基于自适应阈值和区域生长的SD-OCT糖网图像亮斑分割

计算机科学 ›› 2015, Vol. 42 ›› Issue (Z11): 123-125.

基于自适应阈值和区域生长的SD-OCT糖网图像亮斑分割

俞晨琛,陈强,范雯,袁松涛,刘庆淮

南京理工大学计算机科学与工程学院南京210094南京医科大学南京210029,南京理工大学计算机科学与工程学院南京210094南京医科大学南京210029,南京理工大学计算机科学与工程学院南京210094南京医科大学南京210029,南京理工大学计算机科学与工程学院南京210094南京医科大学南京210029,南京理工大学计算机科学与工程学院南京210094南京医科大学南京210029

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受中央高校基本科研业务费专项基金(30920140111004),江苏省六大人才高峰项目(2014-SWYY-024),江苏省“青蓝工程”优秀青年骨干教师项目(D040201),重点病种规范化诊疗研究(BL2014089)资助

Segmentation of Bright Speckles in SD-OCT Diabetic Retinal Images Based on Self-adaption Threshold and Region Growing

YU Chen-chen, CHEN Qiang, FAN Wen, YUAN Song-tao and LIU Qing-huai

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 硬性渗出是糖尿病性视网膜病变的一个比较显著的症状,频域光学相干断层视网膜图像中的高信号亮斑与渗出有着密切的联系。为了研究渗出与病变的关系,有必要找到一种提取亮斑的方法。但是,目前关于糖网图像亮斑提取的研究还非常少。首先运用层分割算法限制亮斑所在区域,然后采用自适应阈值法确定种子集合,最后使用基于人类视觉特性的区域生长方法提取出亮斑。实验结果表明,本方法可以较准确地分割出糖网图像中的亮斑。

关键词: 频域光学相干断层,糖网,硬性渗出,层分割,自适应阈值,区域生长

Abstract: Hard exudation is one of obvious symptoms in diabetic retinopathy.The bright speckles in SD-OCT(Spectral Domain Optical Coherence Tomography)have close relation with exudation.In order to research the relation between retinopathy and exudation,it is necessary to extract the bright speckles.However,there are few studies about the segmentation of bright speckles.In this paper,we first limited target regions by layer segmentation methods,then determined the seeds sets by self-adaption threshold and finally extracted bright speckles by region growing based on human vision feature.Experiments demonstrate that our method can accurately segment the bright speckles in diabetic retinal images.

Key words: Spectral domain optical coherence tomography,Diabetic retina,Hard exudation,Layer segmentation,Self-adaption threshold,Region growing

俞晨琛,陈强,范雯,袁松涛,刘庆淮. 基于自适应阈值和区域生长的SD-OCT糖网图像亮斑分割[J]. 计算机科学, 2015, 42(Z11): 123-125. https://doi.org/

YU Chen-chen, CHEN Qiang, FAN Wen, YUAN Song-tao and LIU Qing-huai. Segmentation of Bright Speckles in SD-OCT Diabetic Retinal Images Based on Self-adaption Threshold and Region Growing[J]. Computer Science, 2015, 42(Z11): 123-125. https://doi.org/

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