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Proceedings Paper

Automatic airway wall segmentation and thickness measurement for long-range optical coherence tomography images
Author(s): Li Qi; Shenghai Huang; Andrew E. Heidari; Cuixia Dai; Jiang Zhu; Xuping Zhang; Zhongping Chen
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Paper 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.

Paper Details

Date Published: 8 March 2016
PDF: 7 pages
Proc. SPIE 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX, 96973B (8 March 2016); doi: 10.1117/12.2214605
Show Author Affiliations
Li Qi, Beckman Laser Institute and Medical Clinic (United States)
Nanjing Univ. (China)
Shenghai Huang, Beckman Laser Institute and Medical Clinic (United States)
Andrew E. Heidari, Beckman Laser Institute and Medical Clinic (United States)
Cuixia Dai, Beckman Laser Institute and Medical Clinic (United States)
Jiang Zhu, Beckman Laser Institute and Medical Clinic (United States)
Xuping Zhang, Nanjing Univ. (China)
Zhongping Chen, Beckman Laser Institute and Medical Clinic (United States)
Univ. of California, Irvine (United States)


Published in SPIE Proceedings Vol. 9697:
Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX
Joseph A. Izatt; James G. Fujimoto; Valery V. Tuchin, Editor(s)

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