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

Chapter 5 Quantitative shape analysis of hippocampus in AD 125
Accuracy
Accuracy
0.84 0.85 0.86 0.87
●
● ●
●
● ●
● ●
●
●
●
● ● ●
●
● ●
● ●
●
●
● ● ●
●
● ●
● ●●
●● ● ●
● ● ●
● ● ●
●●
●
●
●
●● ●
●
●
●
●
●
● ●● ● ● ●
●
●
● ●
●
● ●
● ●●
● ●
1e−04 1e−03 1e−02 1e−01 1e+00
Threshold α
(a) Testing set accuracy, LR, MR
0.70 0.75 0.80 0.85
● ●●●
●●
● ●●
●
● ●
● ●
● ●
●●●
●
●
●
●●
●
●●
●●●
●●
●
● ●● ●
●
●
●
● ●
● ● ● ● ●
●
● ● ●
●
●
●●
●
● ●●
●
●
1e−04 1e−03 1e−02 1e−01 1e+00
Threshold α
(c) Testing set accuracy, LS, MR
Accuracy
Accuracy
0.70 0.74 0.78 0.82
●
● ● ●
●
●
● ●
●●
●
●
● ●●
●
●
●
●
●●
● ● ● ● ●
● ● ●
● ●
● ● ●
●
●
● ●
●
●●
●●
●●
●
● ●
● ●
● ●●
● ●
●
●
●
●●
●
● ●
●●
1e−04 1e−03 1e−02 1e−01 1e+00
Threshold α
(b) Testing set accuracy, LR, MS
0.70 0.75 0.80 0.85
●
●
●
●
● ●
● ●
●
●
●
●
●● ●
●
●
●
●
●
●●●●
●
●
● ●
●●●
●
● ● ●
●●
● ●●
●●
● ●
● ●
●
●●
●
●
●●
● ●●
● ●
●
● ●●
●
●
1e−04 1e−03 1e−02 1e−01 1e+00
Threshold α
(d) Testing set accuracy, LS, MS
Figure 5.6: The accuracy of the disease classification using bagged support
vector machines (SVMs) with varying thresholds in the landmark selection on
a separated testing set. Black circles: shape features from the Statistical Shape
Model (SSM) only; red circles: shape features with additional volume features.
both right and left hippocampus (visualization in Figure 5.12). The shape com-
ponents extracted from subregions with significant shape differences indicate a
better representation of the effect of the disease on the shape of the hippocampus.
The mean difference between the NC and AD groups in the training set is shown
in Figs. 5.14 and 5.15.
5.6 Discussion
5.6.1 Shape model and correspondences
In our current setting, the correspondence over the training set is MDL optimized,
and propagated to the testing set via closest point. This is an economical solution
while suboptimal to the optimization of MDL over the testing set. In practice,
however, we found that the classification accuracy was not lowered when using the