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A study of hippocampal shape difference between genders by efficient hypothesis test and discriminative deformation

Journal Article


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Abstract


  • 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.

Authors


  •   Zhou, Luping
  •   Hartley, Richard (external author)
  •   Lieby, Paulette (external author)
  •   Barnes, Nick (external author)
  •   Anstey, Kaarin J. (external author)
  •   Cherbuin, Nicolas (external author)
  •   Sachdev, Perminder (external author)

Publication Date


  • 2007

Citation


  • Zhou, L., Hartley, R., Lieby, P., Barnes, N., Anstey, K., Cherbuin, N. & Sachdev, P. (2007). A study of hippocampal shape difference between genders by efficient hypothesis test and discriminative deformation. Lecture Notes in Computer Science, 4791 375-383.

Scopus Eid


  • 2-s2.0-38149043418

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2866&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1857

Number Of Pages


  • 8

Start Page


  • 375

End Page


  • 383

Volume


  • 4791

Abstract


  • 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.

Authors


  •   Zhou, Luping
  •   Hartley, Richard (external author)
  •   Lieby, Paulette (external author)
  •   Barnes, Nick (external author)
  •   Anstey, Kaarin J. (external author)
  •   Cherbuin, Nicolas (external author)
  •   Sachdev, Perminder (external author)

Publication Date


  • 2007

Citation


  • Zhou, L., Hartley, R., Lieby, P., Barnes, N., Anstey, K., Cherbuin, N. & Sachdev, P. (2007). A study of hippocampal shape difference between genders by efficient hypothesis test and discriminative deformation. Lecture Notes in Computer Science, 4791 375-383.

Scopus Eid


  • 2-s2.0-38149043418

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2866&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1857

Number Of Pages


  • 8

Start Page


  • 375

End Page


  • 383

Volume


  • 4791