Multi-stage Registration for Quantification of Lung Perfusion in Chest CT Images

  • Helen Hong
  • Jeongjin Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4091)


We propose a multi-stage registration technique to identify perfusion defects of the lungs using pre- and post-contrast CT images. Our method is composed of four main steps. First, point-based rough registration is performed for correcting 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 narrow-band surface registration. Third, thin-plate spline warping is used to accurately align inner region of the lung. 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 applied to subtracted images. Our method has been evaluated using eight pairs of pre- and post-contrast CT images by visual inspection, accuracy evaluation and processing time.


Lung Perfusion Parenchymal Enhancement Surface Registration Compute Tomography Perfusion Image Chest Compute Tomography 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 2006

Authors and Affiliations

  • Helen Hong
    • 1
  • Jeongjin Lee
    • 2
  1. 1.Division of Multimedia Engineering, College of Information and MediaSeoul Women’s UniversitySeoulKorea
  2. 2.School of Computer Science and EngineeringSeoul National UniversitySeoulKorea

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