Segmentation of renal calculi in ultrasound images

Abstract

An algorithm proposed by Sridhar and Kumaravel is extended to include a framework for the detection of renal calculi. Calculi occur due to abnormal collection of certain chemicals like oxalate, phosphate and uric acid. These calculi can be present in the kidney, ureter or urinary bladder. Performance analysis is done to a set of five known algorithms using parameters such as success rate in calculi detection, border error metric and time. The framework is constructed by combining the best algorithm based on the performance analysis and a procedure to validate the detected calculi using the shadow it casts in ultrasound images. Ultrasound images of 37 patients are used for testing the algorithm. The detected calculi based on the framework match those determined by expert clinicians in more than 95% of the cases.

• Kidney Stones
• Renal Calculi
• Nephrolithiasis
• Automatic Segmentation