Otoscopy is an important procedure for the diagnosis of otitis media allowing examiners to visually inspect a patient's eardrum. However, a traditional otoscope enables imaging of the target under white light only, limiting the capability to assess color differences and tympanum morphology, which are distinguishing features in the diagnosis of otitis media. We present a smartphone-attachable trimodal otoscope head capable of spectral, autofluorescence, and photometric 3D stereo imaging. This device uses LEDs, optical fibers, and a smartphone camera to collect quantitative spectral signatures and qualitative morphological data that carry information about the biochemistry and 3D morphology of the sampled eardrum and middle ear to aid examiners in providing precise diagnosis with ubiquitous connectivity and portability of a smartphone device, which is beneficial in telemedicine applications. Finally, we collected normal, otitis media with effusion, and adhesive otitis media data and evaluated our device’s capabilities using deep-learning classifiers.
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