Abstract
Point Distribution Models (PDM) are one of the most extended methods to characterize the underlying population of set of samples, whose usefulness has been demonstrated in a wide variety of applications, including medical imaging. However, one important issue remains unsolved: the large number of training samples required. This problem becomes critical as the complexity of the problem increases, and the modeling of 3D multiobjects/organs represents one of the most challenging cases. Based on the 3D wavelet transform, this paper introduces a multiresolution hierarchical variant of PDM (MRH-PDM) able to efficiently characterize the different inter-object relationships, as well as the particular locality of each element separately. The significant advantage of this new method over two previous approaches in terms of accuracy has been successfully verified for the particular case of 3D subcortical brain structures.
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Duay, V., Li, R., DuBois Daische, A., Merchant, T.E., Cmelak, A.J., Donnely, E.F., Niermann, K.J., Macq, B., Dawant, B.M.: Automatic Segmentation of Brain Structures for Radiation Therapy Planning. In: Proc. of SPIE Medical Imaging 2003: Image Processing, pp. 517–526 (2003)
Nain, D., Haker, S., Bobick, A., Tannenbaum, A.: Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets. IEEE Trans. Med. Imaging 26(4), 598–618 (2007)
Cerrolaza, J.J., Villanueva, A., Cabeza, R.: Hierarchical Statistical Shape Models of Multiobject Anatomical Structures: Application to Brain MRI. IEEE Trans. Med. Imaging 31(3), 71–724 (2012)
Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active Shape Models Their Training and Application. Comput. Vis. Image Underst. 61(1), 38–59 (1995)
Lounsbery, M., DeRose, T.D., Warren, J.: Multiresolution Analysis for Surfaces of Arbitrary Topological Type. ACM Trans. Graph. 16(1), 34–73 (1997)
Praun, E., Hoppe, H.: Spherical Parametrization and Remeshing. ACM Trans. Graph. (SIGGRAPH) 22(3), 340–349 (2003)
Davatzikos, C., Tao, X., Shen, D.: Hierarchical Active Shape Models, Using the Wavelet Transform. IEEE Trans. Med. Imag. 22(3), 414–423 (2003)
IBSR. The Internet Brain Segmentation Repository (IBSR), http://www.cma.mgh.harvard.edu/ibsr/
Klein, S., Staring, M., Murphy, K., Viergever, M.A., Pluim, J.P.W.: Elastix: A Toolbox for Intensity Based Medical Image Registration. IEEE Trans. Med. Imaging 29(1), 196–205 (2010)
Okada, T., Linguraru, M.G., Yoshida, Y., Hori, M., Summers, R.M., Chen, Y.-W., Tomiyama, N., Sato, Y.: Abdominal Multi-Organ Segmentation of CT Images Based on Hierarchical Spatial Modeling of Organ Interrelations. In: Yoshida, H., Sakas, G., Linguraru, M.G. (eds.) Abdominal Imaging 2011. LNCS, vol. 7029, pp. 173–180. Springer, Heidelberg (2012)
Gonzalez Ballester, M.A., Zisserman, A.P., Brady, M.: Estimation of the Partial Volume Effect in MRI. Medical Image Analysis 6(4), 389–405 (2002)
Daubechies, I.: Ten Lectures on Wavelets. Soc. for Industrial and Applied Math., Philadelphia (1992)
Dyn, N., Levine, D., Gregory, J.A.: A Butterfly Subdivision Scheme for Surface Interpolation with Tension Control. ACM Trans. Graph. 9(2), 160–169 (1990)
Uzumcu, M., Frangi, A.F., Reiber, J.H., Lelieveldt, P.F.: Independent Component Analysis in Statistical Shape Models. In: Proc. of SPIE, pp. 375–383 (2003)
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Cerrolaza, J.J., Herrezuelo, N.C., Villanueva, A., Cabeza, R., González Ballester, M.A., Linguraru, M.G. (2013). Multiresolution Hierarchical Shape Models in 3D Subcortical Brain Structures. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. MICCAI 2013. Lecture Notes in Computer Science, vol 8150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40763-5_79
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DOI: https://doi.org/10.1007/978-3-642-40763-5_79
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