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    Blood Vessel Extraction and Optic Disk Localization for Diabetic Retinopathy
    (2020-09-15)
    Kanjanasurat, Isoon
    ;
    Purahong, Boonchana
    ;
    Pintavirooj, Chuchart
    ;
    Satayarak, Nitjaree
    ;
    Benjangkaprasert, Chawalit
    This paper presents methods of vascular extraction and optic disk localization in the retinal images. Our approach begins with preprocessing to improve the quality of blood vessels. In the next step, a matrix filter was applied to express blood vessels. Finally, the blood vessel structure was used to estimate the location of the optic disk. The proposed method was tested on all different forty retinal images from the DRIVE database, which public retinal image dataset. The results of vessel extraction were compared with the ground truth image. The error of vascular extraction showed that the average sensitivity and accuracy were 79.81% and 94.98%, respectively. The optic disk localization achieved 97.5%.
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    Retina blood vessel detection for diabetic retinopathy diagnosis
    (2019-03-28)
    Narkthewan, Athasart
    ;
    Maneerat, Noppadol
    Diabetes affects the microangiopathy in the retina which causes to retinal disorders such as blood vessel blockage then the abnormal blood vessel is occurred. The microvascular leakage will decrease or loss of sight. The aim of this research is to find the retinal blood vessel detection method for diagnosis of diabetic retinopathy. This study was carried out using the principle of image processing to analyze the retina image. The green channel was used for data processing. Consequently, several image processing techniques were applied to the green channel data as image enhancement, scaling, morphological operator and filter to extract the features of the retinal blood vessel in the retina image. The retinal blood vessel was extracted and displayed on the screen for diagnosis. The efficiency of algorithm for the retinal blood vessel detection was presented in this study. All different twenty retinal images from the DRIVE database were tested for blood vessel extraction. The error detection data was compared with the ground truth image. The results show that the maximum specificity and accuracy were 99.66% and 96.80%, respectively. It indicated that the proposed method could detect the blood vessel from retina image.