Algorithm to quantify nuclear features and confidence intervals for classification of oral neoplasia from high-resolution optical images

Purpose: In vivo optical imaging technologies like high-resolution microendoscopy (HRME) can image nuclei of the oral epithelium. In principle, automated algorithms can then calculate nuclear features to distinguish neoplastic from benign tissue. However, images frequently contain regions without vi...

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Detalles Bibliográficos
Autores principales: Yang, Eric C., Brenes, David R., Vohra, Imran S., Schwarz, Richard A., Williams, Michelle D., Vigneswaran, Nadarajah, Gillenwater, Ann M., Richards-Kortum, Rebecca R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2020
Materias:
Computer-Aided Diagnosis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503985/
https://www.ncbi.nlm.nih.gov/pubmed/32999894
http://dx.doi.org/10.1117/1.JMI.7.5.054502

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503985/
https://www.ncbi.nlm.nih.gov/pubmed/32999894
http://dx.doi.org/10.1117/1.JMI.7.5.054502

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