Automatic airway wall segmentation and thickness measurement for long-range optical coherence tomography images

被引：16
|
作者：
Qi, Li [1 ,2 ]
Huang, Shenghai [2 ]
Heidari, Andrew E. [2 ,3 ]
Dai, Cuixia [2 ]
Zhu, Jiang [2 ]
Zhang, Xuping [1 ]
Chen, Zhongping [2 ,3 ]
机构：
[1] Nanjing Univ, Inst Opt Commun Engn, Nanjing 210093, Jiangsu, Peoples R China
[2] Univ Calif Irvine, Beckman Laser Inst, Irvine, CA 92612 USA
[3] Univ Calif Irvine, Dept Biomed Engn, Irvine, CA 92697 USA
来源：
OPTICS EXPRESS | 2015年 / 23卷 / 26期
基金：
美国国家卫生研究院; 中国国家自然科学基金;
关键词：
SMOKE-INHALATION INJURY; GRAPH-THEORY;
D O I：
10.1364/OE.23.033992
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
We present an automatic segmentation method for the delineation and quantitative thickness measurement of multiple layers in endoscopic airway optical coherence tomography (OCT) images. The boundaries of the mucosa and the sub-mucosa layers are accurately extracted using a graph-theory-based dynamic programming algorithm. The algorithm was tested with sheep airway OCT images. Quantitative thicknesses of the mucosal layers are obtained automatically for smoke inhalation injury experiments. (C) 2015 Optical Society of America
引用
收藏
页码：33992 / 34006
页数：15
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