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基于眼前节照相的翼状胬肉人工智能辅助诊断研究进展和思考
米玛卓玛
陈亚萍
纪玉珂
陈楠
吴星阳
杨卫华
钱会
作者及单位信息
·
DOI： 10.3760/cma.j.cn101909-20230707-00013
Research progress and thinking on artificial intelligence assisted diagnosis of pterygium based on anterior segment photographs
Mikma Droma
Chen Yaping
Ji Yuke
Chen Nan
Wu Xingyang
Yang Weihua
Qian Hui
Authors Info & Affiliations
Mikma Droma
Department of Ophthalmology, Naqu People′s Hospital, Naqu 852000, China
Chen Yaping
Department of Ophthalmology, Naqu People′s Hospital, Naqu 852000, China
Ji Yuke
Department of Ophthalmology, Eye Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China
Chen Nan
Department of Ophthalmology, Eye Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China
Wu Xingyang
Big Data and AI Institute, Shenzhen Eye Hospital, Shenzhen 518040, China
Yang Weihua
Big Data and AI Institute, Shenzhen Eye Hospital, Shenzhen 518040, China
Qian Hui
Department of Ophthalmology, Eye Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China
·
DOI： 10.3760/cma.j.cn101909-20230707-00013
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摘要

翼状胬肉是一种常见眼表疾病，表现为纤维血管组织增殖和入侵。翼状胬肉在早期仅引起轻微的眼表不适，一旦累及角膜瞳孔区域，就会影响患者的视力。所以应尽早发现翼状胬肉，并采取相应措施控制其生长。多数患者无法辨别翼状胬肉的出现与发展，而目前的医疗资源尚无法满足完全依靠眼科医生来定期检查。基于机器学习技术，开发一种基于简单成像模式的翼状胬肉人工智能辅助诊断系统，可利于便捷检测翼状胬肉组织的存在并进行分类、分割。本文总结了人工智能在翼状胬肉诊断应用中的最新技术，旨在为人工智能翼状胬肉诊断应用的未来发展提供展望。

翼状胬肉;诊断;深度学习;机器学习;人工智能;眼前节照相
ABSTRACT

Pterygium is a common ocular surface disease in which fibrous vascular tissue multiplies and grows into the corneal area. In the early stage, there is no obvious effect on the patient other than minor ocular surface discomfort. Once the pterygium involves the corneal pupil area, it can affect the patient′s vision. Therefore, it is necessary to detect this condition as early as possible and take corresponding measures to control its growth. Most patients are unable to identify the occurrence and development of pterygium, and current medical resources cannot meet the requirements if regular examinations by ophthalmologist are solely relied upon. Therefore, it is necessary to develop a pterygium artificial intelligence assisted diagnosis system based on anterior segment photographs, so as to conveniently detect the existence of pterygium tissue and perform classification and segmentation. In this paper, the latest technologies of artificial intelligence in the diagnosis of pterygium are reviewed, aiming at providing prospects for the development of artificial intelligence in the diagnosis of pterygium.

Pterygium;Diagnosis;Deep learning;Machine learning;Artificial intelligence;Anterior segment photograph
Qian Hui, Email: mocdef.6ab21025781iuhnaiq
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米玛卓玛,陈亚萍,纪玉珂,等. 基于眼前节照相的翼状胬肉人工智能辅助诊断研究进展和思考[J]. 数字医学与健康,2023,01(02)：115-120.

DOI:10.3760/cma.j.cn101909-20230707-00013

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翼状胬肉是一种常见的眼表疾病，又称为胬肉攀睛，表现为局部纤维血管组织过度增殖，主要起源于内眦结膜的纤维血管组织区域 ［ 1 ］ 。对于较为严重的翼状胬肉病例，胬肉可以生长在内眦部和外眦部两侧。翼状胬肉分两种类型：静止型和进展型。在进展型翼状胬肉中，翼状胬肉组织会不断地向角膜区域生长。最初，翼状胬肉异常组织只是涉及巩膜上方的结膜，一旦病情变得更严重，翼状胬肉就会累及角膜区域，进而阻止光线进入黄斑区域，导致视力下降。故早期翼状胬肉的筛查至关重要，可基于检查结果建议患者采取适当的预防措施，并使用简单的方法控制翼状胬肉的生长 ［ 2 ］ 。本文将对翼状胬肉的基本情况及危险因素进行介绍，并对翼状胬肉的人工智能辅助诊断应用情况进行总结，对进一步提高人工智能在翼状胬肉诊断中的应用性能提出建议。
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钱会，Email： mocdef.6ab21025781iuhnaiq
B
米玛卓玛, 陈亚萍, 纪玉珂, 等. 基于眼前节照相的翼状胬肉人工智能辅助诊断研究进展和思考[J]. 数字医学与健康, 2023, 1(2): 115-120. DOI: 10.3760/cma.j.cn101909-20230707-00013.
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