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.
