基于人工智能技术的斜视诊疗进展

doi:10.3969/j.issn.1674-8115.2024.03.013

上海交通大学学报（医学版） ›› 2024, Vol. 44 ›› Issue (3): 393-398.doi: 10.3969/j.issn.1674-8115.2024.03.013

• 综述 • 上一篇

基于人工智能技术的斜视诊疗进展

郭勇麟¹^,²(), 陈墨馨¹^,²(), 刘哲源³, 李奕霏¹^,², 王子琦¹^,², 舒琴¹^,², 李琳¹^,²()

^1.上海交通大学医学院附属第九人民医院眼科，上海 200011
^2.上海市眼眶病眼肿瘤重点实验室，上海 200011
^3.上海交通大学电子信息与电气工程学院，上海 200240

收稿日期:2023-10-18 接受日期:2023-01-26 出版日期:2024-03-28 发布日期:2024-04-29
通讯作者: 李琳 E-mail:guoyonglin@sjtu.edu.cn;evechen802@outlook.com;jannetlee1300@163.com
作者简介:郭勇麟（2004—），男，本科生；电子信箱：guoyonglin@sjtu.edu.cn
陈墨馨（1997—），女，博士生；电子信箱：evechen802@outlook.com。第一联系人：郭勇麟、陈墨馨为共同第一作者。
基金资助:
上海市“科技创新行动计划”生物医药科技支撑专项项目(23S31900500);上海交通大学中国医院发展研究院定向委托项目(CHDI-2022-DX-02);上海市高水平地方高校创新团队(SSMU-ZDCX20180401);上海交通大学医学院大学生创新性训练计划(1824026)

Progress in diagnosis and treatment of strabismus based on artificial intelligence technology

GUO Yonglin¹^,²(), CHEN Moxin¹^,²(), LIU Zheyuan³, LI Yifei¹^,², WANG Ziqi¹^,², SHU Qin¹^,², LI Lin¹^,²()

^1.Department of Ophthalmology, Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
^2.Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai 200011, China
^3.School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received:2023-10-18 Accepted:2023-01-26 Online:2024-03-28 Published:2024-04-29
Contact: LI Lin E-mail:guoyonglin@sjtu.edu.cn;evechen802@outlook.com;jannetlee1300@163.com
Supported by:
Shanghai Science and Technology Innovation Action Plan Biomedical Technology Support Special Project(23S31900500);Target Commission of China Hospital Development Institute, Shanghai Jiao Tong University(CHDI-2022-DX-02);The Innovative Research Team of High-level Local Universities in Shanghai(SSMU-ZDCX20180401);Undergraduate Training Program on Innovation, Shanghai Jiao Tong University School of Medicine(1824026)

摘要/Abstract

摘要：

斜视是由于中枢管制失调、眼外肌力量失衡，导致双眼不能同时注视目标的一种眼病，通常在儿童期发病，可造成弱视、视功能损害、斜颈等发育不良和心理障碍。该病对患者、家庭乃至社会都会产生消极影响。早诊断、早治疗可避免造成视力和立体视的永久损害。然而，目前斜视的诊断高度依赖眼科医师专业检查，效率低、覆盖面小，而常规的入校筛查无法反映斜视度，且准确率低。因此如何提高斜视筛检效率是具有重要意义的热点问题。该文从人工智能技术发展的角度，基于近年来国内外的斜视诊疗现状，综述斜视领域中人工智能模型和算法的研究进展及不足，为进一步探索人工智能辅助的斜视诊疗前景提供参考。

关键词: 斜视, 人工智能, 诊断, 治疗, 算法

Abstract:

Strabismus, misalignment of the eyes arising from central nervous system dysregulation and extraocular muscles imbalance, commonly manifests in childhood, leading to amblyopia, binocular vision dysfunction, torticollis and other developmental and psychological disorders. This exerts a negative impact on individuals, families and society. Timely diagnosis and intervention are crucial to prevent permanent damage to vision and stereopsis. Presently, strabismus diagnosis is reliant on the ophthalmologists′ evaluations which results in a lack of efficiency and coverage. However, routine school screening proves inadequate in assessing strabismus degree with low accuracy. Therefore, how to improve the efficiency of strabismus screening is an issue of great importance. This paper delves into the present landscape of strabismus diagnosis and treatment, considering both local and global research advancements. It focuses on the evolution of artificial intelligence technology, illuminating the utilization of artificial intelligence models and algorithms in strabismus. By pinpointing and exploring their strengths and limitations, it offers valuable insights, paving the way for future investigations into artificial intelligence-assisted strabismus diagnosis and treatment.

Key words: strabismus, artificial intelligence, diagnosis, treatment, algorithm

中图分类号:

R777.4

郭勇麟, 陈墨馨, 刘哲源, 李奕霏, 王子琦, 舒琴, 李琳. 基于人工智能技术的斜视诊疗进展[J]. 上海交通大学学报（医学版）, 2024, 44(3): 393-398.

GUO Yonglin, CHEN Moxin, LIU Zheyuan, LI Yifei, WANG Ziqi, SHU Qin, LI Lin. Progress in diagnosis and treatment of strabismus based on artificial intelligence technology[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2024, 44(3): 393-398.

参考文献 34

1	潘亚玲, 王晗琦, 陆勇. 人工智能在医学影像CAD中的应用[J]. 国际医学放射学杂志, 2019, 42(1): 3-7.
	PAN Y L, WANG H Q, LU Y. The application of computer aided diagnosis with artificial intelligence in medical imaging[J]. International Journal of Medical Radiology, 2019, 42 (1): 3-7.
2	LAUGHTON S C, HAGEN M M, YANG W, et al. Gender differences in horizontal strabismus: systematic review and meta-analysis shows no difference in prevalence, but gender bias towards females in the clinic[J]. J Glob Health, 2023, 13: 04085.
3	HASHEMI H, PAKZAD R, HEYDARIAN S, et al. Global and regional prevalence of strabismus: a comprehensive systematic review and meta-analysis[J]. Strabismus, 2019, 27(2): 54-65.
4	WANG Y, ZHAO A D, ZHANG X H, et al. Prevalence of strabismus among preschool children in Eastern China and comparison at a 5-year interval: a population-based cross-sectional study[J]. BMJ Open, 2021, 11(10): e055112.
5	REPKA M X, LUM F, BURUGAPALLI B. Strabismus, strabismus surgery, and reoperation rate in the United States: analysis from the IRIS registry[J]. Ophthalmology, 2018, 125(10): 1646-1653.
6	ZHANG X, LI F, RAO J M, et al. Spectrum of ophthalmic diseases in children hospitalized in a tertiary ophthalmology hospital in China from 2010 to 2019[J]. BMC Ophthalmol, 2022, 22(1): 314.
7	MOSTAFAIE A, GHOJAZADEH M, HOSSEINIFARD H, et al. A systematic review of Amblyopia prevalence among the children of the world[J]. Rom J Ophthalmol, 2020, 64(4): 342-355.
8	赵旭峰, 于伟泓. 人工智能技术在眼底图像分析中的应用进展[J]. 中国医学前沿杂志(电子版), 2023, 15(6): 21-26.
	ZHAO X F, YU W H. Advanced in the application of artificial intelligence in fundus image analysis[J]. Chinese Journal of the Frontiers of Medical Science(Electronic Version), 2023, 15(6): 21-26.
9	KAUL V, ENSLIN S, GROSS S A. History of artificial intelligence in medicine[J]. Gastrointest Endosc, 2020, 92(4): 807-812.
10	HARDAS M, MATHUR S, BHASKAR A, et al. Retinal fundus image classification for diabetic retinopathy using SVM predictions[J]. Phys Eng Sci Med, 2022, 45(3): 781-791.
11	KIM S J, CHO K J, OH S. Development of machine learning models for diagnosis of glaucoma[J]. PLoS One, 2017, 12(5): e0177726.
12	YANG Y H, LI R Y, LIN D R, et al. Automatic identification of myopia based on ocular appearance images using deep learning[J]. Ann Transl Med, 2020, 8(11): 705.
13	WALLACE D K, CHRISTIANSEN S P, SPRUNGER D T, et al. Esotropia and exotropia preferred practice pattern®[J]. Ophthalmology, 2018, 125(1): P143-P183.
14	史斌, 谭大鹏, 王雪林, 等. MRI检查在复杂性斜视患儿中的应用价值分析[J]. 江西医药, 2020, 55(6): 767-769.
	SHI B, TAN D P, WANG X L, et al. Analysis of the application value of MRI examination in children with complex strabismus[J]. Jangxi Medical Journal, 2020, 55(6): 767-769.
15	HAO R, LIU Y, ZHANG W, et al. Morphological study of extraocular muscles in dissociated vertical deviation by magnetic resonance imaging[J]. Zhonghua Yan Ke Za Zhi, 2023, 59(3): 202-206.
16	HULL S, TAILOR V, BALDUZZI S, et al. Tests for detecting strabismus in children aged 1 to 6 years in the community[J]. Cochrane Database Syst Rev, 2017, 11(11): CD011221.
17	袁久民, 袁久华, 王正艳. 角膜映光检查法理论与临床[J]. 国际眼科杂志, 2005, 5(3): 522-527.
	YUAN J M, YUAN J H, WANG Z Y. Theory and clinical practice on corneal light reflection[J]. International Eye Science, 2005, 5(3): 522-527.
18	TENGTRISORN S, TUNGSATTAYATHITTHAN A, PHATTHALUNG S N, et al. The reliability of the angle of deviation measurement from the Photo-Hirschberg tests and Krimsky tests[J]. PLoS One, 2021, 16(12): e0258744.
19	牛玉玲, 叶茹珊, 金玲, 等. Hirschberg Test在儿童斜视角测量中的准确性和可靠性研究[J]. 中外医学研究, 2018, 16(24): 149-150.
	NIU Y L, YE R S, JIN L, et al. A study of the accuracy and reliability of the Hirschberg Test in the measurement of oblique angle of vision in children[J]. Chinese And Foreign Medical Research, 2018, 16(24):149-150.
20	王翠英, 陈丽萍, 邢华禹. 同视机在双眼视功能检查的应用[J]. 中国眼镜科技杂志, 2019(11): 107-109.
	WANG C Y, CHEN L P, XING H Y, et al. Application of synoptoscope in binocular visual function examination[J]. China Glasses Science-Technology Magazine, 2019(11): 107-109.
21	周榆松, 庄仪婧, 李劲嵘. 斜视度的客观测量方法[J]. 国际眼科纵览, 2022, 46(1): 76-79.
	ZHOU Y S, ZHUANG Y J, LI J R. Methods for measuring strabismus objectively[J]. International Review of Ophthalmology, 2022, 46(1): 76-9.
22	DYSLI M, FIERZ F C, RAPPOPORT D, et al. Divergence bias in Hess compared to Harms screen strabismus testing[J]. Strabismus, 2021, 29(1): 1-9.
23	THORISDOTTIR R L, SUNDGREN J, SHEIKH R, et al. Comparison of a new digital KM screen test with conventional Hess and Lees screen tests in the mapping of ocular deviations[J]. J AAPOS, 2018, 22(4): 277-280.e6.
24	VALENTE T L A, DE ALMEIDA J D S, SILVA A C, et al. Automatic diagnosis of strabismus in digital videos through cover test[J]. Comput Meth Programs Biomed, 2017, 140: 295-305.
25	姚倩. 基于深度学习的斜视图片自动检测的运用研究[D]. 汕头: 汕头大学, 2019.
	YAO Q. Automatically Detecting on Strabismus Image Based on Deep Learning[D]. Shantou: Shantou University, 2019.
26	DE FIGUEIREDO L A, DIAS J V P, POLATI M, et al. Strabismus and artificial intelligence app: optimizing diagnostic and accuracy[J]. Transl Vis Sci Technol, 2021, 10(7): 22.
27	HUANG X L, LEE S J, KIM C Z, et al. An automatic screening method for strabismus detection based on image processing[J]. PLoS One, 2021, 16(8): e0255643.
28	CHEN Z H, FU H, LO W L, et al. Strabismus recognition using eye-tracking data and convolutional neural networks[J]. J Healthc Eng, 2018, 2018: 7692198.
29	FAN Z, LU J W, ZHENG C, et al. Automated strabismus detection based on deep neural networks for telemedicine applications[EB/OL]. (2018-12-03)[2023-10-03]. http://arxiv.org/abs/1809.02940.
30	ALMEIDA J D, SILVA A C, TEIXEIRA J A M, et al. Surgical planning for horizontal strabismus using Support Vector Regression[J]. Comput Biol Med, 2015, 63: 178-186.
31	LEITE F H F, ALMEIDA J D S, CRUZ L B D, et al. Surgical planning of horizontal strabismus using multiple output regression tree[J]. Comput Biol Med, 2021, 134: 104493.
32	MAO K L, YANG Y H, GUO C, et al. An artificial intelligence platform for the diagnosis and surgical planning of strabismus using corneal light-reflection photos[J]. Ann Transl Med, 2021, 9(5): 374.
33	LOU L X, HUANG X R, SUN Y M, et al. Automated photographic analysis of inferior oblique overaction based on deep learning[J]. Quant Imaging Med Surg, 2023, 13(1): 329-338.
34	WANG S Y, JI Y K, BAI W, et al. Advances in artificial intelligence models and algorithms in the field of optometry[J]. Front Cell Dev Biol, 2023, 11: 1170068.

[1]	徐文晖, 杨畅, 李瑞卿, 卞京, 李夏伊, 郑磊贞. 干扰素调节因子3促结直肠癌细胞增殖与侵袭相关探索[J]. 上海交通大学学报（医学版）, 2024, 44(3): 301-311.
[2]	郑梦奕, 毛家亮, 邹治国, 张瑞雷, 张厚, 李世光. 全身免疫炎症指数及躯体化症状评分对首发心梗PCI术后发生院内主要不良心血管事件的预测价值[J]. 上海交通大学学报（医学版）, 2024, 44(3): 334-341.
[3]	樊强, 吴广博, 赵劲博, 郑磊, 罗蒙. 肝硬化失代偿期门静脉高压症病理生理及分子机制改变的研究进展[J]. 上海交通大学学报（医学版）, 2024, 44(3): 379-384.
[4]	邓青松, 张长青, 陶诗聪. 烟酰胺代谢相关基因与骨关节炎的关系探索[J]. 上海交通大学学报（医学版）, 2024, 44(2): 145-160.
[5]	杨婧偊, 陈留宝, 王康太, 杨兴智, 于海涛. 基于实验室指标的系统性红斑狼疮鉴别诊断列线图的构建及评估[J]. 上海交通大学学报（医学版）, 2024, 44(2): 204-211.
[6]	丁艳玲, 李杰, 袁军, 李燕. 慢性淋巴细胞白血病靶向治疗的研究进展[J]. 上海交通大学学报（医学版）, 2024, 44(2): 264-270.
[7]	朱开元, 苏瑜琛, 刘智超, 章宏, 李春光, 张杰, 李志刚. 食管鳞癌内镜黏膜下剥离术后T1b患者再治疗策略分析[J]. 上海交通大学学报（医学版）, 2024, 44(1): 116-123.
[8]	周海霞, 张靖. m⁶A甲基化修饰调控肿瘤免疫的研究进展[J]. 上海交通大学学报（医学版）, 2024, 44(1): 137-144.
[9]	李倩玉, 郭文韵, 钱逸斐, 李松玲, 朱子俊, 刘艳丰. ASGR1在肝细胞癌中的意义及机制研究[J]. 上海交通大学学报（医学版）, 2023, 43(9): 1107-1114.
[10]	吴凯敏, 麻静, 赵旭赟. 间歇性禁食联合产热脂肪活化防治小鼠肥胖作用研究[J]. 上海交通大学学报（医学版）, 2023, 43(9): 1131-1144.
[11]	杨越, 何开举, 宗家豪, 杨自逸, 吴向嵩, 龚伟. 细胞游离DNA在胆道癌诊断中的价值：一项meta分析[J]. 上海交通大学学报（医学版）, 2023, 43(9): 1175-1185.
[12]	朱涵菁, 殷弘凡, 尤思洁, 杨艳. 前列腺癌患者内分泌治疗相关不良反应的潜在剖面分析[J]. 上海交通大学学报（医学版）, 2023, 43(9): 1186-1193.
[13]	李郡如, 欧阳彦, 谢静远. 肠道菌群在IgA肾病发病与治疗中的作用研究进展[J]. 上海交通大学学报（医学版）, 2023, 43(8): 1044-1048.
[14]	周婉桢, 滕银成. 非经典Wnt通路在卵巢癌中的作用与潜在治疗意义研究进展[J]. 上海交通大学学报（医学版）, 2023, 43(8): 1056-1063.
[15]	赵艳红, 王传萍. 哮喘表型中CD4⁺ T细胞亚群的研究综述：分子机制和生物治疗选择[J]. 上海交通大学学报（医学版）, 2023, 43(8): 1064-1070.

基于人工智能技术的斜视诊疗进展

Progress in diagnosis and treatment of strabismus based on artificial intelligence technology

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 34

相关文章 15

编辑推荐

Metrics