Ultrasound image segmentation with multilevel threshold based on differential search algorithm

Ultrasound (US) image segmentation plays a very important role in diagnostic imaging. In order to extract special tissues from images, this study proposes a new method for segmentation of US images. The proposed method uses multilevel threshold segmentation which is based on Otsu and differential search algorithm. Testing in simulation US images shows that the proposed algorithm has a better result of segmentation than the three existing methods, including region growing, the active contour model and k-means technique. The proposed method gets the highest F-m values and the smallest area errors in experiments. Vivo US images are also tested by the proposed method and it achieves a good segmentation result.