A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging

Xiang Li; Jiao Long Cui; Chunyi Wen; Timothy K.H. Au; Keith D.K. Luk; Yong Hu

doi:10.1109/VECIMS.2012.6273208

A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging

Xiang Li, Jiao Long Cui, Chunyi Wen, Timothy K.H. Au, Keith D.K. Luk, Yong Hu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

Diffusion MR imaging technique has been developed in past decade to permit the detection of tissue water molecular diffusion at microscopic dimension and has been widely used to investigate the spinal cord parenchyma. The commonly used hand-drawn region of interest (ROI)-based segmentation in diffusion tensor imaging(DTI) analysis is highly labor-intensive and user-dependent. In this study, we aim to develop an automatic template (auto-template) based on anatomy knowledge and computational intelligence to extract the regional diffusion anisotropy pattern of cervical spinal cord. A total of 16 healthy volunteers were recruited in this study. Eleven axial diffusion tensor MR images covering C1 to C7 of cervical spinal cord were taken with single-shot spin-echo echo-planar imaging sequence on a 3T MR system. The fractional anisotropy (FA) value of anterior, lateral, posterior column of white matter and gray matter was measured using hand-drawn ROI and knowledge based computational intelligence method respectively. Knowledge based template showed the FA value in the anterior (0.737±0.009), lateral (0.827±0.011), posterior (0.854±0.007) column of white matter and gray matter (0.493±0.009) with higher inter-rater agreement than hand-drawn ROI method. The result suggested that knowledge based template is a convenient tool to extract the diffusion data in various parts of the cervical spinal cord with high accuracy and inter-rater reliability.

Original language	English
Title of host publication	VECIMS 2012 - 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Proceedings
Pages	9-12
Number of pages	4
DOIs	https://doi.org/10.1109/VECIMS.2012.6273208
Publication status	Published - 1 Nov 2012
Externally published	Yes
Event	2012 10th IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, VECIMS 2012 - Tianjin, China Duration: 2 Jul 2012 → 4 Jul 2012

Conference

Conference	2012 10th IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, VECIMS 2012
Country/Territory	China
City	Tianjin
Period	2/07/12 → 4/07/12

Keywords

Cervical spinal cord
computational intelligence
Diffusion tensor imaging
knowledge based
Region of interest

ASJC Scopus subject areas

Artificial Intelligence
Human-Computer Interaction
Control and Systems Engineering
Electrical and Electronic Engineering

More information

10.1109/VECIMS.2012.6273208

Cite this

Li, X., Cui, J. L., Wen, C., Au, T. K. H., Luk, K. D. K., & Hu, Y. (2012). A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging. In VECIMS 2012 - 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Proceedings (pp. 9-12). [6273208] https://doi.org/10.1109/VECIMS.2012.6273208

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title = "A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging",

abstract = "Diffusion MR imaging technique has been developed in past decade to permit the detection of tissue water molecular diffusion at microscopic dimension and has been widely used to investigate the spinal cord parenchyma. The commonly used hand-drawn region of interest (ROI)-based segmentation in diffusion tensor imaging(DTI) analysis is highly labor-intensive and user-dependent. In this study, we aim to develop an automatic template (auto-template) based on anatomy knowledge and computational intelligence to extract the regional diffusion anisotropy pattern of cervical spinal cord. A total of 16 healthy volunteers were recruited in this study. Eleven axial diffusion tensor MR images covering C1 to C7 of cervical spinal cord were taken with single-shot spin-echo echo-planar imaging sequence on a 3T MR system. The fractional anisotropy (FA) value of anterior, lateral, posterior column of white matter and gray matter was measured using hand-drawn ROI and knowledge based computational intelligence method respectively. Knowledge based template showed the FA value in the anterior (0.737±0.009), lateral (0.827±0.011), posterior (0.854±0.007) column of white matter and gray matter (0.493±0.009) with higher inter-rater agreement than hand-drawn ROI method. The result suggested that knowledge based template is a convenient tool to extract the diffusion data in various parts of the cervical spinal cord with high accuracy and inter-rater reliability.",

keywords = "Cervical spinal cord, computational intelligence, Diffusion tensor imaging, knowledge based, Region of interest",

author = "Xiang Li and Cui, {Jiao Long} and Chunyi Wen and Au, {Timothy K.H.} and Luk, {Keith D.K.} and Yong Hu",

year = "2012",

month = nov,

day = "1",

doi = "10.1109/VECIMS.2012.6273208",

language = "English",

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pages = "9--12",

booktitle = "VECIMS 2012 - 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Proceedings",

note = "2012 10th IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, VECIMS 2012 ; Conference date: 02-07-2012 Through 04-07-2012",

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Li, X, Cui, JL, Wen, C, Au, TKH, Luk, KDK & Hu, Y 2012, A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging. in VECIMS 2012 - 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Proceedings., 6273208, pp. 9-12, 2012 10th IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, VECIMS 2012, Tianjin, China, 2/07/12. https://doi.org/10.1109/VECIMS.2012.6273208

A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging. / Li, Xiang; Cui, Jiao Long; Wen, Chunyi et al.
VECIMS 2012 - 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Proceedings. 2012. p. 9-12 6273208.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging

AU - Li, Xiang

AU - Cui, Jiao Long

AU - Wen, Chunyi

AU - Au, Timothy K.H.

AU - Luk, Keith D.K.

AU - Hu, Yong

PY - 2012/11/1

Y1 - 2012/11/1

N2 - Diffusion MR imaging technique has been developed in past decade to permit the detection of tissue water molecular diffusion at microscopic dimension and has been widely used to investigate the spinal cord parenchyma. The commonly used hand-drawn region of interest (ROI)-based segmentation in diffusion tensor imaging(DTI) analysis is highly labor-intensive and user-dependent. In this study, we aim to develop an automatic template (auto-template) based on anatomy knowledge and computational intelligence to extract the regional diffusion anisotropy pattern of cervical spinal cord. A total of 16 healthy volunteers were recruited in this study. Eleven axial diffusion tensor MR images covering C1 to C7 of cervical spinal cord were taken with single-shot spin-echo echo-planar imaging sequence on a 3T MR system. The fractional anisotropy (FA) value of anterior, lateral, posterior column of white matter and gray matter was measured using hand-drawn ROI and knowledge based computational intelligence method respectively. Knowledge based template showed the FA value in the anterior (0.737±0.009), lateral (0.827±0.011), posterior (0.854±0.007) column of white matter and gray matter (0.493±0.009) with higher inter-rater agreement than hand-drawn ROI method. The result suggested that knowledge based template is a convenient tool to extract the diffusion data in various parts of the cervical spinal cord with high accuracy and inter-rater reliability.

AB - Diffusion MR imaging technique has been developed in past decade to permit the detection of tissue water molecular diffusion at microscopic dimension and has been widely used to investigate the spinal cord parenchyma. The commonly used hand-drawn region of interest (ROI)-based segmentation in diffusion tensor imaging(DTI) analysis is highly labor-intensive and user-dependent. In this study, we aim to develop an automatic template (auto-template) based on anatomy knowledge and computational intelligence to extract the regional diffusion anisotropy pattern of cervical spinal cord. A total of 16 healthy volunteers were recruited in this study. Eleven axial diffusion tensor MR images covering C1 to C7 of cervical spinal cord were taken with single-shot spin-echo echo-planar imaging sequence on a 3T MR system. The fractional anisotropy (FA) value of anterior, lateral, posterior column of white matter and gray matter was measured using hand-drawn ROI and knowledge based computational intelligence method respectively. Knowledge based template showed the FA value in the anterior (0.737±0.009), lateral (0.827±0.011), posterior (0.854±0.007) column of white matter and gray matter (0.493±0.009) with higher inter-rater agreement than hand-drawn ROI method. The result suggested that knowledge based template is a convenient tool to extract the diffusion data in various parts of the cervical spinal cord with high accuracy and inter-rater reliability.

KW - Cervical spinal cord

KW - computational intelligence

KW - Diffusion tensor imaging

KW - knowledge based

KW - Region of interest

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DO - 10.1109/VECIMS.2012.6273208

M3 - Conference article published in proceeding or book

SN - 9781457717574

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BT - VECIMS 2012 - 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Proceedings

T2 - 2012 10th IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, VECIMS 2012

Y2 - 2 July 2012 through 4 July 2012

ER -

A knowledge based automatic region of interest (ROI) segment of cervical cord diffusion tensor imaging

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