title: Liver fibrosis identification based on ultrasound images.
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.
authors.affiliation: Institute of Image Processing and Pattern recognition, Shanghai Jiaotong University; Shanghai 200030, China. maggie@sjtu.edu.cn.
authors.forename: Guitao
authors.initials: G
authors.lastname: Cao
authors.forename: Pengfei
authors.initials: P
authors.lastname: Shi
authors.forename: Bing
authors.initials: B
authors.lastname: Hu