Simultaneous Reduction in Noise and Cross-Contamination Artifacts for Dual-Energy X-Ray CT

Baojun Li,Xiaoye Wu,Jack Luo,Baohong Li,Jiandong Mao,Peng Tang

doi:10.1155/2013/417278

Abstract

Purpose. Dual-energy CT imaging tends to suffer from much lower signal-to-noise ratio than single-energy CT. In this paper, we propose an improved anticorrelated noise reduction (ACNR) method without causing cross-contamination artifacts. Methods. The proposed algorithm diffuses both basis material density images (e.g., water and iodine) at the same time using a novel correlated diffusion algorithm. The algorithm has been compared to the original ACNR algorithm in a contrast-enhanced, IRB-approved patient study. Material density accuracy and noise reduction are quantitatively evaluated by the percent density error and the percent noise reduction. Results. Both algorithms have significantly reduced the noises of basis material density images in all cases. The average percent noise reduction is 69.3% and 66.5% with the ACNR algorithm and the proposed algorithm, respectively. However, the ACNR algorithm alters the original material density by an average of 13% (or 2.18 mg/cc) with a maximum of 58.7% (or 8.97 mg/cc) in this study. This is evident in the water density images as massive cross-contaminations are seen in all five clinical cases. On the contrary, the proposed algorithm only changes the mean density by 2.4% (or 0.69 mg/cc) with a maximum of 7.6% (or 1.31 mg/cc). The cross-contamination artifacts are significantly minimized or absent with the proposed algorithm. Conclusion. The proposed algorithm can significantly reduce image noise present in basis material density images from dual-energy CT imaging, with minimized cross-contaminations compared to the ACNR algorithm.

Highlights

Dual-energy X-ray CT permits retrospective decomposition of anatomy into basis material density maps from the low- and high-kVp acquisitions [1,2,3,4,5,6,7,8]
It is well known that the basis material density images suffer from much lower signal-to-noise ratio (SNR) than single-energy CT images
We propose an improved anticorrelated noise reduction (ACNR) algorithm, based on correlated anisotropic diffusion, which can simultaneously reduce the image noise and minimize the crosscontamination in the basis material density images

Summary

Introduction

Dual-energy X-ray CT permits retrospective decomposition of anatomy into basis material density maps (images) from the low- and high-kVp acquisitions [1,2,3,4,5,6,7,8]. It is well known that the basis material density images suffer from much lower signal-to-noise ratio (SNR) than single-energy CT images. Has proposed to use a high-pass filtered version of the first basis material density image (e.g., water) to noise reduce the complimentary basis material density image (e.g., iodine) [12]. Cross-contamination is very undesirable as it alters the original density values and introduces false anatomical or pathological information to the complimentary basis material density image It hinders the quantification accuracy of dual-energy CT imaging, and potentially leads to misdiagnosis [9]. We propose an improved ACNR algorithm, based on correlated anisotropic diffusion, which can simultaneously reduce the image noise and minimize the crosscontamination in the basis material density images. Since our algorithm performs diffusion in both basis material density images simultaneously, it is more efficient than the original ACNR algorithms

Methods

Results

Discussions