1. Automatic airway wall segmentation and thickness measurement for long-range optical coherence tomography images
- Author
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Qi, Li, Huang, Shenghai, Heidari, Andrew E, Dai, Cuixia, Zhu, Jiang, Zhang, Xuping, and Chen, Zhongping
- Subjects
Engineering ,Communications Engineering ,Electronics ,Sensors and Digital Hardware ,Physical Sciences ,Atomic ,Molecular and Optical Physics ,Bioengineering ,Biomedical Imaging ,Algorithms ,Animals ,Automation ,Disease Models ,Animal ,Endoscopy ,Image Enhancement ,Reproducibility of Results ,Respiratory Mucosa ,Respiratory System ,Sheep ,Smoke Inhalation Injury ,Tomography ,Optical Coherence ,Optical Physics ,Electrical and Electronic Engineering ,Communications Technologies ,Optics ,Communications engineering ,Electronics ,sensors and digital hardware ,Atomic ,molecular and optical physics - Abstract
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.
- Published
- 2015