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Material classification using basis material decomposition from spectral X-ray CT

Doniyor JumanazarovACCENT PRO 2000 s.r.l. (AP2K), Nerva Traian 1, K6, Ap. 26, Bucharest, S3, 031041, RomaniaAsalkhon AlimovaUrgench branch of Tashkent Medical Academy, 28, Al-Xorazmiy str, Urgench, 220100, UzbekistanAzamat AbdikarimovDepartment of Physics, Urgench State Universit, 14, Kh. Alimdjan str, Urgench, 220100, UzbekistanJakeoung KooGachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of KoreaHenning Friis PoulsenTechnical University of Denmark, DTU Physics, 2800 Kgs. Lyngby, DenmarkUlrik L. OlsenTechnical University of Denmark, DTU Physics, 2800 Kgs. Lyngby, DenmarkM. IoveaACCENT PRO 2000 s.r.l. (AP2K), Nerva Traian 1, K6, Ap. 26, Bucharest, S3, 031041, Romania
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Spectral X-ray Computed Tomography (CT) exploits advanced photon counting detectors (PCD) to measure a material’s spectrally resolved linear attenuation coefficient (LAC) with the simultaneous spectral acquisition at multiple energy thresholds. We present a method for material classification using spectral CT. The method employs a basis material decomposition model and estimates the effective atomic number (Zeff) from the spectral LAC measurements. Basis material decomposition builds on the fact that the LAC of any material can be well approximated by a linear combination of LACs of basis materials, with known Zeff values at the extremes of the relevant Zeff range. Spectral distortions of the energy spectrum due to the physical interactions between photons and the multi-energy-bin PCD such as charge sharing and photon pileup are corrected by a spectral correction algorithm. The validation of the method has been performed with experimental data acquired with a custom laboratory instrument for spectral CT, examining “real life” phantoms with materials in the range of 6≤Zeff≤15. The classification performance is estimated for different numbers of projections, energy bins and basis materials in LAC decomposition. When using just 12 projections, 15 energy bins and two basis materials, the method gives a relative deviation of 2.2% for Zeff, while this deviation is 5.9% when spectral correction is not used. The classification method is now ready for use in security screening where modern spectral CT systems are employed.

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