Abstract
Diagnostic ultrasound is one of useful and noninvasive tools for clinical medicine. However, due to its qualitative, subjective and experience-based nature, ultrasound images can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, Fisher linear classifier and Support Vector Machine are employed to test on a group of 99 liver fibrosis images from 18 patients, as well as other 273 healthy liver images from 18 specimens.
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