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Publication year
2014Source
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 61, (2014), pp. 207-213ISSN
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Publication type
Article / Letter to editor

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Organization
Radiology
Paediatrics - OUD tm 2017
Medical Imaging
Journal title
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume
vol. 61
Page start
p. 207
Page end
p. 213
Subject
Radboudumc 16: Vascular damage RIHS: Radboud Institute for Health SciencesAbstract
Deformation of tissue can be accurately estimated from radio-frequency ultrasound data using a 2-dimensional normalized cross correlation (NCC)-based algorithm. This procedure, however, is very computationally time-consuming. A major time reduction can be achieved by parallelizing the numerous computations of NCC. In this paper, two approaches for parallelization have been investigated: the OpenMP interface on a multi-CPU system and Compute Unified Device Architecture (CUDA) on a graphics processing unit (GPU). The performance of the OpenMP and GPU approaches were compared with a conventional Matlab implementation of NCC. The OpenMP approach with 8 threads achieved a maximum speed-up factor of 132 on the computing of NCC, whereas the GPU approach on an Nvidia Tesla K20 achieved a maximum speed-up factor of 376. Neither parallelization approach resulted in a significant loss in image quality of the elastograms. Parallelization of the NCC computations using the GPU, therefore, significantly reduces the computation time and increases the frame rate for motion estimation.
This item appears in the following Collection(s)
- Academic publications [234081]
- Electronic publications [116779]
- Faculty of Medical Sciences [89175]
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