![]() ![]() In most cases, only a small number of selected images are analyzed, and this could cause the wasting of medical resources. Ophthalmologists diagnose the fundus diseases by analyzing the change of retinal features in OCT images however, OCT instruments can produce large amounts of data in a short time, so it is difficult to analyze all data by manual method. In addition, there are researches on statistical analysis of normal retinal thickness. Several medical researchers used OCT to acquire retinal statistical characteristics and analyzed different kinds of fundus diseases, such as macular oedema caused by diabetic retinopathy, drusen and drusenoid pigment epithelium detachment caused by non-neovascular age-related macular degeneration, X-linked retinoschisis, epiretinal membrane, macular hole, central serous chorioretinopathy et al. The most significant medical contribution of OCT is the ophthalmology area, as it could provide the retinal structure and functional images that no other noninvasive diagnosis method can perform. Optical coherence tomography (OCT) is an in vivo imaging technique that could rapidly acquire high resolution cross-section images of biological tissues microstructure. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis. The proposed method can obtain the parameters and the features that are associated with retinal morphology. This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. Firstly, the normal retinal reference model based on retinal boundaries was presented. This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. ![]()
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