Segmentation of ultrasound breast tumors using seed region growth is a common method of computer-aided diagnosis. In order to realize automatic and fast locating of seed points, the demand of real-time online image segmentation is satisfied. According to the structural characteristics of ultrasound breast tumor image, and integrating the gray and spatial factors of the image, an algorithm based on iterative quadtree decomposition is proposed to transform the image splitting which meets a specific threshold into searching for seed regions, so as to realize automatic seed location. The verification results of 105 ultrasound breast tumor images show that this method not only satisfies the requirement of automatic location of the seed point within the tumor, with an accuracy of 94.28%. The average time consumed is 2.97 s. This method is also requires few parameters to be adjusted. Compared with other methods, the proposed method is more efficient.