The main goal of medical imaging applications is to diagnose some diseases, try to prevent the progression of them, and actually cure the patients. The number of people that suffer from diabetes is growing very fast these recent years in many countries and it is needed to diagnose this disease in the beginning to prevent the subsequent side effects like blindness and so on. One of the first ways to detect this disease is analysis of vessels in some parts of the eye such as retina and conjunctiva. Some studies have been done on effects of vessel changes of conjunctiva in diabetes diagnosis and it is proved that conjunctival vessel extraction and analysis is a good way for this purpose. In this paper, we proposed a method to detect and extract the vessels of conjunctiva automatically. It is the first stage of the process of diabetes diagnosis. We first extract some textural features from each pixel of the conjunctiva image using LBP and then classify each pixel to vessels or nonvessels according to the features vector based on a supervised classifier, ANFIS. We tested the proposed algorithm on 40 conjunctival images to show the performance and efficiency of our method. 1. Introduction One of the best ways to early detection of some diseases like diabetes, hypertension, arteriosclerosis, and so forth is the vasculature detection and analysis in retinal images. However, manual detection and analysis of the retinal images is a time-consuming and unreliable task, and as the number of images increases, the study becomes very difficult. Therefore, it is necessary to use automated algorithms for analysis of these images. Many studies and works have been done on this issue in recent years [1–6], but there are less works and researches on conjunctiva [7–9]. Multispectral imaging of the ocular fundus, that is used for providing retinal images, suffers from three main problems: the image acquisition process needs advanced technology and also expensive photography devices, and actually it is not possible for every hospitals or medical centers to afford these devices and take the images; long acquisition times are not feasible due to patient discomfort; patient movement can lead to loss of image quality. These difficulties have caused that researchers pay more attention to other parts of eye except fundus of eye such as conjunctiva. The conjunctiva is a clear mucous membrane consisting of cells and underlying basement membrane that covers the sclera (white part of the eye) and lines in the inside of the eyelids. Figure 1 shows conjunctiva of a person. Image capture of
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