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Author: Claude (AI), from PubMed abstracts · Reviewed by: Dr Mina Abdelmseih · Reviewed: 2026-11-15 · Review due: 2027-11-15

Educational content only. Not personalised medical advice. Clinical decisions remain the responsibility of the treating clinician.

Smartphone and portable fundus imaging

Smartphone-based and handheld fundus cameras are portable, low-cost and easy to use in remote places, and images can be sent at once for remote grading [S2]. They can support screening or triage for referable diabetic retinopathy (DR), glaucoma-related disc changes and selected retinopathy of prematurity applications, with accuracy that varies by device, protocol, operator and disease [S11]. Combined with artificial intelligence (AI) and task-shifting, they are a practical route to eye screening in low-resource settings [S9].

Key points - Smartphone ophthalmoscopy detected any DR with pooled sensitivity 87% and specificity 94%, and proliferative DR with 92% and 99%, but mild non-proliferative DR with only 39% sensitivity [S1]. - Smartphone-based AI detected referable DR with pooled sensitivity 98.2% and specificity 81.2% in 6 studies (3,931 patients), four using one algorithm [S7]. - In developing countries, AI-based DR screening had pooled sensitivity 0.933 and specificity 0.903 for referable DR; portable cameras and general physicians agreed well with gold standards [S9]. - In Uganda, a smartphone adapter detected a vertical cup-to-disc ratio above 0.5 with 67.7% sensitivity and 96.7% specificity against OCT [S3]. - Image quality, field of view, data security, privacy, regulation and maintenance remain key challenges [S11].

Evidence last checked: 2026-10-17 (PubMed abstracts).

Red flags: findings on the image that need urgent action

Recognise it: device types and what they can do

Confirm it: getting a gradable, reliable image

  1. Dilate when the protocol requires it. All low-cost smartphone devices in one review used mydriatic drops [S6], and image quality in non-mydriatic eyes is a concern [S8].
  2. Train the operator. After brief training, allied health workers can acquire usable images in selected settings [S11].
  3. Check gradability. In Uganda, 138 eyes were excluded for poor image acquisition such as dense cataract [S3].
  4. Know the reference standard. Reported accuracy depends on device, protocol, operator and reference standard; no universal performance threshold exists [S11].

Manage it: running a portable imaging programme at each tier

Flowchart: dilate if required, trained operator captures image, a diamond asking gradable; no leads to retake once then refer, yes leads to remote grader or validated AI, which branches to disc swelling, proliferative DR and referable DR, each referred per local protocol.
A portable fundus imaging pathway as described in this article, from image capture and a gradability check to remote or AI grading and referral by finding. Symptoms or reduced acuity still need examination when the image looks normal. Original illustration (schematic), not a photograph or scan of a real patient. Easy Ophthalmology; drawn by Claude (AI), 2026-10-18; awaiting the Editor-in-Chief's review.

Before acting on this section, check the national and local guidelines, product information and regulatory approvals that apply where you practise. See the medical disclaimer.

Tier A (primary care / no specialist)

  1. Trained non-specialists can capture images for remote grading, supporting task-shifted screening and referral pathways [S9] [S11].
  2. Send images for remote grading by trained graders or ophthalmologists [S2], or use a validated AI system where available [S7] [S9].
  3. Refer every ungradable image or AI-positive result (see table).

Tier B (general eye clinic)

  1. Use portable cameras for documentation and patient counselling, as well as screening [S2].
  2. Use smartphone disc imaging to estimate cup-to-disc ratio in population screening; minimal training and low cost suit low-resource settings [S3].
  3. Use smartphone fundoscopy to teach and to support non-ophthalmic colleagues [S4] [S5].

Tier C (specialist centre)

  1. Act as the grading and referral hub for telemedicine programmes, which have widened screening coverage and timely referral of sight-threatening DR [S2].
  2. Audit programme accuracy locally: smartphone-based approaches are feasible but outcomes vary and need context-specific validation [S10].
  3. Address data governance, maintenance, regulatory compliance and photobiological safety when choosing devices [S11].

Refer when

Situation Urgency
Disc swelling on a portable image [S5] Same-day [EIC expert opinion]
Proliferative DR on a screening image [S1] Urgent; timing per your local service or specialist advice
Referable DR (graded or AI-positive) [S7] [S9] Routine; timing per your local service or specialist advice [EIC expert opinion]
Ungradable image after one retake [S3] Routine, for full examination; timing per your local service or specialist advice [EIC expert opinion]

Pitfalls

Evidence notes

Source Date Design
[S1] 2020 Scoping review and meta-analysis, 9 studies, 1430 participants
[S2] 2021 Narrative review
[S3] 2021 Prospective diagnostic study, 467 patients, Uganda
[S4] 2021 Randomised crossover trial, 102 medical students
[S5] 2022 Prospective crossover diagnostic study, 79 inpatients
[S6] 2023 Systematic review, 5 studies
[S7] 2023 Systematic review and meta-analysis, 6 studies
[S8] 2023 Systematic review, 35 studies
[S9] 2025 Systematic review and meta-analysis, 25 studies, developing countries
[S10] 2026 Systematic review and meta-analysis, 45 studies
[S11] 2026 Scoping review, 30 devices, 274 publications

Related articles

References

See the numbered source list below. Each marker [S#] links to its PubMed and DOI record.

Sources

  1. [S1] Tan CH, Kyaw BM, Smith H, Tan CS, Tudor Car L Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies. Journal of medical Internet research. (2020). PubMed 32347810 · doi:10.2196/16658
  2. [S2] Rajalakshmi R, Prathiba V, Arulmalar S, Usha M Review of retinal cameras for global coverage of diabetic retinopathy screening. Eye (London, England). (2021). PubMed 33168977 · doi:10.1038/s41433-020-01262-7
  3. [S3] Idriss BR, Tran TM, Atwine D, Chang RT, Myung D, Onyango J Smartphone-based Ophthalmic Imaging Compared With Spectral-domain Optical Coherence Tomography Assessment of Vertical Cup-to-disc Ratio Among Adults in Southwestern Uganda. Journal of glaucoma. (2021). PubMed 33394852 · doi:10.1097/ijg.0000000000001779
  4. [S4] Dunn HP, Marks S, Teo KZ, Dunn SM, Healey PR, White AJ eFOCUS 2: A randomised crossover trial of smartphone fundoscopy and direct ophthalmoscopy aiming to improve optic disc interpretation by medical students with e-learning support. Clinical & experimental ophthalmology. (2021). PubMed 34291862 · doi:10.1111/ceo.13977
  5. [S5] He G, Dunn HP, Ahmad KE, Watson E, Henderson A, Tynan D, et al. Fundoscopy use in neurology departments and the utility of smartphone photography: a prospective prevalence and crossover diagnostic accuracy study amongst neurology inpatients. European journal of neurology. (2022). PubMed 35531644 · doi:10.1111/ene.15390
  6. [S6] Prayogo ME, Zaharo AF, Damayanti NNR, Widyaputri F, Thobari JA, Susanti VY, et al. Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review. Clinical ophthalmology (Auckland, N.Z.). (2023). PubMed 37614846 · doi:10.2147/opth.s416422
  7. [S7] Hasan SU, Siddiqui MAR Diagnostic accuracy of smartphone-based artificial intelligence systems for detecting diabetic retinopathy: A systematic review and meta-analysis. Diabetes research and clinical practice. (2023). PubMed 37805002 · doi:10.1016/j.diabres.2023.110943
  8. [S8] Robles R, Patel N, Neag E, Mittal A, Markatia Z, Ameli K, et al. A Systematic Review of Digital Ophthalmoscopes in Medicine. Clinical ophthalmology (Auckland, N.Z.). (2023). PubMed 37822326 · doi:10.2147/opth.s423845
  9. [S9] Yudistira Y, Hendrawan KA, Andayani A, Suryathi NMA, Ernawati T, Gunawan ACV, et al. Diabetic Retinopathy Screening Approaches in Developing Countries: A Systematic Review and Meta-Analysis. Turkish journal of ophthalmology. (2025). PubMed 41142633 · doi:10.4274/tjo.galenos.2025.32916
  10. [S10] Wu Z, Li L Effectiveness of screening modalities for early detection of diabetic retinopathy: a systematic review and meta-analysis of tele-ophthalmology, AI-based tools, and conventional methods. Frontiers in medicine. (2026). PubMed 42100279 · doi:10.3389/fmed.2026.1778534
  11. [S11] Lechtenboehmer R, Cleland CR, Malerbi FK, Vaughan N, Rajalakshmi R, Young BK, et al. Smartphone-based fundus imaging in global eye care: Closing the gap. Progress in retinal and eye research. (2026). PubMed 42674180 · doi:10.1016/j.preteyeres.2026.101515

Guidelines

  1. [G1] NHS Scotland (Community Eyecare Guidelines, eyes.nhs.scot). 10.3 Diabetic Retinopathy, Proliferative (n.d.). https://www.eyes.nhs.scot/eyecare-guidelines/section-10-retina/103-diabetic-retinopathy-proliferative/