CORRESPONDENCE EVALUATION IN LOCAL SHAPE ANALYSIS AND STRUCTURAL SUBDIVISION

Regional volumetric and local shape analysis has become of increasing interest to the neuroimaging community due to the potential to locate morphological changes. In this paper we compare three common correspondence methods applied to two studies of hippocampal shape in schizophrenia: correspondence via deformable registration, spherical harmonics (SPHARM) and minimum description length (MDL) optimization. These correspondence methods are evaluated in respect to local statistical shape analysis and structural subdivision analysis. Results show a non-negligible influence of the choice of correspondence especially in studies with low numbers of subjects. The differences are especially striking in the structural subdivision analysis and hints at a possible source for the diverging findings in many subdivision studies. Our comparative study is not meant to be exhaustive, but rather raises awareness of the issue and shows that assessing the validity of the correspondence is an important step.

[1]  Jerry L Prince,et al.  A computerized approach for morphological analysis of the corpus callosum. , 1996, Journal of computer assisted tomography.

[2]  Timothy F. Cootes,et al.  A minimum description length approach to statistical shape modeling , 2002, IEEE Transactions on Medical Imaging.

[3]  Timothy F. Cootes,et al.  Use of active shape models for locating structures in medical images , 1994, Image Vis. Comput..

[4]  Michael I. Miller,et al.  On The Geometry and Shape of Brain Sub-Manifolds , 1997, Int. J. Pattern Recognit. Artif. Intell..

[5]  Guido Gerig,et al.  Parametrization of Closed Surfaces for 3-D Shape Description , 1995, Comput. Vis. Image Underst..

[6]  Anand Rangarajan,et al.  The Softassign Procrustes Matching Algorithm , 1997, IPMI.

[7]  Martin Styner,et al.  Statistical surface-based morphometry using a nonparametric approach , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[8]  Martin Styner,et al.  Evaluation of 3D Correspondence Methods for Model Building , 2003, IPMI.

[9]  Dominik S. Meier,et al.  Parameter space warping: shape-based correspondence between morphologically different objects , 2002, IEEE Transactions on Medical Imaging.

[10]  D'arcy W. Thompson.  On growth and form i , 1943 .

[11]  D'arcy W. Thompson.  On Growth and Form , 1945 .

[12]  D. Louis Collins,et al.  Hippocampal shape analysis using medial surfaces , 2005, NeuroImage.

[13]  Fillia Makedon,et al.  Hippocampal shape analysis: surface-based representation and classification , 2003, SPIE Medical Imaging.

[14]  A. C. Fabergé.  On growth and form. Second edition , 1942 .

[15]  Martin Styner,et al.  Statistical shape analysis of neuroanatomical structures based on medial models , 2003, Medical Image Anal..

[16]  Ch. Brechbuhler,et al.  Parameterisation of closed surfaces for 3-D shape description , 1995 .

[17]  Christopher J. Taylor,et al.  Automatic construction of eigenshape models by direct optimization , 1998, Medical Image Anal..

[18]  J. Thompson,et al.  MOVPE growth for the fabrication of OEICs , 1992 .

[19]  Paul A. Yushkevich,et al.  Segmentation, registration, and measurement of shape variation via image object shape , 1999, IEEE Transactions on Medical Imaging.

[20]  D'arcy W. Thompson,et al.  On Growth and Form , 1917, Nature.

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

[22]  Timothy F. Cootes,et al.  The Use of Active Shape Models for Locating Structures in Medical Images , 1993, IPMI.