Automated Kidney Stone Detection Using Image Processing Techniques

Kidney stones, also referred to as renal calculi, are solid masses made from crystals. It's vital to detect the precise and accurate position of urinary calculus for surgical operations. Since the ultrasound images contain speckle noise, therefore it's difficult to detect the urinary calculus manually and hence it's required to use automated techniques in detection of kidney stones in ultrasound images. Ultrasound imaging is one among the available imaging techniques used for diagnosis of kidney abnormalities, which can be like change in shape and position and swelling of limb; there also are other kidney abnormalities like formation of stones, cysts, blockage of urine, congenital anomalies, and cancerous cells. This challenge can be overcome by employing suitable image processing techniques. This paper proposes an image processing technique to identify kidney stones automatically without human intervention. This report also presents the literature review and comparative study of varied algorithms available within the existing literature for urinary calculus detection in human bodies.