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GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images.

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Title: GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images.
Author: Khallaghi, Siavash; Abolmaesumi, Purang; Gong, Ren Hui; Chen, Elvis C. S.; Gill, Sean; Boisvert, Jonathan; Pichora, David; Borschneck, Dan; Fichtinger, Gabor; Mousavi, Parvin
Issue Date: 2011
Publicly Available in cIRcle 2011-08-16
Publisher Society of Photo-Optical Instrumentation Engineers
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. http://dx.doi.org/10.1117/12.878377
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.
Affiliation: Electrical and Computer Engineering, Dept of
URI: http://hdl.handle.net/2429/36699
Peer Review Status: Reviewed
Scholarly Level: Faculty

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