title: Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU.
abstract: OBJECTIVE
  To accelerate the simultaneous algebraic reconstruction technique (SART) with motion compensation for speedy and quality computed tomography reconstruction by exploiting CUDA-enabled GPU.
  
  
  METHODS
  Two core techniques are proposed to fit SART into the CUDA architecture: (1) a ray-driven projection along with hardware trilinear interpolation, and (2) a voxel-driven back-projection that can avoid redundant computation by combining CUDA shared memory. We utilize the independence of each ray and voxel on both techniques to design CUDA kernel to represent a ray in the projection and a voxel in the back-projection respectively. Thus, significant parallelization and performance boost can be achieved. For motion compensation, we rectify each ray's direction during the projection and back-projection stages based on a known motion vector field.
  
  
  RESULTS
  Extensive experiments demonstrate the proposed techniques can provide faster reconstruction without compromising image quality. The process rate is nearly 100 projections s (-1), and it is about 150 times faster than a CPU-based SART. The reconstructed image is compared against ground truth visually and quantitatively by peak signal-to-noise ratio (PSNR) and line profiles. We further evaluate the reconstruction quality using quantitative metrics such as signal-to-noise ratio (SNR) and mean-square-error (MSE). All these reveal that satisfactory results are achieved. The effects of major parameters such as ray sampling interval and relaxation parameter are also investigated by a series of experiments. A simulated dataset is used for testing the effectiveness of our motion compensation technique. The results demonstrate our reconstructed volume can eliminate undesirable artifacts like blurring.
  
  
  CONCLUSIONS
  Our proposed method has potential to realize instantaneous presentation of 3D CT volume to physicians once the projection data are acquired.
authors.affiliation: Spatial Media Group, Computer Arts Lab, University of Aizu, Aizuwakamatsu, Japan.
authors.forename: Wai-Man
authors.initials: WM
authors.lastname: Pang
authors.forename: Jing
authors.initials: J
authors.lastname: Qin
authors.forename: Yuqiang
authors.initials: Y
authors.lastname: Lu
authors.forename: Yongming
authors.initials: Y
authors.lastname: Xie
authors.forename: Chee-Kong
authors.initials: CK
authors.lastname: Chui
authors.forename: Pheng-Ann
authors.initials: PA
authors.lastname: Heng
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003196:Computer Graphics; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D021621:Imaging, Three-Dimensional; D008433:Mathematics; D009038:Motion; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012984:Software; D013997:Time Factors; D014057:Tomography, X-Ray Computed