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Abstract

In this paper, a comparative study of different edge detection methods had been done to determine the vessel wall elasticity for early diagnosis of the Deep Vein Thrombosis condition. Currently, in most research found that the measurement of the vessel detection conducted solely on the raw image obtains from the ultrasound. Thus, the precision of the measurement could be controvertible from time to time. As a matter of fact, the image consists of its individual characteristics or properties that cannot be verified distinctly. Therefore, various methods of edge detection techniques had been applied to the B-mode ultrasound image. There are several edge detection techniques available for pre-processing in computer vision. Though, Canny, Sobel and Roberts are some of the most applied methods. This paper compares each of the methods by the evaluation of the Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) of the output image. The evaluations are using Matlab software, the algorithms applied on the B-mode image of 10 subjects that had been volunteering for the purpose of the study. Both the MSE and the PSNR were in numeric values, that includes the vessel wall elasticity measurement of the popliteal vein, therefore, the performance of the algorithm is determined.