A high-performance GPU-based forward-projection model for computed tomography applications

Ismael Perez; Matthew Bauerle; Edward S. Jimenez Jr.; Kyle R. Thompson

doi:10.1117/12.2064689

4 September 2014 A high-performance GPU-based forward-projection model for computed tomography applications

Ismael Perez, Matthew Bauerle, Edward S. Jimenez Jr., Kyle R. Thompson

Proceedings Volume 9215, Radiation Detectors: Systems and Applications XV; 92150A (2014) https://doi.org/10.1117/12.2064689
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

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.

Citation Download Citation

Ismael Perez, Matthew Bauerle, Edward S. Jimenez Jr., and 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); https://doi.org/10.1117/12.2064689

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