Breast tissue segmentation using KFCM algorithm on MR images

Hong Song; Feifei Sun; Xiangfei Cui; Xiangbin Zhu; Qingjie Zhao

doi:10.1007/978-3-642-38466-0_62

Breast tissue segmentation using KFCM algorithm on MR images

Hong Song^*, Feifei Sun, Xiangfei Cui, Xiangbin Zhu, Qingjie Zhao

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Institute of Technology

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

3 Citations (Scopus)

Abstract

Breast MRI segmentation is useful for assisting the clinician to detect suspicious regions. In this paper, an effective approach is proposed for segmenting the breast into different regions, each corresponding to a different tissue. The segmentation work flow comprises three key steps: MR Images preprocessing, locating breast-skin and breast-chest wall boundary by using OTSU thresholding algorithm, and segmenting fibroglandular and fatty tissues with applying the kernel-based fuzzy clustering algorithm (KFCM). The proposed method was applied to segment the clinical breast MR images. Experimental results have been shown visually and achieve reasonable consistency.

Original language	English
Title of host publication	Proceedings of 2013 Chinese Intelligent Automation Conference - Intelligent Information Processing
Pages	555-563
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-38466-0_62
Publication status	Published - 2013
Event	2013 Chinese Intelligent Automation Conference, CIAC 2013 - Yangzhou, Jiangsu, China Duration: 23 Aug 2013 → 25 Aug 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	256 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	2013 Chinese Intelligent Automation Conference, CIAC 2013
Country/Territory	China
City	Yangzhou, Jiangsu
Period	23/08/13 → 25/08/13

Keywords

Breast MRI
Breast tissue segmentation
KFCM

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10.1007/978-3-642-38466-0_62

Cite this

@inproceedings{2bb308197f7442deb4e8306b44f99a5b,

title = "Breast tissue segmentation using KFCM algorithm on MR images",

abstract = "Breast MRI segmentation is useful for assisting the clinician to detect suspicious regions. In this paper, an effective approach is proposed for segmenting the breast into different regions, each corresponding to a different tissue. The segmentation work flow comprises three key steps: MR Images preprocessing, locating breast-skin and breast-chest wall boundary by using OTSU thresholding algorithm, and segmenting fibroglandular and fatty tissues with applying the kernel-based fuzzy clustering algorithm (KFCM). The proposed method was applied to segment the clinical breast MR images. Experimental results have been shown visually and achieve reasonable consistency.",

keywords = "Breast MRI, Breast tissue segmentation, KFCM",

author = "Hong Song and Feifei Sun and Xiangfei Cui and Xiangbin Zhu and Qingjie Zhao",

year = "2013",

doi = "10.1007/978-3-642-38466-0_62",

language = "English",

isbn = "9783642384653",

series = "Lecture Notes in Electrical Engineering",

pages = "555--563",

booktitle = "Proceedings of 2013 Chinese Intelligent Automation Conference - Intelligent Information Processing",

note = "2013 Chinese Intelligent Automation Conference, CIAC 2013 ; Conference date: 23-08-2013 Through 25-08-2013",

}

Song, H, Sun, F, Cui, X, Zhu, X & Zhao, Q 2013, Breast tissue segmentation using KFCM algorithm on MR images. in Proceedings of 2013 Chinese Intelligent Automation Conference - Intelligent Information Processing. Lecture Notes in Electrical Engineering, vol. 256 LNEE, pp. 555-563, 2013 Chinese Intelligent Automation Conference, CIAC 2013, Yangzhou, Jiangsu, China, 23/08/13. https://doi.org/10.1007/978-3-642-38466-0_62

Breast tissue segmentation using KFCM algorithm on MR images. / Song, Hong; Sun, Feifei; Cui, Xiangfei et al.
Proceedings of 2013 Chinese Intelligent Automation Conference - Intelligent Information Processing. 2013. p. 555-563 (Lecture Notes in Electrical Engineering; Vol. 256 LNEE).

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

TY - GEN

T1 - Breast tissue segmentation using KFCM algorithm on MR images

AU - Song, Hong

AU - Sun, Feifei

AU - Cui, Xiangfei

AU - Zhu, Xiangbin

AU - Zhao, Qingjie

PY - 2013

Y1 - 2013

N2 - Breast MRI segmentation is useful for assisting the clinician to detect suspicious regions. In this paper, an effective approach is proposed for segmenting the breast into different regions, each corresponding to a different tissue. The segmentation work flow comprises three key steps: MR Images preprocessing, locating breast-skin and breast-chest wall boundary by using OTSU thresholding algorithm, and segmenting fibroglandular and fatty tissues with applying the kernel-based fuzzy clustering algorithm (KFCM). The proposed method was applied to segment the clinical breast MR images. Experimental results have been shown visually and achieve reasonable consistency.

AB - Breast MRI segmentation is useful for assisting the clinician to detect suspicious regions. In this paper, an effective approach is proposed for segmenting the breast into different regions, each corresponding to a different tissue. The segmentation work flow comprises three key steps: MR Images preprocessing, locating breast-skin and breast-chest wall boundary by using OTSU thresholding algorithm, and segmenting fibroglandular and fatty tissues with applying the kernel-based fuzzy clustering algorithm (KFCM). The proposed method was applied to segment the clinical breast MR images. Experimental results have been shown visually and achieve reasonable consistency.

KW - Breast MRI

KW - Breast tissue segmentation

KW - KFCM

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U2 - 10.1007/978-3-642-38466-0_62

DO - 10.1007/978-3-642-38466-0_62

M3 - Conference contribution

AN - SCOPUS:84885198900

SN - 9783642384653

T3 - Lecture Notes in Electrical Engineering

SP - 555

EP - 563

BT - Proceedings of 2013 Chinese Intelligent Automation Conference - Intelligent Information Processing

T2 - 2013 Chinese Intelligent Automation Conference, CIAC 2013

Y2 - 23 August 2013 through 25 August 2013

ER -

Breast tissue segmentation using KFCM algorithm on MR images

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Keywords

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