Quantitative low-dose CT: potential value of low signal correction methods

Juan Pablo Cruz-Bastida; Ran Zhang; Daniel Gomez-Cardona; Guang-Hong Chen

doi:10.1117/12.2512889

7 March 2019 Quantitative low-dose CT: potential value of low signal correction methods

Juan Pablo Cruz-Bastida, Ran Zhang, Daniel Gomez-Cardona, Guang-Hong Chen

Author Affiliations +

Proceedings Volume 10948, Medical Imaging 2019: Physics of Medical Imaging; 1094830 (2019) https://doi.org/10.1117/12.2512889
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

In previous works, it has been demonstrated that CT number estimates are biased at low-dose levels for FBPbased CT. The purpose of this work was to explore the potential of noise-reduction methods to address this limitation. One may speculate that these potential CT number bias issues may have been addressed by noisereduction schemes, such as those implemented in commercial products. However, to the best of the authors’ knowledge, this is not the case. In this work, we performed an in-house noise-reduction implementation on benchtop-CT data, to further investigate under what conditions noise-reduction methods could favor quantitative low-dose CT. A quality assurance phantom was scanned at different dose levels, and the CT number bias was estimated for different material inserts of known composition, prior and after noise reduction. Anisotropic diffusion (AD) filtration was used as noise-reduction method, and independently applied in three different signal domains: raw counts, log-processed sinogram and reconstructed CT image. As result, AD filtration in the raw counts domain was the only noise-reduction scheme successful to considerably reduce CT number bias. Our results suggest that noise-reduction methods can help to preserve CT number accuracy to some degree when reducing radiation dose; however, their application cannot be arbitrarily extended to any signal domain. It was also observed that CT number bias reduction is greater for stronger filtration, which suggest that the overall CT image quality may limit the quantification accuracy when noise-reduction is performed.

Citation Download Citation

Juan Pablo Cruz-Bastida, Ran Zhang, Daniel Gomez-Cardona, and Guang-Hong Chen "Quantitative low-dose CT: potential value of low signal correction methods", Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 1094830 (7 March 2019); https://doi.org/10.1117/12.2512889

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE