A non-invasive diabetes diagnosis method based on novel scleral imaging instrument and AI

Wenqi Lv; Rongxin Fu; Xue Lin; Ya Su; Xiangyu Jin; Han Yang; Xiaohui Shan; Wenli Du; Kai Jiang; Yuanhua Lin; Guoliang Huang

doi:10.1117/12.2601222

15 October 2021 A non-invasive diabetes diagnosis method based on novel scleral imaging instrument and AI

Wenqi Lv, Rongxin Fu, Xue Lin, Ya Su, Xiangyu Jin, Han Yang, Xiaohui Shan, Wenli Du, Kai Jiang, Yuanhua Lin, Guoliang Huang

Author Affiliations +

Proceedings Volume 11900, Optics in Health Care and Biomedical Optics XI; 1190013 (2021) https://doi.org/10.1117/12.2601222
Event: SPIE/COS Photonics Asia, 2021, Nantong, JS, China

Abstract

Type 2 diabetes mellitus is one of the most common metabolic diseases in the world. However, frequent blood glucose testing causes continual harm to diabetics, which cannot meet the needs of early diagnosis and long-term tracking of diabetes. Thus non-invasive adjuvant diagnosis methods are urgently needed, enabling early screening of the population for diabetes, the evaluation of diabetes risk, and assessment of therapeutic effects. The human eye plays an important role in painless and non-invasive approaches, because it is considered an internal organ but can be easily be externally observed. We developed an AI model to predict the probability of diabetes from scleral images taken by a specially developed instrument, which could conveniently and quickly collect complete scleral images in four directions and perform artificial intelligence (AI) analysis in 3 min without any reagent consumption or the need for a laboratory. The novel optical instrument could adaptively eliminate reflections and collected shadow-free scleral images. 177 subjects were recruited to participate in this experiment, including 127 benign subjects and 50 malignant subjects. The blood sample and sclera images from each subject was obtained. The scleral image classification model achieved a mean AUC over 0.85, which indicates great potential for early screening of practical diabetes during periodic physical checkups or daily family health monitoring. With this AI scleral features imaging and analysis method, diabetic patients’ health conditions can be rapidly, noninvasively, and accurately analyzed, which offers a platform for noninvasive forecasting, early diagnosis, and long-term monitoring for diabetes and its complications.

Conference Presentation

Citation Download Citation

Wenqi Lv, Rongxin Fu, Xue Lin, Ya Su, Xiangyu Jin, Han Yang, Xiaohui Shan, Wenli Du, Kai Jiang, Yuanhua Lin, and Guoliang Huang "A non-invasive diabetes diagnosis method based on novel scleral imaging instrument and AI", Proc. SPIE 11900, Optics in Health Care and Biomedical Optics XI, 1190013 (15 October 2021); https://doi.org/10.1117/12.2601222

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available