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

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...

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Publicado en:BioMed Research International Vol. 2013; pp. 417278 - 417279
Autores principales: Li, Baojun, Li, Baohong, Luo, Jack, Tang, Peng, Mao, Jiandong, Wu, Xiaoye
Formato: research Journal Article
Publicado: Wiley-Blackwell 2013
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2013
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      pub: Wiley-Blackwell
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        atl: Simultaneous Reduction in Noise and Cross-Contamination Artifacts for Dual-Energy X-Ray CT.
      aug:
        au:
          Li, Baojun
          Li, Baohong
          Luo, Jack
          Tang, Peng
          Mao, Jiandong
          Wu, Xiaoye
        affil: Department of Radiology, Boston University Medical Center, Boston, MA 02118, USA.
      sug:
        subj:
          Artifacts
          Sensitivity and Specificity
          Tomography, X-Ray Computed
          Algorithms
          Human
          Radiographic Image Enhancement
          Radiography, Abdominal
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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