Presenting a combined method in digital image processing to diagnose blood vessel damage
Subject Areas : Electrical engineering (electronics, telecommunications, power, control)
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Keywords: Digital image processing, vessel extraction and segmentation, noise removal, blood vessel damage, value key database,
Abstract :
Damage to blood vessels is one of the most common causes of blindness in the world. Identification of vessels from retinal images plays an important role in the diagnosis of eye diseases such as damage to blood vessels. The extraction of retinal blood vessels is done manually by the doctor, which is time-consuming and difficult, and due to the dependence on the individual, it is associated with errors. It is difficult to identify small vessels in retinal images due to low contrast and rotation. In this article, a new and combined method for extracting blood vessels from retinal digital images is presented. The steps of this method are as follows: removal of noise in retinal images, extraction of central lines of vessels, use of area expansion and removal of noise, application of local processing operations based on the statistical characteristics of the image to improve the contrast of vessels and background, template matching operation to remove the effect Optical disk, applying morphological operations to fill the space between the borders of the vessels and finally extract blood vessels in retinal images. Compared to other methods, the results of this algorithm are a very suitable option for diagnosing blood vessel damage by digital image processing. To evaluate the proposed method, the available images from the value key database were used and the values of sensitivity, precision and accuracy were calculated and the average of these criteria was reported as 0.92896, 0.98965, 0.91756 and 0.96578 respectively. The values of these criteria indicate the satisfactory performance of the proposed method compared to other methods.
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