Liver fibrosis identification based on ultrasound images captured under varied imaging protocols.
- Author:
Gui-tao CAO
1
;
Peng-fei SHI
;
Bing HU
Author Information
1. Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Fractals;
Humans;
Image Enhancement;
methods;
Image Interpretation, Computer-Assisted;
methods;
Information Storage and Retrieval;
methods;
Liver Cirrhosis;
diagnostic imaging;
Pattern Recognition, Automated;
methods;
Reproducibility of Results;
Sensitivity and Specificity;
Ultrasonography
- From:
Journal of Zhejiang University. Science. B
2005;6(11):1107-1114
- CountryChina
- Language:English
-
Abstract:
Diagnostic ultrasound is a useful and noninvasive method in clinical medicine. Although due to its qualitative, subjective and experience-based nature, ultrasound image interpretation 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 a group of 99 in-vivo liver fibrosis images from 18 patients, as well as other 273 liver images from 18 normal human volunteers.
