Optical coherent tomographic image retinopathy intelligent testing system and testing method

Abstract

The invention discloses an optical coherent tomographic image retinopathy intelligent testing system and a testing method. A current acquired retina image is mainly determined by an ophthalmology doctor by means of naked eye observation, and large-scale popularization is not facilitated. According to the system, a deep learning concept is used as a technical core; a migration learning strategy isutilized; a convolutional neural network algorithm in a deep learning model is used for establishing a classifier, thereby realizing classification of retinopathy; furthermore an image segmenting algorithm is used for realizing focus extraction and retina layering, thereby obtaining specific information of a pathology position in a picture and quantification information of shape parameters, and generating a related diagnosis report for further diagnosis by the doctor. The optical coherent tomographic image retinopathy intelligent testing system and the testing method have advantages of fillingin gaps in pathology intelligent identification and accurate positioning in a current optical coherent chromatography imaging system, effectively reducing working intensity of the doctor, and furtherpromoting clinical application and technical development of the optical coherent chromatography imaging system in ophthalmology disease diagnosis.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an optical coherence tomography image retinopathy intelligent detection system and detection method. Background technique [0002] Eye diseases seriously affect the quality of life of patients. The latest figures from the World Health Organization (October 2013) show that the number of visually impaired people worldwide is approximately 285 million, and the World Health Organization predicts that by 2020, if no action is taken, the number of blind people and patients with other vision problems worldwide will The total will also be doubled. At the end of the last century, the "Vision 2020" global blindness prevention strategy goal proposed that about 50% of blindness can be cured (such as cataract, trachoma, etc.), and about 30% of blindness can be prevented (such as glaucoma, diabetic retinopathy). Therefore, early detection and treatment of ophthalmic dise...

AI Technical Summary

Problems solved by technology

[0004] At present, the retinal images obtained by OCT in the examination of retinal diseases are mainly judged by ophthalmologists relying on naked eye observation. The workload is very heavy, and it is extremely dependent on the doctor's personal clinical experience. This identification method is not conducive to large-scale promotion

In addition, patients with preventable and curable blindness and low vision are more distributed in economically underdeveloped countries and regions. The reason is the lack of medical resources and uneven distribution.

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