Mr. Leonardo Di Schiavi Trotta Profile

Leonardo Di Schiavi Trotta

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Proceedings Article | 18 October 2022 Open Access

On the use of voxel-driven backprojection and iterative reconstruction for small ROI CT imaging

Leonardo D. Trotta, Dmitri Matenine, Margherita Martini, Yannick Lemaréchal, Pierre Francus, Philippe Després

Proceedings Volume 12304, 123042V (2022) https://doi.org/10.1117/12.2647012

KEYWORDS: Reconstruction algorithms, Signal attenuation, X-ray computed tomography, Computed tomography, Scanners, Calibration, Tomography

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In this work related to the use of a commercial medical CT scanner for the non-destructive analysis of highly attenuating materials (mineral samples), the effect of backprojection techniques and truncation artifacts corrections were explored. For small ROIs, the CT couch interferes significantly in images of small samples (few centimeters). An iterative reconstruction algorithm (OSC-TV) was used to perform reconstructions from uncorrected raw projection data made available through a collaboration with the CT vendor, who provided binaries and methods to remove low-level, proprietary data corrections (for beam hardening). The OSC-TV algorithm is customizable, allowing for the use of different forward-projection and backprojection techniques. Reconstruction parameters were tuned by performing simulations in a virtual phantom involving highly attenuating materials. Strategies to reconstruct small ROIs were also explored, with the objective of reducing truncation artifacts. Three samples were scanned to compare a ray-driven backprojection and a voxel-driven backprojection technique based on bilinear interpolation. The voxel-driven approach led to better results in terms of noise and reconstruction artifacts. An iterative ROI reconstruction technique was used to reconstruct small ROIs. This technique allows obtaining a sinogram with the projections of the ROI only. With that, truncation artifacts were reduced, which led to images with less blurring.

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