Automatic cortical sulcal parcellation based on surface principal direction flow field tracking

Gang Li; Lei Guo; Jingxin Nie; Tianming Liu

doi:10.1007/978-3-642-02498-6_17

Automatic cortical sulcal parcellation based on surface principal direction flow field tracking

Gang Li
, Lei Guo
, Jingxin Nie
, Tianming Liu

School of Automation

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

1 Scopus citations

Abstract

Automatic parcellation of cortical surfaces into sulcal based regions is of great importance in structural and functional mapping of human brain. In this paper, a novel method is proposed for automatic cortical sulcal parcellation based on the geometric characteristics of the cortical surface including its principal curvatures and principal directions. This method is composed of two major steps: 1) employing the hidden Markov random field model (HMRF) and the expectation maximization (EM) algorithm on the maximum principal curvatures of the cortical surface for sulcal region segmentation, and 2) using a principal direction flow field tracking method on the cortical surface for sulcal basin segmentation. The flow field is obtained by diffusing the principal direction field on the cortical surface. The method has been successfully applied to the inner cortical surfaces of twelve healthy human brain MR images. Both quantitative and qualitative evaluation results demonstrate the validity and efficiency of the proposed method.

Original language	English
Title of host publication	Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings
Pages	202-214
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-02498-6_17
State	Published - 2009
Event	21st International Conference on Information Processing in Medical Imaging, IPMI 2009 - Williamsburg, VA, United States Duration: 5 Jul 2009 → 10 Jul 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5636 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Information Processing in Medical Imaging, IPMI 2009
Country/Territory	United States
City	Williamsburg, VA
Period	5/07/09 → 10/07/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Sulcal basin segmentation
Sulcal region segmentation

Access to Document

10.1007/978-3-642-02498-6_17

Cite this

Li, G., Guo, L., Nie, J., & Liu, T. (2009). Automatic cortical sulcal parcellation based on surface principal direction flow field tracking. In Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings (pp. 202-214). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5636 LNCS). https://doi.org/10.1007/978-3-642-02498-6_17

Li, Gang ; Guo, Lei ; Nie, Jingxin et al. / Automatic cortical sulcal parcellation based on surface principal direction flow field tracking. Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings. 2009. pp. 202-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Automatic cortical sulcal parcellation based on surface principal direction flow field tracking",

abstract = "Automatic parcellation of cortical surfaces into sulcal based regions is of great importance in structural and functional mapping of human brain. In this paper, a novel method is proposed for automatic cortical sulcal parcellation based on the geometric characteristics of the cortical surface including its principal curvatures and principal directions. This method is composed of two major steps: 1) employing the hidden Markov random field model (HMRF) and the expectation maximization (EM) algorithm on the maximum principal curvatures of the cortical surface for sulcal region segmentation, and 2) using a principal direction flow field tracking method on the cortical surface for sulcal basin segmentation. The flow field is obtained by diffusing the principal direction field on the cortical surface. The method has been successfully applied to the inner cortical surfaces of twelve healthy human brain MR images. Both quantitative and qualitative evaluation results demonstrate the validity and efficiency of the proposed method.",

keywords = "Sulcal basin segmentation, Sulcal region segmentation",

author = "Gang Li and Lei Guo and Jingxin Nie and Tianming Liu",

year = "2009",

doi = "10.1007/978-3-642-02498-6\_17",

language = "英语",

isbn = "3642024971",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "202--214",

booktitle = "Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings",

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}

Li, G, Guo, L, Nie, J & Liu, T 2009, Automatic cortical sulcal parcellation based on surface principal direction flow field tracking. in Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5636 LNCS, pp. 202-214, 21st International Conference on Information Processing in Medical Imaging, IPMI 2009, Williamsburg, VA, United States, 5/07/09. https://doi.org/10.1007/978-3-642-02498-6_17

Automatic cortical sulcal parcellation based on surface principal direction flow field tracking. / Li, Gang; Guo, Lei; Nie, Jingxin et al.
Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings. 2009. p. 202-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5636 LNCS).

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

TY - GEN

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AU - Nie, Jingxin

AU - Liu, Tianming

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N2 - Automatic parcellation of cortical surfaces into sulcal based regions is of great importance in structural and functional mapping of human brain. In this paper, a novel method is proposed for automatic cortical sulcal parcellation based on the geometric characteristics of the cortical surface including its principal curvatures and principal directions. This method is composed of two major steps: 1) employing the hidden Markov random field model (HMRF) and the expectation maximization (EM) algorithm on the maximum principal curvatures of the cortical surface for sulcal region segmentation, and 2) using a principal direction flow field tracking method on the cortical surface for sulcal basin segmentation. The flow field is obtained by diffusing the principal direction field on the cortical surface. The method has been successfully applied to the inner cortical surfaces of twelve healthy human brain MR images. Both quantitative and qualitative evaluation results demonstrate the validity and efficiency of the proposed method.

AB - Automatic parcellation of cortical surfaces into sulcal based regions is of great importance in structural and functional mapping of human brain. In this paper, a novel method is proposed for automatic cortical sulcal parcellation based on the geometric characteristics of the cortical surface including its principal curvatures and principal directions. This method is composed of two major steps: 1) employing the hidden Markov random field model (HMRF) and the expectation maximization (EM) algorithm on the maximum principal curvatures of the cortical surface for sulcal region segmentation, and 2) using a principal direction flow field tracking method on the cortical surface for sulcal basin segmentation. The flow field is obtained by diffusing the principal direction field on the cortical surface. The method has been successfully applied to the inner cortical surfaces of twelve healthy human brain MR images. Both quantitative and qualitative evaluation results demonstrate the validity and efficiency of the proposed method.

KW - Sulcal basin segmentation

KW - Sulcal region segmentation

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Li G, Guo L, Nie J, Liu T. Automatic cortical sulcal parcellation based on surface principal direction flow field tracking. In Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings. 2009. p. 202-214. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-02498-6_17

Automatic cortical sulcal parcellation based on surface principal direction flow field tracking

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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