Speciation of otitis media causing bacterial biofilms using texture analysis features from OCT images

Farzana R. Zaki; Kavya Sudhir; Guillermo L. Monroy; Jindou Shi; Stephen A. Boppart

doi:10.1117/12.2647878

17 March 2023 Speciation of otitis media causing bacterial biofilms using texture analysis features from OCT images

Farzana R. Zaki, Kavya Sudhir, Guillermo L. Monroy, Jindou Shi, Stephen A. Boppart

Proceedings Volume 12354, Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2023; 1235403 (2023) https://doi.org/10.1117/12.2647878
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Otitis media (OM) is a prevalent disease among children worldwide. Antibiotic-resistant bacterial biofilms can develop in the middle ear during recurrent/chronic ear infections. OCT was used to compare microstructural texture features from primary bacterial biofilms in vitro. From 1200 ROI images of each biofilm class, 934 texture features were extracted. Principle component analysis and five-fold cross-validation were performed using Support vector machines (SVMs). Currently, the model has achieved 0.97 AUC (cubic kernel function) and an average classification accuracy of 89%. Texture analysis of bacterial biofilm OCT images with SVM may enable real-time visualization and differentiation of OM-causing bacterial biofilms in vivo.

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Farzana R. Zaki, Kavya Sudhir, Guillermo L. Monroy, Jindou Shi, and Stephen A. Boppart "Speciation of otitis media causing bacterial biofilms using texture analysis features from OCT images", Proc. SPIE 12354, Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2023, 1235403 (17 March 2023); https://doi.org/10.1117/12.2647878

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KEYWORDS

Optical coherence tomography

Biological research

Ear

Image analysis

In vitro testing

Binary data

Feature extraction

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