title: A sinogram denoising algorithm for low-dose computed tomography.
abstract: BACKGROUND
  From the viewpoint of the patients' health, reducing the radiation dose in computed tomography (CT) is highly desirable. However, projection measurements acquired under low-dose conditions will contain much noise. Therefore, reconstruction of high-quality images from low-dose scans requires effective denoising of the projection measurements.
  
  
  METHODS
  We propose a denoising algorithm that is based on maximizing the data likelihood and sparsity in the gradient domain. For Poisson noise, this formulation automatically leads to a locally adaptive denoising scheme. Because the resulting optimization problem is hard to solve and may also lead to artifacts, we suggest an explicitly local denoising method by adapting an existing algorithm for normally-distributed noise. We apply the proposed method on sets of simulated and real cone-beam projections and compare its performance with two other algorithms.
  
  
  RESULTS
  The proposed algorithm effectively suppresses the noise in simulated and real CT projections. Denoising of the projections with the proposed algorithm leads to a substantial improvement of the reconstructed image in terms of noise level, spatial resolution, and visual quality.
  
  
  CONCLUSIONS
  The proposed algorithm can suppress very strong quantum noise in CT projections. Therefore, it can be used as an effective tool in low-dose CT.
authors.affiliation: 2366 Main Mall, Vancouver, V6T 1Z4, BC, Canada. karimi@ece.ubc.ca.
authors.forename: Davood
authors.initials: D
authors.lastname: Karimi
authors.affiliation: 2151 Wesbrook Mall, Vancouver, V6T 1Z3, BC, Canada. deman.pierre@gmail.com.
authors.forename: Pierre
authors.initials: P
authors.lastname: Deman
authors.affiliation: 2366 Main Mall, Vancouver, V6T 1Z4, BC, Canada. rababw@ece.ubc.ca.
authors.forename: Rabab
authors.initials: R
authors.lastname: Ward
authors.affiliation: 2151 Wesbrook Mall, Vancouver, V6T 1Z3, BC, Canada. nlford@dentistry.ubc.ca.
authors.forename: Nancy
authors.initials: N
authors.lastname: Ford
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D016012:Poisson Distribution; D011829:Radiation Dosage; D059629:Signal-To-Noise Ratio; D014057:Tomography, X-Ray Computed / Q000379:methods*