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Proceedings Paper

Fast generation of digitally reconstructed radiograph through an efficient preprocessing of ray attenuation values
Author(s): Soheil Ghafurian; Dimitris N. Metaxas; Virak Tan; Kang Li
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Paper Abstract

Digitally reconstructed radiographs (DRR) are a simulation of radiographic images produced through a perspective projection of the three-dimensional (3D) image (volume) onto a two-dimensional (2D) image plane. The traditional method for the generation of DRRs, namely ray-casting, is a computationally intensive process and accounts for most of solution time in 3D/2D medical image registration frameworks, where a large number of DRRs is required. A few alternate methods for a faster DRR generation have been proposed, the most successful of which are based on the idea of pre-calculating the attenuation value of possible rays. Despite achieving good quality, these methods support a limited range of motion for the volume and entail long pre-calculation time. In this paper, we propose a new preprocessing procedure and data structure for the calculation of the ray attenuation values. This method supports all possible volume positions with practically small memory requirements in addition to reducing the complexity of the problem from O(n3) to O(n2). In our experiments, we generated DRRs of high quality in 63 milliseconds with a preprocessing time of 99.48 seconds and a memory size of 7.45 megabytes.

Paper Details

Date Published: 18 March 2016
PDF: 8 pages
Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 97860C (18 March 2016); doi: 10.1117/12.2217756
Show Author Affiliations
Soheil Ghafurian, Rutgers Univ. (United States)
Dimitris N. Metaxas, Rutgers Univ. (United States)
Virak Tan, New Jersey Medical School, Rutgers Univ. (United States)
Kang Li, Rutgers Univ. (United States)
New Jersey Medical School, Rutgers Univ. (United States)


Published in SPIE Proceedings Vol. 9786:
Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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