Study On Some Key Problems In Processing And Analyzing Of The Fundus Images

Medical image processing and analysis plays an important role in image processing and analysis and is generally considered as a difficult problem.Because of the complexity of fundus images,the predecessors as to the quantitative analysis of fundus images got few of the achievements.The fundus images processing and the measurement for its parameters are important to the clinical application and scientific research.The construction of computer aided analysis system of fundus images can be used of quantity measurement of the tissues in fundus images and accurate discrimination between the normal and abnormal images.It can also lead to standardize on the morphological investigation of the fundus system.Also,large advantages have been made on the inspection of the fundus images.In this paper,the fundus images processing technique and the method of its parameters quantitative measurement are studied and many achievements are got.The main achievements are shown as following:1.To improve the quality of fundus images,several pre-processing methods are proposed.Fast distortion rectification method base on slicing approximation and radiant distortion calibration technique base on color information can effectively solve the geometrical and radiant distortion caused by optical lens imaging defects.A robust feature-based method for register and mosaic of the curved color fundus images works well with the rejection error in 0.2 pixels,even for these cases where the fundus images without enough discernble structures.Also,view-field detection for the fundus images is studied.2.To segment the vasculature in fundus images automatically and accurately,a blood vessel segmentation method based on prior knowledge random walks model and an edge detection method based on post-processing are proposed.Experiments indicated that methods perform better than the existing algorithms.Moreover,the efficiency was validated in these results,and could satisfy the requirement of clinic diagnosis.3.To describe the space properties of the retinal vessel,a new conception-cross-network and measures of the network are proposed.Based on the model of fundus organs structure,automatic localization of optic nerve head is realized using the cross-network's measure parameter-cross density.Experimental results verify the effectiveness of the algorithm using the fundus image databases and the clinic images over different image qualities.And it can satisfy the requirement of clinic ophthalmological diagnosis.4.The shape,area and depth of the optic nerve head are important measurement indexes of Health Status for fundus.To realize the computer-aided measurement of these characters,an automated method to segment the optic nerve head based on the improved Random walks segmentation method and an automated detection of optic nerve boundary based on L~*a~*b~* color space are proposed in this paper.In contrast with the state-of-art algorithms,a better overlap accuracy is acquired in the comparing segmentation results for our clinic fundus images database with the golden standards and verifies the effectiveness of the proposed algorithm.5.To realize images calibration and parameters measurement,a novel calibration method based on three points scale and parameters measurement method for length, area and angle are proposed.On the base of the research of fundus images processing algorithm,a kind of developing scheme on fundus image processing system is presented. A software is developed using Visual C++6.0 under the Microsoft windows XP operation system.The software can realize many functions such as fundus image parameters quantitative measurement,assistant diagnosis,the geometry transform of fundus images,gray transform,image enhancement and the pathology report output.In contrast to other software,this software has more functions of image processing and realizes the measurement of many parameters with high application value.The research project of this paper is an intersectant research area,which is based on the development of rapid information discipline and biomedical technology.Research results solved the key problems in the fundus images processing,realized qualitative and quantitative analyses and improved precision and efficiency of clinical diagnosis. The developed system has good prospective clinic application and social benefit,as it meet the requirement of ophthalmologists,enhance ophthalmology diagnosis treatment levels and improve people health status.