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MSCT Lung Perfusion Imaging Based on Multi-stage Registration

  • Helen Hong
  • Jeongjin Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)

Abstract

We propose a novel subtraction-based method for visualizing segmental and subsegmental pulmonary embolism. For the registration of a pair of CT angiography, a proper geometrical transformation is found through the following steps: First, point-based rough registration is performed for correcting the gross translational mismatch. The center of inertia (COI), apex and hilar point of each unilateral lung are proposed as the reference point. Second, the initial alignment is refined by iterative surface registration. Third, thin-plate spline warping is used to accurately align inner region of lung parenchyma. Finally, enhanced vessels are visualized by subtracting registered pre-contrast images from post-contrast images. To facilitate visualization of parenchymal enhancement, color-coded mapping and image fusion is used. Our method has been successfully applied to four pairs of CT angiography.

Keywords

Pulmonary Embolism Compute Tomography Angiography Compute Tomography Perfusion Parenchymal Enhancement Compute Tomography Perfusion Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Helen Hong
    • 1
  • Jeongjin Lee
    • 2
  1. 1.School of Electrical Engineering and Computer Science, BK21: Information TechnologySeoul National University 
  2. 2.School of Electrical Engineering and Computer ScienceSeoul National UniversitySeoulKorea

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