Segmentation of Renal Calculi Using Squared Euclidean Distance Method

In this proposed Contour based Squared Euclidean Distance (CSED) segmentation method, initially the preprocessing techniques are applied to reduce the noise from the ultra sound kidney images. Then Squared Euclidean Distance (SED) is determined between the training image centroid values and the selected regions centroid values. In addition, the usage of ANFIS in supervised learning has made the technique more efficient than the previous techniques. Thus the obtained error is minimized when compared to the existing algorithm that leads to high efficiency.