The invention discloses a method for constructing a similarity matrix in the ultrasound image Ncut segmentation process. The method includes the following steps of firstly, preprocessing an ultrasound image; secondly, conducting over-segmentation on the ultrasound image through a simple linear iterative clustering method to generate even-medium sub-areas with irregular borders; thirdly, enabling average gray level information of all the sub-areas to serve as one characteristic for constructing the Ncut similarity matrix, and calculating the texture characteristics of all the sub-areas through a gray level co-occurrence matrix at the same time, wherein the texture characteristics totally include 24 characteristics with six characteristics in each of the four directions, and the 24 data are combined to form a texture characteristic vector, namely, another characteristic for constructing the Ncut similarity matrix; fourthly, calculating the distance between the characteristics of every two adjacent sub-areas, and combining the sub-areas according to a certain proportion to form a new Ncut similarity matrix calculation formula. When the method is used for segmenting the ultrasound image based on Ncut clustering, a good segmentation result is obtained, the problems that the ultrasound image is high in noise and low in contrast ratio are solved, and the tumor areas and the background areas can be effectively separated.