Liver Fibrosis Identification Based on Ultrasound Images

Author

Cao, Guitao ; Shi, Pengfei ; Hu, Bing

Author_Institution

Inst. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ.

fYear

2006

Firstpage

6317

Lastpage

6320

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

Keywords

biomedical ultrasonics; entropy; feature extraction; fractals; image classification; image texture; liver; medical image processing; support vector machines; Fisher linear classifier; clinical medicine; diagnostic ultrasound images; entropy; feature extraction; fractal dimension; liver fibrosis identification; machine settings; scanning frequency; support vector machine; texture edge cooccurrence matrix; Biomedical imaging; Entropy; Feature extraction; Fractals; Frequency; Liver; Medical diagnostic imaging; Support vector machine classification; Support vector machines; Ultrasonic imaging; Fisher classifier; Fractal; Liver fibrosis; edge co-occurrence matrix; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Conference_Location

Shanghai

Print_ISBN

0-7803-8741-4

Type

conf

DOI

10.1109/IEMBS.2005.1615942

Filename

1615942