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Validation and application of a new image reconstruction software toolbox (TIGRE) for breast cone-beam computed tomography
Author(s): Shada Kazemi; Oliver Diaz; Premkumar Elangovan; Kevin Wells; Annika Lohstroh
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Paper Abstract

A new image reconstruction software toolbox TIGRE (Tomographic Iterative GPU-based Reconstruction) has been evaluated for use in breast cone-beam computed tomography (CBCT) studies. This new software toolbox TIGRE has been compared to a standard Matlab-based implementation previously validated for X-ray mammography imaging. In particular, the image projection generator algorithm in the TIGRE toolbox, which is based on the Siddon ray-tracing algorithm, has been studied. The quantitative evaluation in terms of histograms and profile analyses, illustrates that TIGRE’s image projection show good agreement with our in-house validated X-ray ray tracing tool. In addition, it has been observed that since TIGRE uses GPU-based calculations, it produces projections approximately 90 times faster than CPU-based algorithms, dependent on choice of GPU. The breast CT images have also been reconstructed and evaluated using the two projection tools. The analyses show that the projections taken by TIGRE and our in-house developed Siddon algorithm, yield systematically similar results. To further investigate the differences between these two algorithms, the reconstructed images have been compared to each other. The correlation coefficients for an entire 3D reconstructed breast volumes using the two methods studied is 0.99±3.64x10-12 (mean ±standard deviation), the peak signal noise ratio is 117.17, the mean square error is 1.92x10-12 and the similarity index is 1.00.

Paper Details

Date Published: 9 March 2018
PDF: 8 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105735E (9 March 2018); doi: 10.1117/12.2293200
Show Author Affiliations
Shada Kazemi, Univ. of Surrey (United Kingdom)
Oliver Diaz, Univ. of Surrey (United Kingdom)
Univ. of Girona (Spain)
Premkumar Elangovan, Univ. of Surrey (United Kingdom)
The Royal Surrey County Hospital NHS Trust (United Kingdom)
Kevin Wells, Univ. of Surrey (United Kingdom)
Annika Lohstroh, Univ. of Surrey (United Kingdom)


Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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