AN AUTOMATIC ENERGY-BASED REGION GROWING METHOD FOR ULTRASOUND IMAGE SEGMENTATION

Segmentation for lesion region in ultrasound images is crucial for computer-aided diagnosis system. But it has always been a difficult task due to the defects inherent in the ultrasound images. In this paper, we propose an automatic energy-based region growing (AERG) method to automatically segment the lesion region in ultrasound images of liver. At first, the seed point of lesion region is automatically selected by sparse reconstruction algorithm. Then the region growing process is controlled by a novel energy function including both internal and external energy, so as to make the edge of the region converge to the contour of the lesion accurately and keep a small internal difference at the same time. Experiment results show that our method could improve the segmentation accuracy in comparison with other four often used segmentation methods.