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GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images. Khallaghi, Siavash; Abolmaesumi, Purang; Gong, Ren Hui; Chen, Elvis C. S.; Gill, Sean; Boisvert, Jonathan; Pichora, David; Borschneck, Dan; Fichtinger, Gabor; Mousavi, Parvin

Abstract

We present a parallel implementation of a statistical shape model registration to 3D ultrasound images of the lumbar vertebrae (L2-L4). Covariance Matrix Adaptation Evolution Strategy optimization technique, along with Linear Correlation of Linear Combination similarity metric have been used, to improve the robustness and capture range of the registration approach. Instantiation and ultrasound simulation have been implemented on a graphics processing unit for a faster registration. Phantom studies show a mean target registration error of 3.2 mm, while 80% of all the cases yield target registration error of below 3.5 mm. Copyright 2011 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Item Metadata

Title
GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images.
Creator
Khallaghi, Siavash; Abolmaesumi, Purang; Gong, Ren Hui; Chen, Elvis C. S.; Gill, Sean; Boisvert, Jonathan; Pichora, David; Borschneck, Dan; Fichtinger, Gabor; Mousavi, Parvin
Publisher
Society of Photo-Optical Instrumentation Engineers (SPIE)
Date Issued
2011
Description
We present a parallel implementation of a statistical shape model registration to 3D ultrasound images of the lumbar vertebrae (L2-L4). Covariance Matrix Adaptation Evolution Strategy optimization technique, along with Linear Correlation of Linear Combination similarity metric have been used, to improve the robustness and capture range of the registration approach. Instantiation and ultrasound simulation have been implemented on a graphics processing unit for a faster registration. Phantom studies show a mean target registration error of 3.2 mm, while 80% of all the cases yield target registration error of below 3.5 mm. Copyright 2011 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Genre
Conference Paper
Type
Text
Language
eng
Date Available
2011-08-16
Provider
Vancouver : University of British Columbia Library
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
DOI
10.14288/1.0107560
URI
http://hdl.handle.net/2429/36699
Affiliation
Applied Science, Faculty of; Electrical and Computer Engineering, Department of
Citation
Khallaghi, Siavash; Abolmaesumi, Purang; Gong, Ren Hui; Chen, Elvis C. S.; Gill, Sean; Boisvert, Jonathan; Pichora, David; Borschneck, Dan; Fichtinger, Gabor; Mousavi, Parvin. GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images. Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, edited by Kenneth H. Wong, David R. Holmes III, Proceedings of SPIE, Volume 7964, 79642W, 2011.
Publisher DOI
10.1117/12.878377
Peer Review Status
Reviewed
Scholarly Level
Faculty
Copyright Holder
Abolmaesumi, Purang
Rights URI
http://creativecommons.org/licenses/by-nc-nd/4.0/
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Attribution-NonCommercial-NoDerivatives 4.0 International