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Abstract
In this paper, we propose a novel technique of lung surface registration for investigating temporal changes such as growth rates of pulmonary nodules. For the registration of a pair of CT scans, a proper geometrical transformation is found through the following steps: First, optimal cube registration is performed for the initial gross registration. Second, for allowing fast and robust convergence on the optimal value, a 3D distance map is generated by the local distance propagation. Third, the distance measure between surface boundary points is repeatedly evaluated by the selective distance measure. Experimental results show that the performance of our registration method is very promising compared with conventional methods in the aspects of its computation time androbustness.
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References
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Authors and Affiliations
School of Electrical Engineering and Computer Science BK21: Information Technology, Seoul National University, San 56-1 Shinlim 9-dong Kwanak-gu, Seoul, 151-742, Korea
Helen Hong
School of Electrical Engineering and Computer Science, Seoul National University,
Jeongjin Lee & Yeong Gil Shin
Dept. of Radiology, Seoul National University Bundang Hospital, 300, Gumi-dong, Sungnam-si, Kyunggi-do, Korea
Kyung Won Lee
- Helen Hong
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- Jeongjin Lee
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- Kyung Won Lee
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- Yeong Gil Shin
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Editor information
Editors and Affiliations
Dept. System Engineering and Automation, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
Alberto Sanfeliu
Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Luis Enrique Erro No. 1, 72840, Sta. Maria Tonantzintla, Puebla, Mexico
José Francisco Martínez Trinidad
Computer Science Department, National Institute of Astrophysics, Optics and Electronics, (INAOE), Luis Enrique Erro No.1, 72840, Sta. Maria Tonantzintla, Puebla, Mexico
Jesús Ariel Carrasco Ochoa
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Hong, H., Lee, J., Lee, K.W., Shin, Y.G. (2004). Automatic Lung Surface Registration Using Selective Distance Measure in Temporal CT Scans. In: Sanfeliu, A., Martínez Trinidad, J.F., Carrasco Ochoa, J.A. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2004. Lecture Notes in Computer Science, vol 3287. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30463-0_65
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