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

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

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Chapter 4 Statistical shape mo<strong>de</strong>l of Hippocampus 73<br />

U × V<br />

γi ✲<br />

γj<br />

U × V<br />

✲<br />

.<br />

.<br />

.<br />

U × V<br />

fi ✲ Xi<br />

✻<br />

fj<br />

❄<br />

✲ Xj<br />

correspon<strong>de</strong>nce<br />

Figure 4.1: Parameterizations {fi} <strong>and</strong> reparameterizations {γi} of the shape<br />

surfaces {Xi} <strong>and</strong> correspon<strong>de</strong>nces.<br />

achieved by reparameterization of {fi}<br />

on the parameter space, such that<br />

γi : U × V ↦→ U × V, i = 1, · · · , n (4.2)<br />

γi(uhi , vhi ) = γj(uhj , vhj ) = (uh, vh), (4.3)<br />

<strong>and</strong> the result collection of parameterizations {fi◦γi} establish the correspon<strong>de</strong>nce<br />

across the training data {Xi}.<br />

Since the hippocampal segmentation are simply connected regions on MR images,<br />

the closed surfaces extracted from the segmentations are homeomorphic to the S 2<br />

sphere. The reparameterizations are thus homeomorphisms on S 2<br />

in which a rotation component Γ can be separated<br />

γi : S 2 ↦→ S 2 , i = 1, · · · , n, (4.4)<br />

γi = Γi ◦ ˜γi<br />

(4.5)<br />

We introduce the calculation of the parameterization f in §4.1.1. To establish

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