Automated classification of otitis media in pediatric OCT images: Augmenting with gold-standard animal model data

Guillermo L. Monroy; Jungeun Won; Jungeun Won; Darold Spillman; Stephen A. Boppart; Stephen A. Boppart; Stephen A. Boppart; Stephen A. Boppart

doi:10.1364/OMP.2021.OF2E.5

Biophotonics Congress 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper OF2E.5
•https://doi.org/10.1364/OMP.2021.OF2E.5

Automated classification of otitis media in pediatric OCT images: Augmenting with gold-standard animal model data

Guillermo L. Monroy, Jungeun Won, Darold Spillman, and Stephen A. Boppart

Optical Molecular Probes, Imaging and Drug Delivery 2021

Washington, DC United States
12–16 April 2021
ISBN: 978-1-943580-85-9

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Tissue Morphology (OF2E)

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G. L. Monroy, J. Won, D. Spillman, and S. A. Boppart, "Automated classification of otitis media in pediatric OCT images: Augmenting with gold-standard animal model data," in Biophotonics Congress 2021, C. Boudoux, K. Maitland, C. Hendon, M. Wojtkowski, K. Quinn, M. Schanne-Klein, N. Durr, D. Elson, F. Cichos, L. Oddershede, V. Emiliani, O. Maragò, S. Nic Chormaic, N. Pégard, S. Gibbs, S. Vinogradov, M. Niedre, K. Samkoe, A. Devor, D. Peterka, P. Blinder, and E. Buckley, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper OF2E.5.

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Abstract

Specific disease states are often difficult to observe in a clinical setting. Here we demonstrate OCT images from chinchilla ears can supplement existing human data in a machine learning platform to produce diagnostically relevant conclusions.

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