Docteur de l'université Automatic Segmentation and Shape Analysis ...

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40 Chapter 2 Literature Review have been exploited in the detection of AD and to predict the onset of the dementia Csernansky et al. (2005). Shape surface represented by SPHARM has been employed to model the hippocampus (Gerig et al., 2001) and to detect the shape changes caused by AD (Li et al., 2007; Gutman et al., 2009; Gerardin et al., 2009; Zhou et al., 2009; Cuingnet et al., 2010). SPHARM description of shape boundary has been combined with medial representation (Styner and Gerig, 2001; Bouix et al., 2005) to obtain more localized shape features (Styner et al., 2004). In order to exploit the localized pat- tern of hippocampal atrophy, feature selection methodology has been employed to select patches on hippocampal surface thus improving the performance of shape features in diagnosing schizophrenia (Yushkevich et al., 2003a) and AD (Zhou et al., 2010). Features characterizing local hippocampal surface deformation with respect to the mean shape have also been used to classify AD (Li et al., 2007). SSMs have been applied in modeling the variability in the hippocampal shapes among the population Davies (2002); Davies et al. (2003). However, the principal components spanning the subspace for valid shape samples are not necessarily discriminative between the subpopulations of interest. As global shape descriptor, each component models the variation of the whole hippocampal shape which may not be sensitive to local differences. Constraints upon isotropic lesser principal components restricting to the region of interest has been presented to give more meaningful reconstruction (Vermaak and Perez, 2003). In localized components analysis (LoCA, Alcantara et al. (2007)), spatial locality in the shape variation is explicitly optimized, which has been applied to hippocampus shape analysis and shown to produce local shape components strongly correlated with cognitive measurement Xie et al. (2009). 2.4 Approach adopted in this thesis In this thesis, we will use the multiple atlas-based methods to segment the hippocampal volume, which has been demonstrated to have good performance in this
Chapter 2 Literature Review 41 specific task. We will develop methodologies in various aspects of this approach including the atlas construction and atlas selection. Based on the segmented hippocampal volumes, the groupwise optimization of MDL is used to establish the correspondence across the data set of hippocampal shapes, which is used to build the hippocampal SSMs. We propose an EM-ICP based method to extrapolate the SSM to unseen data and estimate the shape parameters. Then we use the built SSM to analyze hippocampal shape changes in AD. We propose to restrict the shape analysis to the hippocampal subregions where significant difference between the healty controls and AD patients, which is shown in improve the discrimina- tion ability of the PCA-based hippocampal SSM, and better correlated with the episodic memory decline in AD.
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UNIVERSITE DE BOURGOGNE U.F.R. SCIE
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Résumé L’objectif de cette thè
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144 LIST OF PUBLICATIONS using dive
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146 BIBLIOGRAPHY Alzheimer, A. (191
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148 BIBLIOGRAPHY Baillard, C., Hell
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150 BIBLIOGRAPHY of post mortem mag
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BIBLIOGRAPHY 181 Tzourio-Mazoyer, N
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BIBLIOGRAPHY 183 Vos, F. M., de Bru
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BIBLIOGRAPHY 185 Woolrich, M. W., J
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