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

Li Qi; Shenghai Huang; Andrew E. Heidari; Cuixia Dai; Jiang Zhu; Xuping Zhang; Zhongping Chen

doi:10.1117/12.2214605

8 March 2016 Automatic airway wall segmentation and thickness measurement for long-range optical coherence tomography images

Li Qi, Shenghai Huang, Andrew E. Heidari, Cuixia Dai, Jiang Zhu, Xuping Zhang, Zhongping Chen

Author Affiliations +

Proceedings Volume 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX; 96973B (2016) https://doi.org/10.1117/12.2214605
Event: SPIE BiOS, 2016, San Francisco, California, United States

Abstract

We present an automatic segmentation method for 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 were extracted using a graph-theory-based dynamic programming algorithm. The algorithm was tested with pig airway OCT images acquired with a custom built long range endoscopic OCT system. The performance of the algorithm was demonstrated by cross-validation between auto and manual segmentation experiments. Quantitative thicknesses changes in the mucosal layers are obtained automatically for smoke inhalation injury experiments.

Citation Download Citation

Li Qi, Shenghai Huang, Andrew E. Heidari, Cuixia Dai, Jiang Zhu, Xuping Zhang, and Zhongping Chen "Automatic airway wall segmentation and thickness measurement for long-range optical coherence tomography images", Proc. SPIE 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX, 96973B (8 March 2016); https://doi.org/10.1117/12.2214605

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