Region Descriptors to Extricate Renal Calculi by Discerning Artifacts from Ultra Sound Images

The study presents a new technique to identify kidney stones and differentiate it from artifacts from an ultra sound scanned image. Image analysis plays vital role in medical diagnosis. Analysing texture is a major source of discrimination in image analysis. There are situations when artifacts are mistaken for kidney stones in Medical scan using Ultra sound technique. We are proposing a new approach wherein the kidney stones are differentiated from artifacts using various shape descriptive parameters. Various descriptors like Compactness, Dispersion, Smoothness and third moment are used in our method to differentiate artifacts and stones from ultrasound images. Basic regional descriptor characterizes the geometric properties of ROI (Region of Interest) whereas Invariant moment concentrates on the density of ROI. Initially the US image is polished using a Combinational approach of noise removal and this image is taken as input for our further analysis. Pre-processing is done to minimize the occurrence of artifacts. The potential calculi are extracted and the validity is tested using the above specified parameters. Test results show convincing difference in values between Calculi and Artifact. The suggested method efficiently helped in identifying Renal Calculi from Ultra sound Images.