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Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images.

Publication ,  Journal Article
Yang, Z; Soltanian-Zadeh, S; Chu, KK; Zhang, H; Moussa, L; Watts, AE; Shaheen, NJ; Wax, A; Farsiu, S
Published in: Biomedical optics express
October 2021

Optical coherence tomography (OCT) is used for diagnosis of esophageal diseases such as Barrett's esophagus. Given the large volume of OCT data acquired, automated analysis is needed. Here we propose a bilateral connectivity-based neural network for in vivo human esophageal OCT layer segmentation. Our method, connectivity-based CE-Net (Bicon-CE), defines layer segmentation as a combination of pixel connectivity modeling and pixel-wise tissue classification. Bicon-CE outperformed other widely used neural networks and reduced common topological prediction issues in tissues from healthy patients and from patients with Barrett's esophagus. This is the first end-to-end learning method developed for automatic segmentation of the epithelium in in vivo human esophageal OCT images.

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Published In

Biomedical optics express

DOI

EISSN

2156-7085

ISSN

2156-7085

Publication Date

October 2021

Volume

12

Issue

10

Start / End Page

6326 / 6340

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4003 Biomedical engineering
  • 3212 Ophthalmology and optometry
  • 0912 Materials Engineering
  • 0205 Optical Physics
 

Citation

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Yang, Z., Soltanian-Zadeh, S., Chu, K. K., Zhang, H., Moussa, L., Watts, A. E., … Farsiu, S. (2021). Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images. Biomedical Optics Express, 12(10), 6326–6340. https://doi.org/10.1364/boe.434775
Yang, Ziyun, Somayyeh Soltanian-Zadeh, Kengyeh K. Chu, Haoran Zhang, Lama Moussa, Ariel E. Watts, Nicholas J. Shaheen, Adam Wax, and Sina Farsiu. “Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images.Biomedical Optics Express 12, no. 10 (October 2021): 6326–40. https://doi.org/10.1364/boe.434775.
Yang Z, Soltanian-Zadeh S, Chu KK, Zhang H, Moussa L, Watts AE, et al. Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images. Biomedical optics express. 2021 Oct;12(10):6326–40.
Yang, Ziyun, et al. “Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images.Biomedical Optics Express, vol. 12, no. 10, Oct. 2021, pp. 6326–40. Epmc, doi:10.1364/boe.434775.
Yang Z, Soltanian-Zadeh S, Chu KK, Zhang H, Moussa L, Watts AE, Shaheen NJ, Wax A, Farsiu S. Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images. Biomedical optics express. 2021 Oct;12(10):6326–6340.
Journal cover image

Published In

Biomedical optics express

DOI

EISSN

2156-7085

ISSN

2156-7085

Publication Date

October 2021

Volume

12

Issue

10

Start / End Page

6326 / 6340

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4003 Biomedical engineering
  • 3212 Ophthalmology and optometry
  • 0912 Materials Engineering
  • 0205 Optical Physics