When using a photon counting detector for material decomposition problems, a major issue is the low-count rate per energy bin which may lead to high image-noise with compromised contrast and accuracy. A multi-step algorithmic method of material decomposition is proposed for spectral computed tomography (CT), where the problem is formulated as series of simpler and dose efficient decompositions rather than solved simultaneously. A simple domain of four materials; water, hydroxyapatite, iodine and gold was explored. The results showed an improvement in accuracy with low-noise over a similar method where the materials were decomposed simultaneously. In the multi-step approach, for the same acquired energy bin data, the problem is reformulated in each step with decreasing number of energy bins (resulting in a higher count levels per bin) and unknowns in each step. This offers flexibility in the choice of energy bins for each material type. Our results are very preliminary but show promise and potential to tackle challenging decomposition tasks. Complete work will include detailed analysis of this approach and experimental data with more complex mixtures.
Nathaniel R. Fredette, Cale E. Lewis, and Mini Das, "A multi-step method for material decomposition in spectral computed tomography," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101321C (Presented at SPIE Medical Imaging: February 15, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2256114.
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