& Kim, H.-J. Quantitative material decomposition using spectral computed tomography with an energy-resolved photon-counting detector.
Gadolinium and iodine maps were calculated using a linear material decomposition technique and compared to single-energy (conventional) images.
We found that the choice of binning and weighting schemes can greatly affect the performance of material decomposition.
The extent of material decomposition is seen to affect the absorption behaviour of both samples.
The accuracy of the material decomposition algorithm in a test phantom was -0.4 ± 2.2 mM, 0.3 ± 2.2 mM for iodine and gadolinium solutions, respectively.
The method relies on the observation that the material decomposition from a dual energy CT scan allows the transmission of an arbitrary spectrum to be predicted.
It is worth noting, however, that the reaction of vinyl benzoate 38, bearing a potential five-membered chelate ring, is also hampered by starting material decomposition under the standard conditions.
An initial 80/140 kVp dual energy scan of the phantom provided the material decomposition necessary to synthesize images at 100 kVp and at 120 kVp, across a range of mAs values.
On the other hand, because μ-weighted measurements form a sufficient statistic for spectral imaging, the CRLB of the material decomposition estimates is identical to the quantum noise limited performance of a system with complete energy information of all photons.
For large objects, conventional (non-K-edge) beam hardening filters perform well.This study demonstrates the potential of fixed K-edge filtration to improve the dose efficiency and material decomposition precision for rapid kVp-switching dual energy systems.
These statistics are then used to compute the performance (e.g., contrast-to-noise ratio) for both single material and material decomposition contrast detection tasks via the Cramdr-Rao lower bound (CRLB) as a function of the detector input count rate.
