Abstract
We propose a fast and robust registration technique for accurately imaging lung perfusion and efficiently detecting pulmonary embolism in chest CT angiography. For the registration of a pair of CT scans, a proper geometrical transformation is found through the following steps: First, the initial registration using an optimal cube is performed for correcting the gross translational mismatch. Second, the initial alignment is refined by iterative surface registration. For fast and robust convergence of the distance measure to the optimal value, a 3D distance map is generated by the narrow-band distance propagation. Third, 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 ten patients of pre- and post-contrast images in chest CT angiography. Experimental results show that the performance of our method is very promising compared with conventional method with the aspects of its visual inspection, accuracy and processing time.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Schoepf, U.J., Costello, P.: CT angiography for diagnosis of pulmonary embolism: state of the art. Radiology 230, 329–337 (2004)
Patel, S., Kazerooni, E.A., Cascade, P.N.: Pulmonary embolism: optimization of small pulmonary artery visualization at multi-detector row CT. Radiology 227, 455–460 (2003)
Schoepf, U.J., Holzknecht, N., Helmberger, T.K., et al.: Subsegmental pulmonary emboli: improved detection with thin-collimation multi-detector row spiral CT. Radiology 222, 483–490 (2002)
Ko, J.P., Naidich, D.P.: Computer-aided diagnosis and the evaluation of lung disease. Journal of Thoraic Imaging 19(3), 136–155 (2004)
Herzog, P., Wildberger, J.E., Niethammer, M., et al.: CT perfusion imaging of the lung in pulmonary embolism. Acad. Radiol. 10, 1132–1146 (2003)
Wildberger, J.E., Schoepf, U.J., Mahnken, A.H., et al.: Approaches to CT perfusion imaging in pulmonary embolism. Roentgenology, 64–73 (2005)
Chung, M.J., Goo, J.M., Im, J.G., et al.: CT perfusion image of the lung: value in the detection of pulmonary embolism in a porcine model. Investigative Radiology 39(10), 633–640 (2004)
Yim, Y., Hong, H., Shin, Y.G.: Hybrid lung segmentation in chest CT images for computer-aided diagnosis. In: Proc. of HEALTHCOM 2005 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hong, H., Lee, J. (2005). Digital Subtraction CT Lung Perfusion Image Based on 3D Affine Registration. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds) Pattern Recognition. DAGM 2005. Lecture Notes in Computer Science, vol 3663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550518_49
Download citation
DOI: https://doi.org/10.1007/11550518_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28703-2
Online ISBN: 978-3-540-31942-9
eBook Packages: Computer ScienceComputer Science (R0)