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International Journal of Biomedical Imaging - Volume 2015 2015, Article ID 590727, 13 pages -

Research ArticleBiomedical Engineering Department, Cairo University, Giza 12613, Egypt

Received 18 November 2014; Revised 28 December 2014; Accepted 9 January 2015

Academic Editor: Tzung-Pei Hong

Copyright © 2015 Marwan Abdellah et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Fourier volume rendering FVR is a significant visualization technique that has been used widely in digital radiography. As a result of its time complexity, it provides a faster alternative to spatial domain volume rendering algorithms that are computationally complex. Relying on the Fourier projection-slice theorem, this technique operates on the spectral representation of a 3D volume instead of processing its spatial representation to generate attenuation-only projections that look like X-ray radiographs. Due to the rapid evolution of its underlying architecture, the graphics processing unit GPU became an attractive competent platform that can deliver giant computational raw power compared to the central processing unit CPU on a per-dollar-basis. The introduction of the compute unified device architecture CUDA technology enables embarrassingly-parallel algorithms to run efficiently on CUDA-capable GPU architectures. In this work, a high performance GPU-accelerated implementation of the FVR pipeline on CUDA-enabled GPUs is presented. This proposed implementation can achieve a speed-up of 117x compared to a single-threaded hybrid implementation that uses the CPU and GPU together by taking advantage of executing the rendering pipeline entirely on recent GPU architectures.





Author: Marwan Abdellah, Ayman Eldeib, and Amr Sharawi

Source: https://www.hindawi.com/



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