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Proceedings Paper

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

Paper Details

Date Published: 1 March 2011
PDF: 8 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79642W (1 March 2011); doi: 10.1117/12.878377
Show Author Affiliations
Siavash Khallaghi, Queen's Univ. (Canada)
Purang Abolmaesumi, The Univ. of British Columbia (Canada)
Ren Hui Gong, Queen's Univ. (Canada)
Elvis Chen, Queen's Univ. (Canada)
Sean Gill, Queen's Univ. (Canada)
Jonathan Boisvert, National Research Council Canada (Canada)
David Pichora, Kingston General Hospital (Canada)
Dan Borschneck, Kingston General Hospital (Canada)
Gabor Fichtinger, Queen's Univ. (Canada)
Parvin Mousavi, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes, Editor(s)

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