Automatic segmentation of medical images for renal calculi and analysis.
Development of an automated system to identify renal calculi based on its physical characteristics is proposed. Calculi are due to abnormal collection of certain chemicals like oxalate, phosphate and uric arid. Renal calculi may be present in kidney, ureter or in urinary bladder. An algorithm is proposed to detect calculus using its shadow. The system also extracts the properties of calculi such as size, shape and location, which are vital for reliable diagnosis. This method has been implemented in the MATLAB/IDL platform and a considerable success rate is obtained.
Sridhar
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S
Center for Medical Electronics, School of ECE, Anna University, Chennai-600025, India.
Kumaravel
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N
D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007669:Kidney Calculi / Q000000981:diagnostic imaging*; D014463:Ultrasonography