Dose reduction in CT with correlated-polarity noise reduction: Context-dependent spatial resolution and noise properties demonstrating two-fold dose reduction with minimal artifacts

Journal Article

Correlated-polarity noise reduction (CPNR) is a novel noise reduction technique that uses a statistical approach to reducing noise while maintaining excellent spatial resolution and a traditional noise appearance. It was demonstrated in application to CT imaging for the first time at SPIE 2013 and showed qualitatively excellent image quality at half of normal CT dose. In this current work, we measure quantitatively the spatial resolution and noise properties of CPNR in CT imaging. To measure the spatial resolution, we developed a metrology approach that is suitable for nonlinear algorithms such as CPNR. We introduce the formalism of Signal Modification Factor, SMF(u,v), which is the ratio in frequency space of the CPNR-processed image divided by the noise-free image, averaged over an ensemble of ROIs in a given anatomical context. SMF is a nonlinear analog to the MTF. We used XCAT computer-generated anthropomorphic phantom images followed by projection space processing with CPNR. The SMF revealed virtually no effect from CPNR on spatial resolution of the images (<7% degradation at all frequencies). Corresponding contextdependent NPS measurements generated with CPNR at half-dose were about equal to the NPS of full-dose images without CPNR. This result demonstrates for the first time the quantitative determination of a two-fold reduction in dose with CPNR with less than 7% reduction in spatial resolution. We conclude that CPNR shows strong promise as a method for reduction of noise (and hence, dose) in CT. CPNR may also be used in combination with iterative reconstruction techniques for yet further dose reduction, pending further investigation. © 2014 SPIE.

Full Text

Duke Authors

Cited Authors

  • Dobbins, JT; Wells, JR; Segars, WP

Published Date

  • January 1, 2014

Published In

Volume / Issue

  • 9033 /

International Standard Serial Number (ISSN)

  • 1605-7422

Digital Object Identifier (DOI)

  • 10.1117/12.2043685

Citation Source

  • Scopus