Paper:
A Parameterization Based Correspondence Method for PDM Building
Guangxu Li, Hyoungseop Kim, Joo Kooi Tan,
and Seiji Ishikawa
Department of Mechanical and Control Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka 804-8550, Japan
- [1] T. F. Cootes and C. J. Taylor, “Statistical Models of Appearance for Medical Image Analysis and Computer Vision,” Proc. SPIE Medical Imaging, pp. 236-248, 2001.
- [2] H. Park et al., “Construction of an abdominal probabilistic atlas and its application in segmentation,” IEEE Trans. on Medical Imaging, Vol.22, No.4, pp. 483-492, 2003.
- [3] N. Duta, A. Jain, and M. Dubuisson-Jolly, “Automatic construction of 2D shape models,” IEEE Trans. on Pattern Analysis and Machine Intell., Vol.23, No.5, pp. 433-445, 2001.
- [4] R. H. Davies, C. J. Twining, T. F. Cootes, and C. J. Taylor, “Building 3-D Statistical Shape Models by Direct Optimization,” IEEE Trans. on Medical Imaging, Vol.29, No.4, pp. 961-981, 2010.
- [5] M. A. Audette, F. P. Ferrie, and T. M. Peters, “An Algorithmic Overview of Surface Registration Techniques for Medical Imaging,” Medical Image Analysis, Vol.4, No.3, pp. 201-217, 2000.
- [6] H. Chui, “A new point matching algorithm for non-rigid registration,” Computer Vision and Image Understanding, Vol.89, No.2, pp. 114-141, 2003.
- [7] P. J. Besl, “A Method for Registration of 3-D Shapes,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.14, No.2, pp. 239-256, 1992.
- [8] L. Thomas, W. Stefan, R. Karl, and M. S. Peter, “Landmark-Based 3D Elastic Registration of Pre- and Postoperative Liver CT Data,” Proc. SPIE Medical Imaging, pp. 107-111, 2001.
- [9] M. Andriy and X. Song, “Point Set Registration: Coherent Point Drift,” IEEE Trans. on Pattern analysis and Machine Intelligence, Vol.32, No.12, pp. 2262-2275, 2011.
- [10] J. Bing and B. C. Vemuri, “Roust Point Set Registration Using Gaussian Mixture Models,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.33, No.8, pp. 1633-1645, 2011.
- [11] J. Qu, L. Gong, and L. Yang, “A 3D point matching algorithm for affine registration,” Int. J. of Computer Assisted Radiology and Surgery, Vol.6, No.2, pp. 229-236, 2011.
- [12] A. T. Heimann and H. Meinzer, “Statistical Shape Models for 3D Medical Image Segmentation: A review,” Medical Image Analysis, Vol.13, No.4, pp. 543-563, 2009.
- [13] D. Han and J. Bayouth et al., “Motion artifact Reduction in 4D Helical CT: Graph-based Structure Alignment,” Medical Computer Vision. Recognition Techniques and Applications inMedical Imaging, Lecture Notes in Computer Science, Vol.6533, pp. 63-73, 2011.
- [14] D. Han and J. Bayouth et al., “Feature Guided Motion Artifact Reduction with Structure-Awareness in 4D CT Images,” IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 1057-1064, 2011.
- [15] A. Sheffer, E. Praun, and K. Rose, “Mesh Parameterization Methods and their Applications,” Foundations and Trends in Computer Graphics and Vision, Vol.2, No.2, pp. 105-171, 2006.
- [16] A. Baumberg and D. Hogg, “Learning flexible models from image sequences,” Proc. of European Conf. on Computer Vision (ECCV), pp. 299-308, 1994.
- [17] Y. Wang, B. S. Peterson, and L. H. Staib, “Shape-based 3D surface correspondence using geodesics and local geometry,” Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pp. 644-651, 2000.
- [18] S. Belongie, J. Malik, and J. Puzicha, “Shape matching and object recognition using shape contexts,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.42, No.4, pp. 509-522, 2002.
- [19] G. L. Scott and H. C. Longuet-Higgins, “An algorithm for associating the features of two images,” Proc. of the Royal Society of London, Vol.244, No.1309, pp. 21-26, 1991.
- [20] A. Kelemen, G. Szekely, and G. Gerig, “Elastic model-based segmentation of 3-D neuroradiological data sets,” IEEE Trans. on Medical Imaging, Vol.18, No.10, pp. 828-839, 1999.
- [21] D. Meier and E. Fisher, “Parameter space warping: shape-based correspondence between morphologically different objects,” IEEE Trans. on Medical Imaging, Vol.21, No.1, pp. 31-47, 2002.
- [22] X. Gu, Y. Wang, T. F. Chan, P. M. Thompson, and S. Yau, “Genus Zero Surface Conformal Mapping and Its Application to Brain Surface Mapping,” IEEE Trans. on Medical Imaging, Vol.23, No.8, pp. 949-958, 2004.
- [23] X. Gu, Y. Wang, and S. T. Yau, “Geometric Compression Using Riemann Surface Structure,” Communications in Information and Systems, Vol.3, No.3, pp. 171-182, 2004.
- [24] M. S. Floater and K. Hormann, “Surface Parameterization: a Tutorial and Survey,” Advances in Multiresolution for Geometric Modelling Mathematics and Visualization, pp. 157-186, 2005.
- [25] M. Mark, D. Mathieu, S. Peter, and H. B. Alan, “Discrete Differential-Geometry Operators for Triangulated 2-Manifolds,” Proc. of Visualization and Mathematics (VisMath), 2002.
- [26] J. Arvo, “Fast Random Rotation Matrices,” Graphics Gems III, Academic Press, 1992.
- [27] W. E. Lorensen and H. E. Cline, “Marching Cubes: A High Resolution 3D Surface Construction Algorithm,” ACM SIGGRAPH computer Graphics, Vol.21, No.4, pp. 163-169, 1987.
- [28] C. J. Twining, T. F. Cootes et al., “A unified information-theoretic approach to groupwise non-rigid registration and model building,” Information Proc. in Medical Imaging (IPMI), pp. 167-198, 2005.
- [29] Y. Wang, “Brain Surface Conformal Parameterization With the Ricci Flow,” IEEE Trans. on Medical Imaging, Vol.31, No.2, pp. 251-264, 2012.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.