Abstract
PurposeA real-time automatic cataract-grading algorithm based on cataract video is proposed.Materials and methodsIn this retrospective study, we set the video of the eye lens section as the research target. A method is proposed to use YOLOv3 to assist in positioning, to automatically identify the position of the lens and classify the cataract after color space conversion. The data set is a cataract video file of 38 people's 76 eyes collected by a slit lamp. Data were collected using five random manner, the method aims to reduce the influence on the collection algorithm accuracy. The video length is within 10 s, and the classified picture data are extracted from the video file. A total of 1520 images are extracted from the image data set, and the data set is divided into training set, validation set and test set according to the ratio of 7:2:1.ResultsWe verified it on the 76-segment clinical data test set and achieved the accuracy of 0.9400, with the AUC of 0.9880, and the F1 of 0.9388. In addition, because of the color space recognition method, the detection per frame can be completed within 29 microseconds and thus the detection efficiency has been improved significantly.ConclusionWith the efficiency and effectiveness of this algorithm, the lens scan video is used as the research object, which improves the accuracy of the screening. It is closer to the actual cataract diagnosis and treatment process, and can effectively improve the cataract inspection ability of non-ophthalmologists. For cataract screening in poor areas, the accessibility of ophthalmology medical care is also increased.
Highlights
Cataract as the main blinding eye disease and has a serious impact on people’s health and life [1]
With the efficiency and effectiveness of this algorithm, the lens scan video is used as the research object, which improves the accuracy of the screening
This paper proposes a method that uses the entire eye lens video collected by the mobile phone slit lamp as the research object, and uses the YOLOv3 [22] algorithm to assist in positioning to complete the identification and classification of cataracts
Summary
Cataract as the main blinding eye disease and has a serious impact on people’s health and life [1]. The global blindness due to cataract accounts for more than 50%. As a country with the most population, China has about a quarter of the world’s visually impaired and blind population [2]. The American Academy of Ophthalmology (AAO) defines cataract as the opacity of the lens [3]. Untreated cataract is still the main cause of blindness in the world, and there are nearly 18 million people who lose sight in both eyes [4]. More people accept cataract examination, which has
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