Hierarchical Statistical Shape Models of Multiobject Anatomical Structures: Application to Brain MRI

The accurate segmentation of subcortical brain structures in magnetic resonance (MR) images is of crucial importance in the interdisciplinary field of medical imaging. Although statistical approaches such as active shape models (ASMs) have proven to be particularly useful in the modeling of multiobject shapes, they are inefficient when facing challenging problems. Based on the wavelet transform, the fully generic multiresolution framework presented in this paper allows us to decompose the interobject relationships into different levels of detail. The aim of this hierarchical decomposition is twofold: to efficiently characterize the relationships between objects and their particular localities. Experiments performed on an eight-object structure defined in axial cross sectional MR brain images show that the new hierarchical segmentation significantly improves the accuracy of the segmentation, and while it exhibits a remarkable robustness with respect to the size of the training set.

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

[2]  Horst Karl Hahn.  Computer-assistance in neuroimaging: From quantitative image analysis to computer-aided diagnosis , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[3]  H Grosman,et al.  Computed tomography and lateral ventricular asymmetry: clinical and brain structural correlates. , 1990, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

[4]  Conglin Lu,et al.  Statistical Multi-Object Shape Models , 2007, International Journal of Computer Vision.

[5]  David Salesin,et al.  Wavelets for computer graphics: theory and applications , 1996 .

[6]  W. Eric L. Grimson,et al.  Mutual information in coupled multi-shape model for medical image segmentation , 2004, Medical Image Anal..

[7]  Zohreh Azimifar,et al.  Wavelet shrinkage with correlated wavelet coefficients , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[8]  Alejandro F. Frangi,et al.  Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling , 2002, IEEE Transactions on Medical Imaging.

[9]  N. Karabulut,et al.  Cerebral lateral ventricular asymmetry on CT: how much asymmetry is representing pathology? , 2008, Surgical and Radiologic Anatomy.

[10]  A. Haar.  Zur Theorie der orthogonalen Funktionensysteme , 1910 .

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

[12]  C. Goodall.  Procrustes methods in the statistical analysis of shape , 1991 .

[13]  Verónica Médina-Bañuelos,et al.  Data-driven brain MRI segmentation supported on edge confidence and a priori tissue information , 2006, IEEE Transactions on Medical Imaging.

[14]  Paul A. Yushkevich,et al.  Deformable M-Reps for 3D Medical Image Segmentation , 2003, International Journal of Computer Vision.

[15]  David Salesin,et al.  Multiresolution curves , 1994, SIGGRAPH.

[16]  Mikkel B. Stegmann.  On Properties of Active Shape Models , 2000 .

[17]  P. Shui,et al.  Image denoising algorithm via best wavelet packet base using Wiener cost function , 2007 .

[18]  Milan Sonka,et al.  Segmentation and interpretation of MR brain images. An improved active shape model , 1998, IEEE Transactions on Medical Imaging.

[19]  Timothy F. Cootes,et al.  Training Models of Shape from Sets of Examples , 1992, BMVC.

[20]  M. Stella Atkins,et al.  Fully automatic segmentation of the brain in MRI , 1998, IEEE Transactions on Medical Imaging.

[21]  Yutaka Hata,et al.  Computer-aided diagnosis system of systems for neonatal and infantile brain using MR images , 2008, 2008 IEEE International Conference on System of Systems Engineering.

[22]  Conglin Lu,et al.  Estimating the Statistics of Multi-object Anatomic Geometry Using Inter-object Relationships , 2005, DSSCV.

[23]  Bram van Ginneken,et al.  Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database , 2006, Medical Image Anal..

[24]  Vikash Sethia.  Wavelet Applications in Medicine , 2003 .

[25]  Gábor Székely,et al.  Multiscale Medial Loci and Their Properties , 2003, International Journal of Computer Vision.

[26]  R. Kikinis,et al.  Computer-assisted interactive three-dimensional planning for neurosurgical procedures. , 1996, Neurosurgery.

[27]  Isabelle Bloch,et al.  Computational modeling of thoracic and abdominal anatomy using spatial relationships for image segmentation , 2004, Real Time Imaging.

[28]  Juan J. Cerrolaza,et al.  Multi-Shape-Hierarchical Active Shape Models , 2011 .

[29]  Alejandro F. Frangi,et al.  Active shape model segmentation with optimal features , 2002, IEEE Transactions on Medical Imaging.

[30]  Wufan Chen,et al.  Diagnosis system of computer-aided brain MRI using content-based image retrieval , 2008, 2008 International Conference on Information Technology and Applications in Biomedicine.

[31]  Juan J. Cerrolaza,et al.  Shape Constraint Strategies: Novel Approaches and Comparative Robustness , 2011, BMVC.

[32]  Reinhilde Jacobs,et al.  Detecting Reduced Bone Mineral Density From Dental Radiographs Using Statistical Shape Models , 2007, IEEE Transactions on Information Technology in Biomedicine.

[33]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[34]  Hayit Greenspan,et al.  An Adaptive Mean-Shift Framework for MRI Brain Segmentation , 2009, IEEE Transactions on Medical Imaging.

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

[36]  J. Soares,et al.  Brain anatomy and development in autism: review of structural MRI studies , 2003, Brain Research Bulletin.

[37]  Christopher J. Taylor,et al.  Kernel Principal Component Analysis and the construction of non-linear Active Shape Models , 2001, BMVC.

[38]  Sankatha Prasad Singh,et al.  Approximation Theory, Wavelets and Applications , 1995 .

[39]  M. LeMay,et al.  Abnormalities of the left temporal lobe and thought disorder in schizophrenia. A quantitative magnetic resonance imaging study. , 1992, The New England journal of medicine.

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

[41]  Daniel Rueckert,et al.  Hierarchical Statistical Shape Analysis and Prediction of Sub-cortical Brain Structures , 2007 .