Paper
16 March 2011 A comparison of four algorithms for metal artifact reduction in CT imaging
Caroline Golden, Samuel R. Mazin, F. Edward Boas, Grace Tye, Pejman Ghanouni, Garry Gold, Marc Sofilos, Norbert J. Pelc
Author Affiliations +
Abstract
Streak artifacts caused by the presence of metal have been a significant problem in CT imaging since its inception in 1972. With the fast evolving medical device industry, the number of metal objects implanted in patients is increasing annually. This correlates directly with an increased likelihood of encountering metal in a patient CT scan, thus necessitating the need for an effective and reproducible metal artifact reduction (MAR) algorithm. Previous comparisons between MAR algorithms have typically only evaluated a small number of patients and a limited range of metal implants. Although the results of many methods are promising, the reproducibility of these results is key to providing more tangible evidence of their effectiveness. This study presents a direct comparison between the performances, assessed by board certified radiologists, of four MAR algorithms: 3 non-iterative and one iterative method, all applied and compared to the original clinical images. The results of the evaluation indicated a negative mean score in almost all uses for two of the non-iterative methods, signifying an overall decrease in the diagnostic quality of the images, generally due to perceived loss of detail. One non-iterative algorithm showed a slight improvement. The iterative algorithm was superior in all studies by producing a considerable improvement in all uses.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Caroline Golden, Samuel R. Mazin, F. Edward Boas, Grace Tye, Pejman Ghanouni, Garry Gold, Marc Sofilos, and Norbert J. Pelc "A comparison of four algorithms for metal artifact reduction in CT imaging", Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79612Y (16 March 2011); https://doi.org/10.1117/12.878896
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Cited by 13 scholarly publications.
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KEYWORDS
Metals

Reconstruction algorithms

Bone

Computed tomography

Image segmentation

Tissues

Diagnostics

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