Metal-induced streak artifact reduction using iterative reconstruction algorithms in X-ray CT image of the dento-alveolar region

Objective: To reduce metal-induced streak artifact on oral and maxillofacial X-ray CT (computed tomography) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Study design: Adjacent CT images often depict similar anatomical structures in thin slices. So firstly images were reconstructed using the same projection data of an artifact-free image. Secondly images were processed by the successive iterative restoration method where projection data was generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also small ROI setting and reverse processing were applied for improving performance. Results: Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing didn’t show apparent effects. Conclusions: Two alternatives in iterative reconstruction methods were effective for artifacts reduction. The OS-EM algorithm and small ROI setting improved the performance.Our joint research project was partly supported by the Bilateral Program of the Japan Society for the Promotion of Science, 2010-2012