4 September 2014 A high-performance GPU-based forward-projection model for computed tomography applications
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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.
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Ismael Perez, Matthew Bauerle, Edward S. Jimenez, Kyle R. Thompson, "A high-performance GPU-based forward-projection model for computed tomography applications", Proc. SPIE 9215, Radiation Detectors: Systems and Applications XV, 92150A (4 September 2014); doi: 10.1117/12.2064689; https://doi.org/10.1117/12.2064689
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