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

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22 Chapter 2 Literature Review • the inferior medial border; • and the use of arbitrary lines. One of the most widely adopted protocol (15% of the studies reviewed by Geuze et al., 2004) was developed by Watson et al. (1992), with high inter-rater reliability reported (di Sclafani et al., 1998; Du et al., 2001). It defines the hippocampus com- prising the hippocampus proper, subicular complex, dentate gyrus, and including the white matter structures of alveus and fimbria. According to this protocol, the hippocampus is traced on the coronal plane. The head of hippocampus is sepa- rated from amygdala by the inferior horn of the lateral ventricle (mainly CSF), which extends to the deep part of the uncus forming the uncal recess. If the inferior horn is not visible in the image, the following three alternatives may be used to outline the hippocampus-amygdala boundary: the alveus, an arbitrary line from the inferior horn of lateral ventricle to the sulcus at the inferior margin of the semilunar gyrus, or from straight horizontal line connecting the plane of the inferior horn of the lateral ventricle with the surface of the uncus. The posterior border is defined by the section with the crus of fornix separating the hippocampus from the fimbria. The inferior border is drawn to include the subicular complex and uncal cleft, separating from the parahippocampal gyrus by the angle between the most medial extent of subiculum and parahippocampal gyrus. This protocol is estimated to include 90-95% of the total volume of hippocampal formation. The protocol set forth by Watson et al. (1992) has been used to validate the automatic segmentations provided by Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 . The automatic segmentation uses the high-dimensional brain mapping tool SNT (Surgical Navigation Technologies), which is commercially available from Medtronic Surgical Navigation Technologies (Louisville, Colorado, USA). The val- idation was been performed on the normal aging, MCI and AD subjects (Hsu et al., 2002). The hippocampal volumes from ADNI used in the preparation of this thesis are segmented using the SNT tool, with corrections by qualified reviewers. Com- pared to the manual segmentation protocol, the automated SNT segmentation 2 Available at www.loni.ucla.edu/ADNI. For a description of the data provided by ADNI, see §3.4.2.1.
Chapter 2 Literature Review 23 does not include alveus and fimbria, and the volume is 10% less than the volume measured on the manual segmentation. 2.1.2 Survey of segmentation algorithms Earlier developments in image segmentation are usually solely based on image features, such as thresholding of image intensity, textual analysis, region growing etc. Artificial neural network (ANN) has been used by Pérez de Alejo et al. (2003) for hippocampal segmentation, in which an tissue classification is obtained by an ANN-based vector quantization, and subsequently a supervised multi-layer perceptron on a selected ROI is used to segment the anatomical structure of hippocampus. Methodologies incorporating anatomical templates and atlases model- ing the shape and appearance of anatomical structures are later developed to deal with objects such as hippocampus. Apart from the segmentation per se, a meta- segmentation method using AdaBoost classifiers (Freund and Schapire, 1995) has been developed by (Wang et al., 2011) to detect and correct systematic error in the segmentation based on the spatial, contextual and intensity patterns of the error. 2.1.2.1 Region growing and deformable models Region growing and deformable model methods usually start from a initial set of seed points, which deforms or grows to match the structure to be segmented. In Ashton et al. (1997), the region starts from a line of seeds along the long axis of the hippocampus, and deforms elastically constrained by the surface tension, deviation from expected surface normal and the force from surrounding tissues. Driven by gray level gradient and internal forces from surface curvature, an initial stack of polygons localizing the hippocampus on parallel slices was used by Ghanei et al. (1998, 2001) and Ghanei and Soltanian-Zadeh (2002). The Segmentation Automatisée Compétitive de l’Hippocampe et de l’Amygdale (SACHA) algorithm developed by Chupin et al. (2007, 2009) segments simultaneously hippocampus and
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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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