An automatic partitioning method of CTA head-neck image

Zhaoxuan Gong; Wenjun Tan; Jinzhu Yang; Meng Jia Xu; Zijian Bian; Da Zhe Zhao

doi:10.1109/WCICA.2014.7053258

An automatic partitioning method of CTA head-neck image

Zhaoxuan Gong, Wenjun Tan, Jinzhu Yang, Meng Jia Xu, Zijian Bian, Da Zhe Zhao

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

1 Scopus citations

Abstract

The segmentation of vessel in CTA is a challenging task mainly due to bone contact from different regions. The proposed method considers a spatial structure features based partition algorithm which can be separated into three sub-volumes. Firstly, a region growing method was brought forward to remove the background interference, and then added up the bone pixel number in the canter region of head image with specific rules to separate from the proximal layer and the middle layer. Finally, the structure feature of bone profile in neck image was used to separate from middle layer and the distal layer. The experiment results illustrate that the proposed method effectively separate the CTA head-neck image into three sub-volumes in terms of real-timeness, effectiveness and robustness.

Original language	English (US)
Title of host publication	Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3283-3285
Number of pages	3
Edition	March
ISBN (Electronic)	9781479958252
DOIs	https://doi.org/10.1109/WCICA.2014.7053258
State	Published - Mar 2 2015
Externally published	Yes
Event	2014 11th World Congress on Intelligent Control and Automation, WCICA 2014 - Shenyang, China Duration: Jun 29 2014 → Jul 4 2014

Publication series

Name	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
Number	March
Volume	2015-March

Conference

Conference	2014 11th World Congress on Intelligent Control and Automation, WCICA 2014
Country/Territory	China
City	Shenyang
Period	6/29/14 → 7/4/14

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Software
Computer Science Applications

Keywords

CTA
Region growing
Spatial structure
Vessel

Access to Document

10.1109/WCICA.2014.7053258

Cite this

Gong, Z., Tan, W., Yang, J., Xu, M. J., Bian, Z., & Zhao, D. Z. (2015). An automatic partitioning method of CTA head-neck image. In Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014 (March ed., pp. 3283-3285). Article 7053258 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); Vol. 2015-March, No. March). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCICA.2014.7053258

Gong, Zhaoxuan ; Tan, Wenjun ; Yang, Jinzhu et al. / An automatic partitioning method of CTA head-neck image. Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014. March. ed. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 3283-3285 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); March).

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title = "An automatic partitioning method of CTA head-neck image",

abstract = "The segmentation of vessel in CTA is a challenging task mainly due to bone contact from different regions. The proposed method considers a spatial structure features based partition algorithm which can be separated into three sub-volumes. Firstly, a region growing method was brought forward to remove the background interference, and then added up the bone pixel number in the canter region of head image with specific rules to separate from the proximal layer and the middle layer. Finally, the structure feature of bone profile in neck image was used to separate from middle layer and the distal layer. The experiment results illustrate that the proposed method effectively separate the CTA head-neck image into three sub-volumes in terms of real-timeness, effectiveness and robustness.",

keywords = "CTA, Region growing, Spatial structure, Vessel",

author = "Zhaoxuan Gong and Wenjun Tan and Jinzhu Yang and Xu, {Meng Jia} and Zijian Bian and Zhao, {Da Zhe}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 11th World Congress on Intelligent Control and Automation, WCICA 2014 ; Conference date: 29-06-2014 Through 04-07-2014",

year = "2015",

month = mar,

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doi = "10.1109/WCICA.2014.7053258",

language = "English (US)",

series = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Gong, Z, Tan, W, Yang, J, Xu, MJ, Bian, Z & Zhao, DZ 2015, An automatic partitioning method of CTA head-neck image. in Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014. March edn, 7053258, Proceedings of the World Congress on Intelligent Control and Automation (WCICA), no. March, vol. 2015-March, Institute of Electrical and Electronics Engineers Inc., pp. 3283-3285, 2014 11th World Congress on Intelligent Control and Automation, WCICA 2014, Shenyang, China, 6/29/14. https://doi.org/10.1109/WCICA.2014.7053258

An automatic partitioning method of CTA head-neck image. / Gong, Zhaoxuan; Tan, Wenjun; Yang, Jinzhu et al.
Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014. March. ed. Institute of Electrical and Electronics Engineers Inc., 2015. p. 3283-3285 7053258 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); Vol. 2015-March, No. March).

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

TY - GEN

T1 - An automatic partitioning method of CTA head-neck image

AU - Gong, Zhaoxuan

AU - Tan, Wenjun

AU - Yang, Jinzhu

AU - Xu, Meng Jia

AU - Bian, Zijian

AU - Zhao, Da Zhe

PY - 2015/3/2

Y1 - 2015/3/2

N2 - The segmentation of vessel in CTA is a challenging task mainly due to bone contact from different regions. The proposed method considers a spatial structure features based partition algorithm which can be separated into three sub-volumes. Firstly, a region growing method was brought forward to remove the background interference, and then added up the bone pixel number in the canter region of head image with specific rules to separate from the proximal layer and the middle layer. Finally, the structure feature of bone profile in neck image was used to separate from middle layer and the distal layer. The experiment results illustrate that the proposed method effectively separate the CTA head-neck image into three sub-volumes in terms of real-timeness, effectiveness and robustness.

AB - The segmentation of vessel in CTA is a challenging task mainly due to bone contact from different regions. The proposed method considers a spatial structure features based partition algorithm which can be separated into three sub-volumes. Firstly, a region growing method was brought forward to remove the background interference, and then added up the bone pixel number in the canter region of head image with specific rules to separate from the proximal layer and the middle layer. Finally, the structure feature of bone profile in neck image was used to separate from middle layer and the distal layer. The experiment results illustrate that the proposed method effectively separate the CTA head-neck image into three sub-volumes in terms of real-timeness, effectiveness and robustness.

KW - CTA

KW - Region growing

KW - Spatial structure

KW - Vessel

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Gong Z, Tan W, Yang J, Xu MJ, Bian Z, Zhao DZ. An automatic partitioning method of CTA head-neck image. In Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014. March ed. Institute of Electrical and Electronics Engineers Inc. 2015. p. 3283-3285. 7053258. (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); March). doi: 10.1109/WCICA.2014.7053258

An automatic partitioning method of CTA head-neck image

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All Science Journal Classification (ASJC) codes

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