Research On Key Technologies Of Intelligent Assistant System For Fundus Laser Therapy

Laser therapy is one of the main methods to treat diabetic retinopathy.However,at present,the automation of fundus laser therapy instrument is not high.The laser positioning and focusing of fundus retina are basically dependent on the manual operation of doctors.The accuracy of the manual operation of doctors is low,and the treatment effect is poor.In serious cases,it will even damage the patients' retina.Moreover,the manual operation efficiency is low,and the treatment time is long,which will cause doctors' fatigue and patients' discomfort.In view of the above problems,the key technologies of the intelligent assistant system for fundus laser therapy are studied in this paper.First of all,this paper puts forward the overall design scheme of the intelligent assistant system of fundus laser therapy,which is mainly composed of fundus digital image acquisition unit,upper computer software control unit,embedded laser control unit.It analyzes the function of each module in the whole system and the relationship between each module,and analyzes in detail the hardware equipment selected in the whole module The detailed parameter information of each hardware is introduced in detail.Secondly,this paper focuses on the research of fundus feature recognition algorithm in the intelligent assistant system of fundus laser therapy,and introduces the basic knowledge involved in the algorithm in detail.Based on the structure of bilinear convolution neural network,a bilinear hole convolution U-net neural network model is proposed,which is used for image semantic segmentation of fovea and optic disc areas of fundus retina This paper analyzes the design principle of the neural network model,explains the construction and implementation process of the neural network model,and introduces the production process of the fundus retina data set in detail.Thirdly,based on the galvanometer system,the embedded laser control system is designed in this paper.The realization principle of the embedded laser control system is explained in detail.The mathematical model of two-dimensional laser scanning is deduced,and the laser galvanometer scanning control card is designed.The laser dynamic focusing optical system is designed,and the mathematical model of the laser dynamic focusing optical system is calculated in detail,using the method based on the figure The focusing depth method of image processing focuses the laser dynamically.Finally,we test the proposed neural network,and compare the test results with the common neural network model from three aspects: accuracy,running speed and model memory size.It is found that the comprehensive results of the neural network proposed in this paper are the best.In this paper,the design of the embedded laser control system is also carried out in the experimental environment,control software design,and finally a large number of experimental tests.The test results show that the positioning accuracy,focusing accuracy and scanning speed of the embedded laser control system can greatly meet the actual medical needs.