document: Prospects for quantitative computed tomography imaging in the presence of foreign metal bodies using statistical image reconstruction X-ray computed tomography -LRB- CT -RRB- images of patients bearing metal intracavitary applicators or other metal foreign objects exhibit severe artifacts including streaks and aliasing . We have systematically evaluated via computer simulations the impact of scattered radiation , the polyenergetic spectrum , and measurement noise on the performance of three reconstruction algorithms : conventional filtered backprojection -LRB- FBP -RRB- , deterministic iterative deblurring , and a new iterative algorithm , alternating minimization -LRB- AM -RRB- , based on a CT detector model that includes noise , scatter , and polyenergetic spectra . Contrary to the dominant view of the literature , FBP streaking artifacts are due mostly to mismatches between FBP 's simplified model of CT detector response and the physical process of signal acquisition . Artifacts on AM images are significantly mitigated as this algorithm substantially reduces detector-model mismatches . However , metal artifacts are reduced to acceptable levels only when prior knowledge of the metal object in the patient , including its pose , shape , and attenuation map , are used to constrain AM 's iterations . AM image reconstruction , in combination with object-constrained CT to estimate the pose of metal objects in the patient , is a promising approach for effectively mitigating metal artifacts and making quantitative estimation of tissue attenuation coefficients a clinical possibility
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