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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References
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© 2005 Springer-Verlag Berlin Heidelberg
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Hong, H., Lee, J. (2005). MSCT Lung Perfusion Imaging Based on Multi-stage Registration. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_57
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DOI: https://doi.org/10.1007/11578079_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
eBook Packages: Computer ScienceComputer Science (R0)
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