Presentation + Paper
1 March 2019 Physical modeling and performance of spatial-spectral filters for CT material decomposition
Author Affiliations +
Abstract
Material decomposition for imaging multiple contrast agents in a single acquisition has been made possible by spectral CT: a modality which incorporates multiple photon energy spectral sensitivities into a single data collection. This work presents an investigation of a new approach to spectral CT which does not rely on energy-discriminating detectors or multiple x-ray sources. Instead, a tiled pattern of K-edge filters are placed in front of the x-ray to create spatially encoded spectra data. For improved sampling, the spatial-spectral filter is moved continuously with respect to the source. A model-based material decomposition algorithm is adopted to directly reconstruct multiple material densities from projection data that is sparse in each spectral channel. Physical effects associated with the x-ray focal spot size and motion blur for the moving filter are expected to impact overall performance. In this work, those physical effects are modeled and a performance analysis is conducted. Specifically, experiments are presented with simulated focal spot widths between 0.2 mm and 4.0 mm. Additionally, filter motion blur is simulated for a linear translation speeds between 50 mm/s and 450 mm/s. The performance differential between a 0.2 mm and a 1.0 mm focal spot is less than 15% suggesting feasibility of the approach with realistic x-ray tubes. Moreover, for reasonable filter actuation speeds, higher speeds are shown to decrease error (due to improved sampling) despite motion-based spectral blur.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthew Tivnan, Steven Tilley II, and J. Webster Stayman "Physical modeling and performance of spatial-spectral filters for CT material decomposition", Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109481A (1 March 2019); https://doi.org/10.1117/12.2513481
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Sensors

Motion models

Iodine

Performance modeling

Data modeling

Gold

Detection and tracking algorithms

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