Liver fibrosis identification based on ultrasound images

Cao Guitao; Shi Pengfei; Hu Bing

Liver fibrosis identification based on ultrasound images

Cao Guitao, Shi Pengfei, Hu Bing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages	6317-6320
Number of pages	4
State	Published - 2005
Externally published	Yes
Event	2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China Duration: 1 Sep 2005 → 4 Sep 2005

Publication series

Name	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	7 VOLS
ISSN (Print)	0589-1019

Conference

Conference	2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/Territory	China
City	Shanghai
Period	1/09/05 → 4/09/05

Keywords

Edge co-occurrence matrix
Fisher classifier
Fractal
Liver fibrosis
Support vector machine

Cite this

Guitao, C., Pengfei, S., & Bing, H. (2005). Liver fibrosis identification based on ultrasound images. In Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 (pp. 6317-6320). Article 1615942 (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings; Vol. 7 VOLS).

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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.",

keywords = "Edge co-occurrence matrix, Fisher classifier, Fractal, Liver fibrosis, Support vector machine",

author = "Cao Guitao and Shi Pengfei and Hu Bing",

year = "2005",

language = "英语",

isbn = "0780387406",

series = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

pages = "6317--6320",

booktitle = "Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005",

note = "2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 ; Conference date: 01-09-2005 Through 04-09-2005",

}

Guitao, C, Pengfei, S & Bing, H 2005, Liver fibrosis identification based on ultrasound images. in Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005., 1615942, Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, vol. 7 VOLS, pp. 6317-6320, 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005, Shanghai, China, 1/09/05.

Liver fibrosis identification based on ultrasound images. / Guitao, Cao; Pengfei, Shi; Bing, Hu.
Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005. 2005. p. 6317-6320 1615942 (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings; Vol. 7 VOLS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Liver fibrosis identification based on ultrasound images

AU - Guitao, Cao

AU - Pengfei, Shi

AU - Bing, Hu

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

KW - Edge co-occurrence matrix

KW - Fisher classifier

KW - Fractal

KW - Liver fibrosis

KW - Support vector machine

UR - https://www.scopus.com/pages/publications/33846915192

M3 - 会议稿件

AN - SCOPUS:33846915192

SN - 0780387406

SN - 9780780387409

T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

SP - 6317

EP - 6320

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

T2 - 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

Y2 - 1 September 2005 through 4 September 2005

ER -

Liver fibrosis identification based on ultrasound images

Abstract

Publication series

Conference

Keywords

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Cite this