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7 March 2022 Advanced ear examination using deep learning-assisted mobile otoscope
Sanzhar Askaruly, Hyunmo Yang, Nurbolat Aimakov, Geoseong Na, Yujin Ahn, Joon S. You, Gil-Jin Jang, Jeong Hun Jang, Woonggyu Jung
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Proceedings Volume PC11950, Optics and Biophotonics in Low-Resource Settings VIII; PC1195002 (2022) https://doi.org/10.1117/12.2608191
Event: SPIE BiOS, 2022, San Francisco, California, United States
Abstract
Digital video otoscope is an indispensable tool in otology that allows inspection of the external auditory canal and tympanic membrane. However, existing solutions have limitations in the diagnosis of various ear diseases and portability. Here, we propose a mobile, deep learning-assisted otoscope for low-resource settings. Our deep learning architecture was trained on clinical data to identify and classify various ear diseases. To evaluate our platform, we compared its performance with the device used in the hospital practice. Our preliminary results demonstrated high diagnostic accuracy indicating a strong potential to become a viable screening solution in low-resource, non-specialist settings.
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Sanzhar Askaruly, Hyunmo Yang, Nurbolat Aimakov, Geoseong Na, Yujin Ahn, Joon S. You, Gil-Jin Jang, Jeong Hun Jang, and Woonggyu Jung "Advanced ear examination using deep learning-assisted mobile otoscope", Proc. SPIE PC11950, Optics and Biophotonics in Low-Resource Settings VIII, PC1195002 (7 March 2022); https://doi.org/10.1117/12.2608191
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KEYWORDS
Ear
Diagnostics
Digital video recorders
Video
Medicine
Optical design
Visual analytics
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