Automated segmentation of gallstones in ultrasound images

Gallstones are solid particles formed from bile in the gall bladder. In this paper, we propose a technique to automatically detect gallstones in ultrasound images, christened as, automated gallstone segmentation (AGS) technique. Speckle noise in the ultrasound image is first suppressed using anisotropic diffusion technique. The edges are then enhanced using unsharp filtering. NCUT segmentation technique is then put to use to segment the image. Afterwards, edges are detected using Sobel edge detection. Further, edge thickening process is used to smoothen the edges and probability maps are generated using floodfill technique. Then, the image is scribbled using automatic scribbling technique. Finally, we get the segmented gallstone within the gallbladder using the closed form matting technique.