AI搭載のポータブル眼科検査システムを開発― 場所を選ばない眼科スクリーニングにより白内障などの早期発見へ ―

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2026-04-01 東北大学

東北大学の研究チームは、AIを搭載したポータブル眼科検査システムを開発し、場所を選ばない眼疾患スクリーニングを可能にした。軽量AIにより通信環境が不要で、従来の細隙灯顕微鏡と同等の精度を維持しつつコストを約6分の1に削減。さらに自撮り機能により専門医が不在でも検査が可能となり、駅や施設など日常環境での検診を実現する。これにより白内障や緑内障の早期発見が期待され、医療過疎地や災害時の診断支援にも貢献する技術として注目される。

AI搭載のポータブル眼科検査システムを開発― 場所を選ばない眼科スクリーニングにより白内障などの早期発見へ ―
図1. 検査の有用性 あらゆるところで検査ができ、多くの疾患を発見

<関連情報>

低コストの眼疾患スクリーニングのための、AI搭載型携帯型スキャン式スリットライト装置 Portable AI-powered scanning slit-light device for low-cost eye disease screening

Neelam Kaushik,Parmanand Sharma,Takehiro Miya,Noriko Himori,Masataka Sato,Satoru Tsuda & Toru Nakazawa
Scientific Reports  Published:17 March 2026
DOI:https://doi.org/10.1038/s41598-026-44392-w  Unedited version

Abstract

Accurate anterior-segment assessment is essential for detecting conditions such as primary angle-closure glaucoma, cataract, and keratoconus, yet current tools remain limited: slit-lamp biomicroscopy is qualitative and operator-dependent, whereas anterior segment OCT (AS-OCT) is costly and clinic-bound. We introduce an AI-integrated portable scanning slit-light device that delivers quantitative anterior-segment biometry at a material cost below USD 500. The system combines a motorized slit-scanning mechanism with synchronized imaging and an on-device deep-learning model (LWBNA-unet) to segment corneal and iris reflections, pupil boundaries, and corneal surfaces. Geometry-aware corrections—including slit-incidence compensation and per-frame anatomical scaling—enable calibrated estimation of anterior chamber depth (ACD) as the primary quantitative output, with exploratory estimates of central corneal thickness (CCT) derived from the same scan. In a clinical study of 170 participants, ACD showed excellent agreement with AS-OCT (Pearson’s r ≈ 0.92, concordance correlation coefficient ≈ 0.90; mean bias ≈ 0.0–0.04 mm with 95% limits of agreement LoR ~ ± 0.3 mm) indicating near-clinical interchangeability for ACD in a screening context. Representative cases illustrated clear visualization of anterior-segment features associated with narrow angles, cataract, corneal opacity, and keratoconic ectasia from a single scanning-slit video. A typical 51-frame video (captured in ~ 15 s) can be fully processed on a Jetson Orin Nano in 18.5 s (≈ 2.7 fps), supporting compact, battery-powered deployment. These results establish the first ultra–low-cost platform capable of automated, quantitative, and anatomically calibrated anterior-segment imaging, offering a scalable foundation for community screening and teleophthalmology in resource-limited settings.

医療・健康
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