.5772±0.0059; =0.92441±0.0085; = 0.1453±0.0051; for skeletonised versions, =1.6303±0.0051; =1.6012±0.0059; =1.5531±0.0058; =0.65032±0.0162; = 0.0238±0.0161. The average of generalized dimensions ( ) for =0, 1, 2, the width of the multifractal spectrum () and the spectrum arms' heights difference () of the segmented versions was slightly greater than the skeletonised versions.

CONCLUSION

The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases.

摘要

目的

应用多重分形分析方法作为一种定量手段,全面描述正常人视网膜微血管网络结构。

方法

2012年1月至2014年1月期间,罗马尼亚克卢日-纳波卡眼科诊所招募了50名志愿者参与本研究。研究了一组100张对应视网膜正常状态的分割和骨架化的人类视网膜图像。在进行多重分形分析之前,应用了一种自动无监督的视网膜血管分割方法。使用计算机算法,应用标准盒计数法对数字视网膜图像进行多重分形分析。使用GraphPad InStat软件进行统计分析。

结果

正常人视网膜微血管网络结构能够用多重分形几何来描述。正常图像在q = 0、1、2时的广义维数(Dq)平均值、多重分形谱宽度(Δf)和谱臂高度差(Δα)表示为均值±标准差(SD):对于分割版本,D0 = 1.7014±0.0057;D1 = 1.6507±0.0058;D2 = 1.5772±0.0059;Δf = 0.92441±0.0085;Δα = 0.1453±0.0051;对于骨架化版本,D0 = 1.6303±0.0051;D1 = 1.6012±0.0059;D2 = 1.5531±0.0058;Δf = 0.65032±0.0162;Δα = 0.0238±0.0161。分割版本在q = 0、1、2时的广义维数(Dq)平均值、多重分形谱宽度(Δf)和谱臂高度差(Δα)略大于骨架化版本。

结论

眼底照片的多重分形分析可作为评估视网膜微血管复杂三维结构的定量参数,作为早期检测与视网膜疾病相关拓扑变化的潜在标志物。