• DocumentCode
    2938477
  • Title

    A new representation of intensity atlas for GPU-accelerated instance generation

  • Author

    Gong, Ren Hui ; Stewart, James ; Abolmaesumi, Purang

  • Author_Institution
    Sch. of Comput., Queen´´s Univ., Kingston, ON, Canada
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 4 2010
  • Firstpage
    4399
  • Lastpage
    4402
  • Abstract
    Fast instance generation is a key requirement in atlas-based registration and other problems that need a large number of atlas instances. This paper describes a new method to represent and construct intensity atlases. Both geometry and intensity information are represented using B-spline deformation lattices; intensities are approximated using the multi-level B-spline approximation algorithm during model creation and the parallel computation capability of modern graphics processing units is used to accelerate the process of instance generation. Experiments with distal radius CTs show that, with a coefficients-to-voxels ratio of 0.16, intensities can be approximated up to an average accuracy of 2 ± 17 grey-levels (out of 3072 total grey-levels), and instances of resolution 256×256×200 can be produced in a rate of 25 instances per second with a GeForce GTX 285 video card, which is about 500 times performance improvement over the traditional method that uses plain CPU.
  • Keywords
    computer graphics; computerised tomography; image registration; image representation; medical image processing; splines (mathematics); B-spline deformation lattices; GPU-accelerated instance generation; GeForce GTX 285 video card; atlas-based registration; coefficients-to-voxels ratio; computed tomography; distal radius CT; fast instance generation; graphics processing units; intensity atlas; model creation; multilevel B-spline approximation; parallel computation; signal representation; Approximation methods; Geometry; Graphics processing unit; Lattices; Shape; Spline; Training; Algorithms; Computer Graphics; Computer Simulation; Humans; Models, Anatomic; Pattern Recognition, Automated; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; Tomography, X-Ray Computed; Wrist;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
  • Conference_Location
    Buenos Aires
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4123-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2010.5627135
  • Filename
    5627135