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Proceedings Paper

Assessment of toxin-induced airway injury and therapeutic effects in a rat model by optical coherence tomography
Author(s): Ryan Cheung; Yusi Miao; Andy Choi; Carl W. White; Matthew Brenner; Zhongping Chen
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Paper Abstract

In recent years, the use of convolutional neural networks has been rapidly increasing in computer vision related tasks, thanks to its versatility and flexibility in its ability to be trained with large swaths of data. In the biomedical field, neural networks have great potential to streamline and perform tasks on the level of human ability without the drawbacks of human error potentially tainting the results. This study evaluates the efficiency and accuracy of a trained neural network in segmenting the trachea of rats before and after exposure to methyl isocyanate (MIC) and a drug candidate, nitro-oleic acid (NO2OA) . The images of the trachea were gathered using optical coherence tomography. The neural network was modeled after the U-net convolutional network model for biomedical image segmentation. Accuracy was evaluated by taking cross-sectional areas of the trachea and using the Sørensen-Dice similarity coefficient comparing the neural network’s prediction of segmentation to manual segmentation of the trachea. The trained neural network showed an accuracy similar, but not perfect, to human analysis of the trachea.

Paper Details

Date Published: 6 March 2020
PDF: 6 pages
Proc. SPIE 11213, Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2020, 112130G (6 March 2020); doi: 10.1117/12.2546356
Show Author Affiliations
Ryan Cheung, Univ. of California, Irvine (United States)
Yusi Miao, Univ. of California, Irvine (United States)
Andy Choi, Univ. of California, Irvine (United States)
Carl W. White, Univ. of Colorado Denver (United States)
Matthew Brenner, Beckman Laser Institute (United States)
Zhongping Chen, Univ. of California, Irvine (United States)


Published in SPIE Proceedings Vol. 11213:
Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2020
Brian J. F. Wong M.D.; Justus F. Ilgner M.D., Editor(s)

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