Major project

Evaluation of two iterative techniques for reducing metal artifacts in computed tomography

Boas et al. (2011) conducted a study to evaluate methods for reducing the severity of metal artifacts in computed tomography. The metal deletion technique and selective algebraic reconstruction techniques were compared the image quality with filtered back projection and linear interpolation in term of the metal artifact reduction in the computed tomography images. The metal deletion technique can be suppressed the metal artifact in computed tomography images by using forward projection to replace detector measurements that involve metal. It reduces metal artifacts that caused by photon counting noise, beam hardening and motion. At the same time, it can avoid introducing new streak between metal and bone. Eleven clinical computed tomography data were collected by retrospectively with metal streak artifacts, with a total of 178 images containing metal.  Each image data set was reconstructed using metal deletion technique, selective algebraic reconstruction techniques, filtered back projection and linear interpolation. The quantitative evaluation was performed by calculating the average error in Hounsfield units for each pixel in the phantom study. Two radiologists who were blinded to the reconstruction algorithms used qualitatively evaluated the clinical cases by ranking the overall severity of metal artifacts. The results shows metal deletion technique had the lowest average error (76% less than filtered back projection, 42% less than linear interpolation and 17% less than selective algebraic reconstruction techniques). Blinded comparison of the clinical scans indicated that metal deletion technique had the best image quality 100% of the time.

            This study provides the good metal artifact reduction technique that can be used in the wide range of clinical application. However, there are some limitations.

1)      The researchers did not explain the detail of score ranking the overall severity of metal artifacts evaluation. They mentioned only a rank of 1 and 4; they did not explain a rank of 2 and 3 in the clinical qualitative evaluation. Gur D et al. (1997) introduced the forced choice and ordinal discrete rating assessment of image quality. It is another option to evaluate the image quality.

2)      Most of the clinical computed tomography data were metal streak artifact in the abdomen and pelvis region. It might be not difficult to suppress metal artifact in that region because the size and pattern of metal streak artifact is relative small and certain pattern. In contrast, the metal streak artifact in the oral cavity might be more challenging to suppress metal streak artifact in the computed tomography images because it seem to be sizes and pattern variety of the metal in the oral cavity (Tibrewala et al., 2013).

3)      The metal deletion technique reconstruction time is approximately 19 times slower than filtered back projection. It due to the fact that reconstructions used raw data from the computed tomography scanner and were performed on a general purpose central processing unit without any hardware acceleration.

            The strength of this study is that their concept and methodology is satisfy and widely accepted for metal artifact reduction in computed tomography images. Moreover, this technique can be implemented to every computed tomography scanner because it suppress metal artifact from the raw data of the computed tomography scanner.

References

Boas, F.E. & Fleischmann D. (2011). Evaluation of two iterative techniques for reducing metal artifacts in computed tomography. Radiology, 259(3), 894-902.

Gur, D. et al. (1997). Forced choice and ordinal discrete rating assessment of image quality: A comparison. Journal of Digital Imaging, 10(3), 103-107.

Tibrewala, S., Roplekar, S. & Varma, R. (2013). Computed tomography evaluation of oral cavity and oropharyngeal cancers. An International Journal of Otorhinolaryngology Clinic, 5(2), 51-62.