Title: A review of methods for detection and segmentation of kidney stones from CT scan images using image processing method

Authors: Vahid Nazmdeh; Somayeh Saraf Esmaili

Addresses: Department of Biomedical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran ' Department of Biomedical Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran

Abstract: Kidney stone disease is on the rise today. Kidney stones are hard deposits often due to the occurrence of high concentration of minerals and salts in the urine. Computed Tomography (CT) has become the gold standard for diagnosing kidney stones. The aim of this study was to review Computer-Aided Detection (CAD) algorithms for the detection of kidney stones in CT images. Owing to the presence of different organs in CT images, image segmentation and Region of Interest (ROI) selection is one of the challenges in this field, and choosing a suitable method for image segmentation can increase the accuracy, sensitivity and efficiency of the system. In this article, we provide a brief overview of recent work in the diagnosis of kidney stones using image processing techniques.

Keywords: kidney stone; computed tomography; medical imaging; image processing; segmentation; detection; region of interest; feature extraction; classification.

DOI: 10.1504/IJCCPS.2022.124877

International Journal of Cybernetics and Cyber-Physical Systems, 2022 Vol.1 No.2, pp.157 - 168

Received: 06 Sep 2021
Accepted: 04 Dec 2021
Published online: 13 Aug 2022 *

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