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

Optics Express
Li QiZhongping Chen

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.

References

Nov 11, 1991·The Journal of Trauma·G B HubbardB A Pruitt
Oct 1, 1988·Burns, Including Thermal Injury·D L TraberT Prien
Apr 8, 1995·Journal of Intensive Care Medicine·B A Pruitt, W G Cioffi
Aug 26, 2003·American Journal of Respiratory Cell and Molecular Biology·Robert A CoxHal K Hawkins
Aug 1, 1952·Proceedings of the National Academy of Sciences of the United States of America·R Bellman
Mar 7, 2008·The Laryngoscope·James Matthew RidgwayBrian Wong
Dec 12, 2012·Journal of Biomedical Optics·Joseph JingZhongping Chen
May 16, 2014·Journal of Biomedical Optics·Yongzhao DuZhongping Chen

❮ Previous
Next ❯

Citations

Mar 2, 2016·Journal of Biomedical Optics·Yu GanChristine P Hendon
Jun 28, 2019·The Journal of Trauma and Acute Care Surgery·Yusi MiaoZhongping Chen
Jan 27, 2019·Lasers in Surgery and Medicine·Tiffany T PhamBrian J F Wong
Nov 22, 2019·Applied Spectroscopy Reviews·Jiang ZhuZhongping Chen
Feb 26, 2019·Biomedical Optics Express·Li QiWufan Chen

❮ Previous
Next ❯

Related Concepts

Related Feeds

Cell Imaging in CNS

Here is the latest research on cell imaging and imaging modalities, including light-sheet microscopy, in the central nervous system.