Model-based Multi-material Decomposition using Spatial-Spectral CT Filters
Spectral CT with multiple contrast agents has been enabled by energy-discriminating detectors with multiple spectral channels. We propose a new approach that uses spatial-spectral filters to provide multiple beamlets with different incident spectra for spectral channels based on "source-side&qu...
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| Published in | Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography Vol. 2018; p. 102 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United States
01.05.2018
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| Online Access | Get more information |
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| Summary: | Spectral CT with multiple contrast agents has been enabled by energy-discriminating detectors with multiple spectral channels. We propose a new approach that uses spatial-spectral filters to provide multiple beamlets with different incident spectra for spectral channels based on "source-side" control. Since these spatial-spectral filters yield spectral channels that are sparse, we adopt model-based material decomposition to directly reconstruct material densities from projection data. Simulation studies in three-and four-material decomposition experiments show the underlying feasibility of the spatial-spectral filtering technique. This methodology has the potential to facilitate imaging of multiple contrast agents simultaneously with relatively simple hardware, or to improve spectral CT performance via combination with other established spectral CT methods for additional control and flexibility. |
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