title: Adaptive noise correction of dual-energy computed tomography images.
abstract: OBJECTIVE
  Noise reduction in material density images is a necessary preprocessing step for the correct interpretation of dual-energy computed tomography (DECT) images. In this paper we describe a new method based on a local adaptive processing to reduce noise in DECT images
  
  
  METHODS
  An adaptive neighborhood Wiener (ANW) filter was implemented and customized to use local characteristics of material density images. The ANW filter employs a three-level wavelet approach, combined with the application of an anisotropic diffusion filter. Material density images and virtual monochromatic images are noise corrected with two resulting noise maps.
  
  
  RESULTS
  The algorithm was applied and quantitatively evaluated in a set of 36 images. From that set of images, three are shown here, and nine more are shown in the online supplementary material. Processed images had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than the raw material density images. The average improvements in SNR and CNR for the material density images were 56.5 and 54.75%, respectively.
  
  
  CONCLUSIONS
  We developed a new DECT noise reduction algorithm. We demonstrate throughout a series of quantitative analyses that the algorithm improves the quality of material density images and virtual monochromatic images.
authors.affiliation: Department of Computer Science, University of Calgary, 2500 University Dr NW, Calgary, AB, T2N 1N4, Canada. rafaelsimonmaia@gmail.com.
authors.forename: Rafael Simon
authors.initials: RS
authors.lastname: Maia
authors.affiliation: Department of Computer Science, University of Calgary, 2500 University Dr NW, Calgary, AB, T2N 1N4, Canada.
authors.forename: Christian
authors.initials: C
authors.lastname: Jacob
authors.affiliation: Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ, 85259, USA.
authors.forename: Amy K
authors.initials: AK
authors.lastname: Hara
authors.affiliation: Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ, 85259, USA.
authors.forename: Alvin C
authors.initials: AC
authors.lastname: Silva
authors.affiliation: Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ, 85259, USA.
authors.forename: William
authors.initials: W
authors.lastname: Pavlicek
authors.affiliation: Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ, 85259, USA.
authors.forename: J Ross
authors.initials: JR
authors.lastname: Mitchell
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D019047:Phantoms, Imaging; D059629:Signal-To-Noise Ratio; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Adaptive Wiener filter; Dual-energy computed tomography; Material density; Noise reduction