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Abstract
Low brightness contrast and grey level discontinuities of the ultrasonic liver image make it difficult to segment the object and the background and to extract the edges of the object using the global optimal threshold method. In this paper, we investigate a local optimal threshold method for the segmentation of ultrasound liver image. First of all, the distributed energy of the ultrasound liver image is estimated in the proposed liver segmentation. Then, the polynomials are fitted from the distributed energy data and a peak zone is defined from the minimum of the fitted polynomials. Finally, a few blocked images are divided from the number of the peak zones. Furthermore, multiple local optimal thresholds are obtained from the blocked images using Otsu’s method, and the ultrasonic liver image is segmented according to all local optimal thresholds. Experimental results validate the segmentation and edge detection of liver in the ultrasound images.
This work was supported by the National Natural Science Foundation of China under grant No60875023 and The Fundamental Research Funds for the Central Universities (ZZ1134 and ZZ1013).