Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity
Retinopathy of prematurity(ROP)is the primary cause of preventable childhood blindness. It is hard to screen, diagnose and objectively evaluate. There are various modalities for ROP screening, including various contact or non-contact imaging devices, smart phone-based fundus photography, and artific...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Press of International Journal of Ophthalmology (IJO PRESS)
2023-05-01
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| Series: | Guoji Yanke Zazhi |
| Subjects: | |
| Online Access: | http://ies.ijo.cn/cn_publish/2023/5/202305013.pdf |
| _version_ | 1797837867750260736 |
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| author | Meng Li Jian Zhang Hong Yan |
| author_facet | Meng Li Jian Zhang Hong Yan |
| author_sort | Meng Li |
| collection | DOAJ |
| description | Retinopathy of prematurity(ROP)is the primary cause of preventable childhood blindness. It is hard to screen, diagnose and objectively evaluate. There are various modalities for ROP screening, including various contact or non-contact imaging devices, smart phone-based fundus photography, and artificial intelligence-based fundus image analysis. The diagnosis of ROP is based on visualization and recording of the entire retinal fundus of ROP, which is also the basis for subsequent screening, treatment assessment. Fundus screening is critical for early recognition and facilitates early detection and prompt referral. Potential features may be found by analyzing and summarizing the characteristics of ROP fundus images. Subsequently, timely and targeted ROP prevention and treatment could be performed. Artificial intelligence promotes automatic, quantifiable and objective diagnosis of ROP. This article reviews commonly used clinical fundus examination methods and fundus image characteristics of ROP and summarizes the latest research progress on the application of artificial intelligence in the automatic diagnosis of ROP. |
| first_indexed | 2024-04-09T15:32:40Z |
| format | Article |
| id | doaj.art-cbc0fbfb92fe43988e14b71b9f33ba69 |
| institution | Directory Open Access Journal |
| issn | 1672-5123 |
| language | English |
| last_indexed | 2024-04-09T15:32:40Z |
| publishDate | 2023-05-01 |
| publisher | Press of International Journal of Ophthalmology (IJO PRESS) |
| record_format | Article |
| series | Guoji Yanke Zazhi |
| spelling | doaj.art-cbc0fbfb92fe43988e14b71b9f33ba692023-04-28T06:27:01ZengPress of International Journal of Ophthalmology (IJO PRESS)Guoji Yanke Zazhi1672-51232023-05-0123578378610.3980/j.issn.1672-5123.2023.5.13202305013Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurityMeng Li0Jian Zhang1Hong Yan2Xi'an Medical University, Xi'an 710021, Shaanxi Province, ChinaDepartment of Ophthalmology, Shaanxi Provincial People's Hospital, Xi'an 710068, Shaanxi Province, ChinaXi'an People's Hospital(Xi'an Fourth Hospital);Shaanxi Eye Hospital;Affiliated People's Hospital of Northwest University, Xi'an 710004, Shaanxi Province, ChinaRetinopathy of prematurity(ROP)is the primary cause of preventable childhood blindness. It is hard to screen, diagnose and objectively evaluate. There are various modalities for ROP screening, including various contact or non-contact imaging devices, smart phone-based fundus photography, and artificial intelligence-based fundus image analysis. The diagnosis of ROP is based on visualization and recording of the entire retinal fundus of ROP, which is also the basis for subsequent screening, treatment assessment. Fundus screening is critical for early recognition and facilitates early detection and prompt referral. Potential features may be found by analyzing and summarizing the characteristics of ROP fundus images. Subsequently, timely and targeted ROP prevention and treatment could be performed. Artificial intelligence promotes automatic, quantifiable and objective diagnosis of ROP. This article reviews commonly used clinical fundus examination methods and fundus image characteristics of ROP and summarizes the latest research progress on the application of artificial intelligence in the automatic diagnosis of ROP.http://ies.ijo.cn/cn_publish/2023/5/202305013.pdfretinopathy of prematurityindirect ophthalmoscopewide-angle digital retinal imaging systemfundus image characteristicsartificial intelligence |
| spellingShingle | Meng Li Jian Zhang Hong Yan Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity Guoji Yanke Zazhi retinopathy of prematurity indirect ophthalmoscope wide-angle digital retinal imaging system fundus image characteristics artificial intelligence |
| title | Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity |
| title_full | Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity |
| title_fullStr | Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity |
| title_full_unstemmed | Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity |
| title_short | Research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity |
| title_sort | research progress on fundus examination methods and fundus image characteristics of retinopathy of prematurity |
| topic | retinopathy of prematurity indirect ophthalmoscope wide-angle digital retinal imaging system fundus image characteristics artificial intelligence |
| url | http://ies.ijo.cn/cn_publish/2023/5/202305013.pdf |
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