Abstract
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The “discriminative direction” has been proven useful to re-
veal the subtle difference between two anatomical shape classes. When a
shape moves along this direction, its deformation will best manifest the
class difference detected by a kernel classifier. However, we observe that
such a direction cannot maintain a shape’s “anatomical” correctness, in-
troducing spurious difference. To overcome this drawback, we develop
a regularized discriminative direction by requiring a shape to conform
to its population distribution when it deforms along the discriminative
direction. Instead of iterative optimization, an analytic solution is pro-
vided to directly work out this direction. Experimental study shows its
superior performance in detecting and localizing the difference of hip-
pocampal shapes for sex. The result is supported by other independent
research in the same domain.