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x TABLE DES MATIÈRES 3 Hippocampal segmentation using multiple atlases 43 3.1 Basic version of multi-atlas based segmentation propagation . . . . 44 3.1.1 Atlas registration . . . . . . . . . . . . . . . . . . . . . . . . 45 3.1.1.1 Affine registration . . . . . . . . . . . . . . . . . . 46 3.1.1.2 Non-rigid registration . . . . . . . . . . . . . . . . 47 3.1.2 Similarity based atlas selection . . . . . . . . . . . . . . . . 47 3.1.2.1 Image mutual information . . . . . . . . . . . . . . 48 3.1.2.2 Correlation coefficient . . . . . . . . . . . . . . . . 49 3.1.3 Label fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.2 Supervised construction of population-specific atlas . . . . . . . . . 51 3.2.1 Construction of atlas set . . . . . . . . . . . . . . . . . . . . 51 3.2.2 Evaluation of atlas set . . . . . . . . . . . . . . . . . . . . . 53 3.2.2.1 Entropy of probability image . . . . . . . . . . . . 54 3.2.2.2 Partial moment of histogram . . . . . . . . . . . . 55 3.3 Atlas selection by re-ranking . . . . . . . . . . . . . . . . . . . . . . 55 3.3.1 MMR re-ranking . . . . . . . . . . . . . . . . . . . . . . . . 56 3.3.1.1 Atlas similarity and image similarity . . . . . . . . 56 3.3.1.2 Atlas selection by MMR algorithm . . . . . . . . . 57 3.3.2 Least angle regression . . . . . . . . . . . . . . . . . . . . . 58 3.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . 60 3.4.1 Supervised atlas construction . . . . . . . . . . . . . . . . . 61 3.4.1.1 Materials . . . . . . . . . . . . . . . . . . . . . . . 61 3.4.1.2 Results . . . . . . . . . . . . . . . . . . . . . . . . 63 3.4.1.3 Discussion . . . . . . . . . . . . . . . . . . . . . . 63 3.4.2 Atlas selection strategies . . . . . . . . . . . . . . . . . . . . 65 3.4.2.1 Materials . . . . . . . . . . . . . . . . . . . . . . . 65 3.4.2.2 Experimental results . . . . . . . . . . . . . . . . . 66 3.4.2.3 Discussion . . . . . . . . . . . . . . . . . . . . . . 67 3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4 Statistical shape model of Hippocampus 71 4.1 Building the shape model . . . . . . . . . . . . . . . . . . . . . . . 72 4.1.1 Parameterization of the shape surfaces . . . . . . . . . . . . 74 4.1.1.1 Initial parameterization by diffusion . . . . . . . . 75 4.1.1.2 Distortion minimization . . . . . . . . . . . . . . . 76 4.1.2 Reparameterization by rotation . . . . . . . . . . . . . . . . 78 4.1.3 Groupwise optimization on shape images . . . . . . . . . . . 80 4.1.3.1 Image representation and manipulation of shapes . 81 4.1.3.2 MDL cost function and its gradient . . . . . . . . 83 4.1.3.3 Fluid regularization . . . . . . . . . . . . . . . . . 85 4.1.3.4 Optimization process . . . . . . . . . . . . . . . . 87 4.1.4 Validation and evaluation of shape models . . . . . . . . . . 87 4.1.4.1 Compactness . . . . . . . . . . . . . . . . . . . . . 90 4.1.4.2 Generalization ability . . . . . . . . . . . . . . . . 90
TABLE DES MATIÈRES xi 4.1.4.3 Specificity . . . . . . . . . . . . . . . . . . . . . . 90 4.2 Extrapolation of testing cases . . . . . . . . . . . . . . . . . . . . . 91 4.2.1 Gaussian mixture model and EM algorithm . . . . . . . . . 92 4.2.2 Estimation with symmetrical consistency and shape priors . 94 4.3 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . 97 4.3.1 SSM Building . . . . . . . . . . . . . . . . . . . . . . . . . . 97 4.3.2 SSM parameter estimation . . . . . . . . . . . . . . . . . . . 102 4.3.3 Results and discussion . . . . . . . . . . . . . . . . . . . . . 103 4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5 Quantitative shape analysis of hippocampus in AD 109 5.1 Overview of the method . . . . . . . . . . . . . . . . . . . . . . . . 110 5.2 Shape analysis using SSM . . . . . . . . . . . . . . . . . . . . . . . 113 5.2.1 Localization step . . . . . . . . . . . . . . . . . . . . . . . . 114 5.2.2 Shape modeling step . . . . . . . . . . . . . . . . . . . . . . 115 5.3 Disease classification based on localized shape analysis . . . . . . . 116 5.4 Correlating the shape variation with memory performance . . . . . 119 5.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 119 5.5.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 5.5.2 SSM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 5.5.3 Disease classification of AD using regional SSM . . . . . . . 121 5.5.4 Correlation of hippocampal SSM descriptors with memory scores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 5.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 5.6.1 Shape model and correspondences . . . . . . . . . . . . . . 125 5.6.2 Identification of atrophy affected subregions . . . . . . . . . 126 5.6.3 Disease classification using SSM . . . . . . . . . . . . . . . . 128 5.6.4 Correlation analysis . . . . . . . . . . . . . . . . . . . . . . 132 5.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 6 Conclusions 137 6.1 Contributions of this thesis . . . . . . . . . . . . . . . . . . . . . . 137 6.1.1 Multi-atlas based segmentation . . . . . . . . . . . . . . . . 138 6.1.2 Statistical shape models . . . . . . . . . . . . . . . . . . . . 138 6.1.3 Shape analysis of hippocampus in Alzheimer’s disease . . . . 139 6.2 Future works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6.2.1 Non-local approach to the atlas based image segmentation . 140 6.2.2 Groupwise shape correspondence by optimization . . . . . . 140 6.2.3 Shape analysis of biological objects . . . . . . . . . . . . . . 141 List of publications 143 Bibliography 145
Page 1: UNIVERSITE DE BOURGOGNE U.F.R. SCIE
Page 5 and 6: Résumé L’objectif de cette thè
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Page 9: TABLE DES MATIÈRES Acknowledgement
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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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152 BIBLIOGRAPHY B. (2008). Three-d
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154 BIBLIOGRAPHY Cootes, T. F., Tay
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156 BIBLIOGRAPHY head in MR images
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158 BIBLIOGRAPHY Evans, A. C., Coll
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BIBLIOGRAPHY 161 Ghanei, A., Soltan
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BIBLIOGRAPHY 163 Heckemann, R. A.,
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BIBLIOGRAPHY 165 R. C. (2003). MRI
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BIBLIOGRAPHY 167 Konrad, C., Ukas,
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BIBLIOGRAPHY 169 Mahony, R. and Man
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BIBLIOGRAPHY 171 disease, mild cogn
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BIBLIOGRAPHY 173 Petersen, R. C., S
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BIBLIOGRAPHY 175 Rorden, C. and Bre
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BIBLIOGRAPHY 177 Shen, K., Bourgeat
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BIBLIOGRAPHY 179 Barillot, C., Hayn
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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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