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Now-a-days Renal Calculi is becoming a most common disease in both men and women. Calculi are due to abnormal collection of certain chemicals like oxalate, phosphate and uric acid. These calculi can be present in kidney, urethra or in urinary bladder. Most of the previous study in diagnosis of Renal Calculi spots out the presence or absence of the calculi in the kidney. In this paper we propose an algorithm to detect the renal calculi and to find the level of the calculi. It is more helpful to change the diet conditions. In this paper, we presented a method for ultrasound kidney image diagnosis for calculi and to find the size of the calculi using Advanced seeded region growing based segmentation. With segmented portions of the images the intensity threshold values helps to classify the level of the calculi as early calculi, medium calculi and large calculi. The Advanced Seeded Region Growing based image segmentation process homogeneous region depends on the image features. First, the regions of interest (ROIs) extracted from the pre-processed image. Second, the initial seed is selected based on ROIs extracted from the image. The size of the growing regions depends on this look up table entries. After completing region growing, region merging is used to suppress the high frequency artifacts. The diagnosis process is done based on the intensity threshold variation obtained from the segmented portions of the image and level of the calculi is found out.

Renal Calculi Detection in Ultrasound images and Diagnosis of Images using Image Segmentation