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Proceedings Paper

A high-performance GPU-based forward-projection model for computed tomography applications
Author(s): Ismael Perez; Matthew Bauerle; Edward S. Jimenez Jr.; Kyle R. Thompson
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Paper Abstract

This work describes a high-performance approach to radiograph (i.e. X-ray image for this work) simulation for arbitrary objects. The generation of radiographs is more generally known as the forward projection imaging model. The formation of radiographs is very computationally expensive and is not typically approached for large-scale applications such as industrial radiography. The approach described in this work revolves around a single GPU-based implementation that performs the attenuation calculation in a massively parallel environment. Additionally, further performance gains are realized by exploiting the GPU-specific hardware. Early results show that using a single GPU can increase computational performance by three orders-of- magnitude for volumes of 10003 voxels and images with 10002 pixels.

Paper Details

Date Published: 4 September 2014
PDF: 7 pages
Proc. SPIE 9215, Radiation Detectors: Systems and Applications XV, 92150A (4 September 2014); doi: 10.1117/12.2064689
Show Author Affiliations
Ismael Perez, Sandia National Labs. (United States)
Matthew Bauerle, Sandia National Labs. (United States)
Edward S. Jimenez Jr., Sandia National Labs. (United States)
Kyle R. Thompson, Sandia National Labs. (United States)

Published in SPIE Proceedings Vol. 9215:
Radiation Detectors: Systems and Applications XV
Gary P. Grim; H. Bradford Barber, Editor(s)

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