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Erschienen in:
2007 | OriginalPaper | Buchkapitel
A Study of Hippocampal Shape Difference Between Genders by Efficient Hypothesis Test and Discriminative Deformation
verfasst von : Luping Zhou, Richard Hartley, Paulette Lieby, Nick Barnes, Kaarin Anstey, Nicolas Cherbuin, Perminder Sachdev
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007
Verlag: Springer Berlin Heidelberg
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Hypothesis testing is an important way to detect the statistical difference between two populations. In this paper, we use the Fisher permutation and bootstrap tests to differentiate hippocampal shape between genders. These methods are preferred to traditional hypothesis tests which impose assumptions on the distribution of the samples. An efficient algorithm is adopted to rapidly perform the
exact
tests. We extend this algorithm to multivariate data by projecting the original data onto an “informative direction” to generate a scalar test statistic. This “informative direction” is found to preserve the original discriminative information. This direction is further used in this paper to isolate the discriminative shape difference between classes from the individual variability, achieving a visualization of shape discrepancy.