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Artificial intelligence in the anterior segment of eye diseases
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作者 Yao-Hong Liu Lin-Yu Li +4 位作者 Si-Jia Liu Li-Xiong Gao Yong Tang Zhao-Hui Li Zi Ye 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2024年第9期1743-1751,共9页
Ophthalmology is a subject that highly depends on imaging examination.Artificial intelligence(AI)technology has great potential in medical imaging analysis,including image diagnosis,classification,grading,guiding trea... Ophthalmology is a subject that highly depends on imaging examination.Artificial intelligence(AI)technology has great potential in medical imaging analysis,including image diagnosis,classification,grading,guiding treatment and evaluating prognosis.The combination of the two can realize mass screening of grass-roots eye health,making it possible to seek medical treatment in the mode of“first treatment at the grass-roots level,two-way referral,emergency and slow treatment,and linkage between the upper and lower levels”.On the basis of summarizing the AI technology carried out by scholars and their teams all over the world in the field of ophthalmology,quite a lot of studies have confirmed that machine learning can assist in diagnosis,grading,providing optimal treatment plans and evaluating prognosis in corneal and conjunctival diseases,ametropia,lens diseases,glaucoma,iris diseases,etc.This paper systematically shows the application and progress of AI technology in common anterior segment ocular diseases,the current limitations,and prospects for the future. 展开更多
关键词 artificial intelligence anterior segment ocular disease AMETROPIA GLAUCOMA
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EyeHealer:A large-scale anterior eye segment dataset with eye structure and lesion annotations 被引量:1
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作者 Wenjia Cai Jie Xu +15 位作者 Ke Wang Xiaohong Liu Wenqin Xu Huimin Cai Yuanxu Gao Yuandong Su Meixia Zhang Jie Zhu Charlotte L.Zhang Edward E.Zhang Fangfei Wang Yun Yin Iat Fan Lai Guangyu Wang Kang Zhang Yingfeng Zheng 《Precision Clinical Medicine》 2021年第2期85-92,共8页
Anterior segment eye diseases account for a significant proportion of presentations to eye clinics worldwide,including diseases associated with corneal pathologies,anterior chamber abnormalities(e.g.blood or inflammat... Anterior segment eye diseases account for a significant proportion of presentations to eye clinics worldwide,including diseases associated with corneal pathologies,anterior chamber abnormalities(e.g.blood or inflammation),and lens diseases.The construction of an automatic tool for segmentation of anterior segment eye lesions would greatly improve the efficiency of clinical care.With research on artificial intelligence progressing in recent years,deep learning models have shown their superiority in image classification and segmentation.The training and evaluation of deep learning models should be based on a large amount of data annotated with expertise;however,such data are relatively scarce in the domain of medicine.Herein,the authors developed a new medical image annotation system,called EyeHealer.It is a large-scale anterior eye segment dataset with both eye structures and lesions annotated at the pixel level.Comprehensive experiments were conducted to verify its performance in disease classification and eye lesion segmentation.The results showed that semantic segmentation models outperformed medical segmentation models.This paper describes the establishment of the system for automated classification and segmentation tasks.The dataset will be made publicly available to encourage future research in this area. 展开更多
关键词 anterior segment eye diseases artificial intelligence ANNOTATION
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