CLC number: R445; TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 10
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CAO Gui-tao, SHI Peng-fei, HU Bing. Liver fibrosis identification based on ultrasound images captured under varied imaging protocols[J]. Journal of Zhejiang University Science B, 2005, 6(11): 1107-1114.
@article{title="Liver fibrosis identification based on ultrasound images captured under varied imaging protocols",
author="CAO Gui-tao, SHI Peng-fei, HU Bing",
journal="Journal of Zhejiang University Science B",
volume="6",
number="11",
pages="1107-1114",
year="2005",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2005.B1107"
}
%0 Journal Article
%T Liver fibrosis identification based on ultrasound images captured under varied imaging protocols
%A CAO Gui-tao
%A SHI Peng-fei
%A HU Bing
%J Journal of Zhejiang University SCIENCE B
%V 6
%N 11
%P 1107-1114
%@ 1673-1581
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.B1107
TY - JOUR
T1 - Liver fibrosis identification based on ultrasound images captured under varied imaging protocols
A1 - CAO Gui-tao
A1 - SHI Peng-fei
A1 - HU Bing
J0 - Journal of Zhejiang University Science B
VL - 6
IS - 11
SP - 1107
EP - 1114
%@ 1673-1581
Y1 - 2005
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2005.B1107
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.
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Open peer comments: Debate/Discuss/Question/Opinion
<1>
manju@free<manju\_r\_99@yahoo.com>
2012-01-16 16:19:09
may be useful