Image quality improvement in cone-beam CT using the super-resolution technique.

08:00 EDT 5th April 2018 | BioPortfolio

Summary of "Image quality improvement in cone-beam CT using the super-resolution technique."

This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.


Journal Details

This article was published in the following journal.

Name: Journal of radiation research
ISSN: 1349-9157


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Medical and Biotech [MESH] Definitions

Improvement in the quality of an x-ray image by use of an intensifying screen, tube, or filter and by optimum exposure techniques. Digital processing methods are often employed.

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The attainment or process of attaining a new level of performance or quality.

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