Narkthewan, Athasart
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Preferred name
Narkthewan, Athasart
Main Affiliation
Email
athasart.na@kmitl.ac.th
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Item type:Publication, Automatic localization of optic disc in fundus image using iterative background removal(2019-07-01); Diabetic retinopathy (DR) is leading to cause of blood clot stimulating the formation of abnormal new blood vessels. hemorrhage and protein secretion from blood vessels to retinal tissue. The retinal damage causes the loss of sight thus the localization of Optic Disc is necessary for analysis of the abnormal retinal image. However, the data located at the Optic Disc image are similar to Hard Exudates in the retinal image. Therefore, the aim of the present study is to detect Optic Disc using the technique of background removal. The principle of image processing is also applied for the retinal image. The image data from Fundus camera are recorded in RGB color model separated into 3 channels: Red, green and blue channel. The data of all channels are evaluated by the preprocessing algorithm to make a more clear appearance of Optic Disc. Subsequently, the preprocessing image is analyzed by iterative background removal using entropy evaluation of the image data. Finally., the variance analysis of data intensity is performed in both the horizontal and vertical axis to determine the localization and size of Optic Disc. The result shows that the accuracy of localization and size of Optic Disc is approximately 98%. It indicates that this method is useful for retinal image analysis of diabetic retinopathy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Retina blood vessel detection for diabetic retinopathy diagnosis(2019-03-28); 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.