The purpose of this study was to evaluate the effect of single-energy metal artifact reduction (SEMAR) for metal artifacts using CT images reconstructed with adaptive iterative dose reduction three dimensional (AIDR3D) and advanced intelligent clear-IQ engine (AiCE) in calibration-field of view of various sizes. A prosthetic hip joint was arranged at the center of the phantom. The phantom images were scanned by changing calibration-field of view of 320 mm and 500 mm, and were reconstructed using filtered back-projection (FBP), AIDR3D, and AiCE with and without SEMAR, respectively. The metal artifact reduction with SEMAR was evaluated by calculated the relative artifact index value and visual scores in degree of artifact by seven radiology technologists. Relative artifact index of FBP, AIDR3D, and AiCE with 320 mm/500 mm calibration-field of views were 10.2/10.0, 16.3/16.4, and 17.8/17.9 without SEMAR, 3.3/3.1, 2.6/2.5, and 2.3/2.0 with SEMAR, respectively. Visual scores were not significantly different between 320 and 500 mm calibration-field of views in all reconstruction methods. The effect of metal artifact reduction was not affected by calibration-field of view sizes in the SEMAR combined with AIDR3D or AiCE.
Keywords: Artifact; Computed tomography; Deep learning; Field of view; SEMAR.
© 2022. Australasian College of Physical Scientists and Engineers in Medicine.