Multiresolution Hierarchical Shape Models in 3D Subcortical Brain Structures

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.

[1]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[2]  N. Dyn,et al.  A butterfly subdivision scheme for surface interpolation with tension control , 1990, TOGS.

[3]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[4]  Andrew Zisserman,et al.  Estimation of the partial volume effect in MRI , 2002, Medical Image Anal..

[5]  Max A. Viergever,et al.  elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.

[6]  Alejandro F. Frangi,et al.  Independent component analysis in statistical shape models , 2003, SPIE Medical Imaging.

[7]  Juan J. Cerrolaza,et al.  Hierarchical Statistical Shape Models of Multiobject Anatomical Structures: Application to Brain MRI , 2012, IEEE Transactions on Medical Imaging.

[8]  Dinggang Shen,et al.  Hierarchical active shape models, using the wavelet transform , 2003, IEEE Transactions on Medical Imaging.

[9]  Tony DeRose,et al.  Multiresolution analysis for surfaces of arbitrary topological type , 1997, TOGS.

[10]  Hugues Hoppe,et al.  Spherical parametrization and remeshing , 2003, ACM Trans. Graph..

[11]  Ronald M. Summers,et al.  Abdominal Multi-Organ Segmentation of CT Images Based on Hierarchical Spatial Modeling of Organ Interrelations , 2011, Abdominal Imaging.

[12]  Valerie Duay,et al.  Automatic segmentation of brain structures for radiation therapy planning , 2003, SPIE Medical Imaging.

[13]  Aaron F. Bobick,et al.  Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets , 2007, IEEE Transactions on Medical Imaging.