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徐军, 陈强, 牛四杰. 青光眼视神经头参数与视网膜神经纤维层的相关性分析[J]. 计算机辅助设计与图形学学报, 2017, 29(6): 977-983.
引用本文: 徐军, 陈强, 牛四杰. 青光眼视神经头参数与视网膜神经纤维层的相关性分析[J]. 计算机辅助设计与图形学学报, 2017, 29(6): 977-983.
Xu Jun, Chen Qiang, Niu Sijie. Correlation between Optic Nerve Head Parameters and Retinal Nerve Fiber Layer in Glaucoma[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(6): 977-983.
Citation: Xu Jun, Chen Qiang, Niu Sijie. Correlation between Optic Nerve Head Parameters and Retinal Nerve Fiber Layer in Glaucoma[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(6): 977-983.

青光眼视神经头参数与视网膜神经纤维层的相关性分析

Correlation between Optic Nerve Head Parameters and Retinal Nerve Fiber Layer in Glaucoma

  • 摘要: 青光眼是一种以视神经萎缩和视野缺损为共同特征的视网膜疾病,是导致人类失明的第二大视网膜疾病.青光眼的早期症状不明显,因此对早期青光眼的筛选和诊断将会阻止青光眼的进一步发展.文中提出一种评估青光眼发病机制的算法,首先利用随机森林分割视网膜神经纤维层,然后利用块搜索算法分割视盘与视杯,最后分析两者相关性.实验结果表明,视网膜神经纤维层与垂直杯盘比,视杯面积以及沿盘面积比的相关性大小为0.64,0.62和0.54,验证了在诊断青光眼方面计算视网膜神经纤维层厚度与杯盘比大小是密切相关和互补的,对研究青光眼的发展趋势具有重要意义.

     

    Abstract: Glaucoma is a kind of retinal diseases with the feature of optic nerve atrophy and visual field defect, which is the second foremost reason of blindness. Early glaucoma is not obvious, so the screening and diagnosis of early glaucoma will prevent further development of glaucoma. In this paper, we propose a method to evaluate the pathogenesis of glaucoma that can be divided into three parts:the first is using random forest to segment the retinal nerve fiber layer; the second is using patch searching to segment disk and cup; and the third is calculating the relationship of retinal nerve fiber layer(RNFL) thickness and cup-to-disk ratio(CDR). Experimental results demonstrate that the correlations of the thickness of RNFL with vertical CDR, cup area and rim disk ratio are 0.64, 0.62, 0.54, respectively, which conforms that RNFL thickness and CDR are highly relative and complementary for the glaucoma diagnose. It plays an important role in the study on the development of glaucoma.

     

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