title: Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT.
abstract: OBJECTIVE
  The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain.
  
  
  METHODS
  3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability.
  
  
  RESULTS
  The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold speed-up of the processing (from 1336 to 150 s).
  
  
  CONCLUSIONS
  Adaptive anisotropic filtering has the potential to substantially improve image quality and/or reduce the radiation dose required for obtaining 3D image data using cone beam CT.
authors: Department of Radiology, Stanford University, Stanford, CA 94305, USA. akmaier@stanford.edu
authors: Andreas
authors: A
authors: Maier
authors: Lars
authors: L
authors: Wigstrom
authors: Hannes G
authors: HG
authors: Hofmann
authors: Joachim
authors: J
authors: Hornegger
authors: Lei
authors: L
authors: Zhu
authors: Norbert
authors: N
authors: Strobel
authors: Rebecca
authors: R
authors: Fahrig
mesh_terms: D000818:Animals; D016880:Anisotropy; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006321:Heart / Q000000981:diagnostic imaging; D021621:Imaging, Three-Dimensional / Q000379:methods*; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods*