Efficient probabilistic and geometric anatomical mapping using particle mesh approximation on GPUs

Update Item Information
Publication Type pre-print
School or College <blank>
Department <blank>
Creator Gerig, Guido
Other Author Ha, Linh; Prastawa, Marcel; Gilmore, John H.; Silva, Claudio T.; Joshi, Sarang
Title Efficient probabilistic and geometric anatomical mapping using particle mesh approximation on GPUs
Date 2011-01-01
Description Deformable image registration in the presence of considerable contrast differences and large size and shape changes presents significant research challenges. First, it requires a robust registration framework that does not depend on intensity measurements and can handle large nonlinear shape variations. Second, it involves the expensive computation of nonlinear deformations with high degrees of freedom. Often it takes a significant amount of computation time and thus becomes infeasible for practical purposes. In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. We show results on the registrations of neonatal to 2-year old infant MRIs. Quantitative validation demonstrates that our proposed method generates registrations that better maintain the consistency of anatomical structures over time and provides transformations that better preserve structures undergoing large deformations than transformations obtained by standard intensity-only registration. We also achieve the speedup of three orders of magnitudes compared to a CPU reference implementation, making it possible to use the technique in time-critical applications.
Type Text
Publisher Hindawi Publishing Corporation
Volume 2011
Issue ID572187
First Page 1
Last Page 16
Language eng
Bibliographic Citation Ha, L., Prastawa, M., Gerig, G., Gilmore, J. H., Silva, C. T., & Joshi, S. (2011). Efficient probabilistic and geometric anatomical mapping using particle mesh approximation on GPUs. International Journal of Biomedical Imaging, 2011(ID572187), 1-16.
Rights Management (c) Guido Gerig, http://creativecommons.org/licenses/by/3.0/legalcode
Format Medium application/pdf
Format Extent 7,670,841 bytes
Identifier uspace,19190
ARK ark:/87278/s6mw5s82
Setname ir_uspace
ID 712776
Reference URL https://collections.lib.utah.edu/ark:/87278/s6mw5s82
Back to Search Results