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Deep-learning approach for automated thickness measurement of epithelial tissue and scab using optical coherence tomography.
Ji, Yubo; Yang, Shufan; Zhou, Kanheng; Rocliffe, Holly R; Pellicoro, Antonella; Cash, Jenna L; Wang, Ruikang; Li, Chunhui; Huang, Zhihong.
Affiliation
  • Ji Y; University of Dundee, School of Science and Engineering, Dundee, United Kingdom.
  • Yang S; Edinburgh Napier University, School of Computing, Edinburgh, United Kingdom.
  • Zhou K; University of Glasgow, Center of Medical and Industrial Ultrasonics, Glasgow, United Kingdom.
  • Rocliffe HR; University of Dundee, School of Science and Engineering, Dundee, United Kingdom.
  • Pellicoro A; The University of Edinburgh, The Queen's Medical Research Institute, MRC Centre for Inflammation Res, United Kingdom.
  • Cash JL; The University of Edinburgh, The Queen's Medical Research Institute, MRC Centre for Inflammation Res, United Kingdom.
  • Wang R; The University of Edinburgh, The Queen's Medical Research Institute, MRC Centre for Inflammation Res, United Kingdom.
  • Li C; University of Washington, Department of Bioengineering, Seattle, Washington, United States.
  • Huang Z; University of Dundee, School of Science and Engineering, Dundee, United Kingdom.
J Biomed Opt ; 27(1)2022 01.
Article in En | MEDLINE | ID: mdl-35043611
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tomography, Optical Coherence / Deep Learning Type of study: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: J Biomed Opt Journal subject: ENGENHARIA BIOMEDICA / OFTALMOLOGIA Year: 2022 Document type: Article Affiliation country: Reino Unido Country of publication: Estados Unidos
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tomography, Optical Coherence / Deep Learning Type of study: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: J Biomed Opt Journal subject: ENGENHARIA BIOMEDICA / OFTALMOLOGIA Year: 2022 Document type: Article Affiliation country: Reino Unido Country of publication: Estados Unidos