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Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

by Ayman M. Abdalla1,*, Mohammad Abu Awad2, Omar AlZoubi2

1 Department of Computer Science, Al-Zaytoonah University of Jordan, Amman, 11733, Jordan
2 Department of Computer Science, Jordan University of Science and Technology, Irbid, 22110, Jordan
3 Department of Water and Environmental Engineering, Al-Huson University College, Al-Balqa Applied University, Irbid, Jordan

* Corresponding Author: Ayman M. Abdalla. Email: email

Computers, Materials & Continua 2022, 72(1), 797-814. https://doi.org/10.32604/cmc.2022.024913

Abstract

The enlarged veins in the pampiniform venous plexus, known as varicocele disease, are typically identified using ultrasound scans. The medical diagnosis of varicocele is based on examinations made in three positions taken to the right and left testicles of the male patient. The proposed system is designed to determine whether a patient is affected. Varicocele is more frequent on the left side of the scrotum than on the right and physicians commonly depend on the supine position more than other positions. Therefore, the experimental results of this study focused on images taken in the supine position of the left testicles of patients. There are two possible vein structures in each image: a cross-section (circular) and a tube (non-circular) structure. This proposed system identifies dilated (varicocele) veins of these structures in ultrasound images in three stages: preprocessing, processing, and detection and measurement. These three stages are applied in three different color modes: Grayscale, Red-Green-Blue (RGB), and Hue, Saturation, and Value (HSV). In the preprocessing stage, the region of interest enclosing the pampiniform plexus area is extracted using a median filter and threshold segmentation. Then, the processing stage employs different filters to perform image denoising. Finally, edge detection is applied in multiple steps and the detected veins are measured to determine if dilated veins exist. Overall implementation results showed the proposed system is faster and more effective than the previous work.

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Cite This Article

APA Style
Abdalla, A.M., Awad, M.A., AlZoubi, O., Al-Samrraie, L.A. (2022). Automatic segmentation and detection system for varicocele using ultrasound images. Computers, Materials & Continua, 72(1), 797-814. https://doi.org/10.32604/cmc.2022.024913
Vancouver Style
Abdalla AM, Awad MA, AlZoubi O, Al-Samrraie LA. Automatic segmentation and detection system for varicocele using ultrasound images. Comput Mater Contin. 2022;72(1):797-814 https://doi.org/10.32604/cmc.2022.024913
IEEE Style
A. M. Abdalla, M. A. Awad, O. AlZoubi, and L.A. Al-Samrraie, “Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images,” Comput. Mater. Contin., vol. 72, no. 1, pp. 797-814, 2022. https://doi.org/10.32604/cmc.2022.024913



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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