Enhanced Kidney Stone Identification Using Ultrasonographic Images in Image Processing

Authors

  • Pil-Kee Min Department of Informatics, The University of Electro-Communications (UEC), Tokyo, 182-8585, Japan
  • Debnath Bhattacharyya Computer Science and Engineering Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India
  • Byung Chan Min Hanbat National University, Department of Industrial & Management Engineering, 34158, Daejeon, Republic of Korea
  • Tae-Hoon Kim School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
  • Kazuyuki Mito Department of Informatics, The University of Electro-Communications (UEC), Tokyo, 182-8585, Japan

Keywords:

kidney stones, computed tomography, image processing, Ultrasonographic Images

Abstract

Stones, cysts, urinary tract obstruction, birth defects, and malignant cells are just some of the problems that may manifest in the kidneys. Kidney stone disease occurs when a stone is formed in the kidney or elsewhere in the urinary system. There may be no ill effects from passing the little stone. Pain in the lower back or abdomen may be experienced if a stone develops to a size greater than 5 millimetres and blocks the ureter. Thus, a method of detecting kidney stones is required to prevent future medical complications. The primary goal of this work is to use different image processing algorithms to identify the kidney stone in a digital ultrasound picture of the kidney. Yet, owing to poor contrast and the presence of speckle noise, the ultrasound-generated picture is unfit for further processing. Although improving the ultrasound picture quality by denoising methods was also a focus of the research, this was also investigated. More so, the improved ultrasound picture is utilised to pinpoint the precise location of the stone. The primary objective of this work was to provide a simple and efficient method for locating kidney stone. As this can be done on any computer, any healthy person may potentially check for a kidney stone using ultrasound and begin the process of dissolving it right away. Depending on the size and position of the lesion, these methods greatly aid the doctor in proceeding with further treatment.

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Published

10.11.2023

How to Cite

Min, P.-K. ., Bhattacharyya, D. ., Min, B. C. ., Kim, T.-H. ., & Mito, K. . (2023). Enhanced Kidney Stone Identification Using Ultrasonographic Images in Image Processing. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 477–484. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3809

Issue

Vol. 12 No. 4s (2024)

Section

Research Article

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