Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs
Joint Authors
Joshi, Sarang
Gerig, Guido
Gilmore, John H.
Prastawa, Marcel
Silva, Cláudio T.
Ha, Linh
Source
International Journal of Biomedical Imaging
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-08-17
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Ha, Linh& Prastawa, Marcel& Gerig, Guido& Gilmore, John H.& Silva, Cláudio T.& Joshi, Sarang. 2011. Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs. International Journal of Biomedical Imaging،Vol. 2011, no. 2011, pp.1-16.
https://search.emarefa.net/detail/BIM-481745
Modern Language Association (MLA)
Ha, Linh…[et al.]. Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs. International Journal of Biomedical Imaging No. 2011 (2011), pp.1-16.
https://search.emarefa.net/detail/BIM-481745
American Medical Association (AMA)
Ha, Linh& Prastawa, Marcel& Gerig, Guido& Gilmore, John H.& Silva, Cláudio T.& Joshi, Sarang. Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs. International Journal of Biomedical Imaging. 2011. Vol. 2011, no. 2011, pp.1-16.
https://search.emarefa.net/detail/BIM-481745
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-481745