• DocumentCode
    1156162
  • Title

    Efficient Implementation for Spherical Flux Computation and Its Application to Vascular Segmentation

  • Author

    Law, Max W K ; Chung, Albert C S

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong
  • Volume
    18
  • Issue
    3
  • fYear
    2009
  • fDate
    3/1/2009 12:00:00 AM
  • Firstpage
    596
  • Lastpage
    612
  • Abstract
    Spherical flux is the flux inside a spherical region, and it is very useful in the analysis of tubular structures in magnetic resonance angiography and computed tomographic angiography. The conventional approach is to estimate the spherical flux in the spatial domain. Its running time depends on the sphere radius quadratically, which leads to very slow spherical flux computation when the sphere size is large. This paper proposes a more efficient implementation for spherical flux computation in the Fourier domain. Our implementation is based on the reformulation of the spherical flux calculation using the divergence theorem, spherical step function, and the convolution operation. With this reformulation, most of the calculations are performed in the Fourier domain. We show how to select the frequency subband so that the computation accuracy can be maintained. It is experimentally demonstrated that, using the synthetic and clinical phase contrast magnetic resonance angiographic volumes, our implementation is more computationally efficient than the conventional spatial implementation. The accuracies of our implementation and that of the conventional spatial implementation are comparable. Finally, the proposed implementation can definitely benefit the computation of the multiscale spherical flux with a set of radii because, unlike the conventional spatial implementation, the time complexity of the proposed implementation does not depend on the sphere radius.
  • Keywords
    biomedical MRI; blood vessels; brain; computerised tomography; fast Fourier transforms; image segmentation; medical image processing; Fourier domain; computed tomographic angiography; convolution; divergence theorem; magnetic resonance angiography; spherical flux computation; spherical step function; vascular segmentation; Angiography; Biomedical imaging; Blood vessels; Computer applications; Convolution; Image analysis; Image segmentation; Magnetic analysis; Magnetic resonance; Tomography; Efficient implementation; flux; vascular segmentation; Algorithms; Blood Vessels; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Angiography; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2008.2010073
  • Filename
    4782069