Chapter title |
Application of Pseudo-enhancement Correction to Virtual Monochromatic CT Colonography.
|
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Chapter number | 16 |
Book title |
Abdominal Imaging. Computational and Clinical Applications
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Published in |
Lecture notes in computer science, September 2014
|
DOI | 10.1007/978-3-319-13692-9_16 |
Pubmed ID | |
Book ISBNs |
978-3-31-913691-2, 978-3-31-913692-9
|
Authors |
Tachibana, Rie, Näppi, Janne J, Yoshida, Hiroyuki, Rie Tachibana, Janne J. Näppi, Hiroyuki Yoshida, Näppi, Janne J. |
Abstract |
In CT colonography, orally administered positive-contrast fecal-tagging agents are used for differentiating residual fluid and feces from true lesions. However, the presence of high-density tagging agent in the colon can introduce erroneous artifacts, such as local pseudo-enhancement and beam-hardening, on the reconstructed CT images, thereby complicating reliable detection of soft-tissue lesions. In dual-energy CT colonography, such image artifacts can be reduced by the calculation of virtual monochromatic CT images, which provide more accurate quantitative attenuation measurements than conventional single-energy CT colonography. In practice, however, virtual monochromatic images may still contain some pseudo-enhancement artifacts, and efforts to minimize radiation dose may enhance such artifacts. In this study, we evaluated the effect of image-based pseudo-enhancement post-correction on virtual monochromatic images in standard-dose and low-dose dual-energy CT colonography. The mean CT values of the virtual monochromatic standard-dose CT images of 51 polyps and those of the virtual monochromatic low-dose CT images of 20 polyps were measured without and with the pseudo-enhancement correction. Statistically significant differences were observed between uncorrected and pseudo-enhancement-corrected images of polyps covered by fecal tagging in standard-dose CT (p < 0.001) and in low-dose CT (p < 0.05). The results indicate that image-based pseudo-enhancement post-correction can be useful for optimizing the performance of image-processing applications in virtual monochromatic CT colonography. |
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