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

Chapter 1 Introduction 15
and the statistical analysis of hippocampal volume and shape in AD studies are
reviewed.
In Chapter 3, we will introduce the hippocampal segmentation method on MR
images using multiple atlases. A supervised method to build a population specific
atlas set is developed. The issue of atlas selection in multi-atlas based segmentation
is discussed. Two alternative criteria for atlas selection are proposed and evaluated.
In Chapter 4, we detailed the construction of the statistical shape models (SSMs)
for hippocampus and the establishment of correspondence by groupwise optimiza-
tion. We also developed the extrapolation of the SSM to the unseen point set and
the shape parameter estimation based on expectation-maximization algorithm.
In Chapter 5, we used the SSMs to perform the shape analysis on the hippocampus
and to detect the hippocampal shape changes in AD. We used statistical test to
select hippocampal landmarks exhibiting significant difference between the control
and the AD groups. We then developed shape analysis method to model the shape
variability on the subregions identified by the statistical tests, in order to improve
the discrimination ability of the shape analysis using SSM, and correlation of the
hippocampal shape description with decline of episodic memory in AD.
The thesis concludes in Chapter 6, which summarizes the work presented in the
preparation of this thesis, and outlines the possible future works.