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Portable cameras and AI show promise for diabetic retinopathy screening. While smartphone cameras had lower image quality and AI performance, smartscopes offered better results for detecting diabetic retinopathy.

Keywords:
artificial intelligencediabetic retinopathyhandheld retinal cameraimage qualitypublic healthscreeningsmartphonestelemedicine

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Diabetic retinopathy (DR) screening via telemedicine is effective but limited in reach.
  • Portable cameras and AI offer potential solutions for broader diabetes population screening.

Purpose of the Study:

  • To evaluate the efficacy of smartphone and smartscope handheld cameras for DR screening.
  • To compare image quality and AI-based DR detection performance between handheld devices and OCT.

Main Methods:

  • Two handheld cameras (smartphone, smartscope) were assessed for image acquisition.
  • Images were evaluated by retina specialists and an AI algorithm for DR detection.
  • Comparison with Optical Coherence Tomography (OCT) imaging standards.

Main Results:

  • Smartphone cameras required mydriasis more often and yielded more ungradable images (27.98%) than smartscopes (7.98%).
  • AI detection of any DR showed lower recall (0.89) and F1 scores (0.89) for smartphones versus smartscopes (0.99).
  • Smartphones performed less effectively in detecting mild DR compared to smartscopes.

Conclusions:

  • Handheld devices combined with AI algorithms can aid DR screening.
  • Improvements in image acquisition, particularly with small pupils, are needed for handheld DR screening devices.