Title

Hippocampal shape analysis for Alzheimer's disease using an efficient hypothesis test and regularized discriminative deformation

RIS ID

86594

Publication Details

Zhou, L., Lieby, P., Barnes, N., Reglade-Meslin, C., Walker, J., Cherbuin, N. & Hartley, R. (2009). Hippocampal shape analysis for Alzheimer's disease using an efficient hypothesis test and regularized discriminative deformation. The Hippocampus, 19 (6), 533-540.

Abstract

In this paper, we present a framework to perform statistical shape analysis for manually segmented hippocampi, which includes an efficient permutation test for detecting subtle class differences, and a regularized ``discriminative direction" method for visualizing the shape discrepancy. Fisher permutation and bootstrap tests are preferred to traditional hypothesis tests which impose assumptions on the distribution of the samples. In this paper, an efficient algorithm is adopted to rapidly perform the {\em exact} tests. We extend this algorithm to multivariate data by projecting the shape descriptors onto an ``informative direction'' that preserves the original discriminative information as much as possible to generate a scalar test statistic. This ``informative direction'' is further used to seek a ``discriminative direction'' to isolate the discriminative shape difference between classes from the individual variability. Compared with the existing method, the ``discriminative direction" used in this paper is regularized by requiring the newly generated shapes to respect the underlying shape manifold as well as reflecting the essential shape differences in two populations. Hence a more accurate localization of difference is produced. We apply our methods to analyzing the hippocampal shapes between controls and Alzheimer's Disease (AD) based on the publicly available OASIS MRI database, and report the findings.

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Link to publisher version (DOI)

http://dx.doi.org/10.1002/hipo.20639