Paper Info
Title
Exploiting Parallelism in a X-ray Tomography Reconstruction Algorithm on Hybrid Multi-GPU and Multi-core Platforms
Abstract
Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. Currently there are a strong need to speed-up the reconstruction of XRay CT data in order to extend its clinical applications. We present an efficient modular implementation of an FDK-based reconstruction algorithm that takes advantage of the parallel computing capabilities and the efficient bilinear interpolation provided by general purpose graphic processing units (GPGPU). The proposed implementation of the algorithm is evaluated for a high-resolution micro-CT and achieves a speed-up of 46, while preserving the reconstructed image quality.
Year
DOI
Venue
2012
10.1109/ISPA.2012.138
ISPA
Keywords
Field
DocType
X-ray microscopy,computerised tomography,geometry,graphics processing units,image reconstruction,medical image processing,multiprocessing systems,parallel processing,CT scanners,FDK-based reconstruction,GPGPU,X-ray tomography reconstruction,circular trajectory,clinical applications,cone-beam geometry,flat-panel detector,general purpose graphic processing units,hybrid multi-GPU,image quality,image reconstruction,multicore platforms,parallel computing,parallelism,small-animal X-ray computed tomography
Computer science,Image quality,Real-time computing,Reconstruction algorithm,Computational science,Artificial intelligence,Multi-core processor,Iterative reconstruction,Computer vision,Tomography,General-purpose computing on graphics processing units,Graphics processing unit,Bilinear interpolation
Conference
Citations 
PageRank 
References 
1
0.35
0
Authors
5
Name
Order
Citations
PageRank
Ernesto Liria140.83
Daniel Higuero2483.97
M Abella3174.68
Claudia de Molina410.69
Manuel Desco517419.81