The detection of local shape changes via the geometry of Hotelling's T2 fields
成果类型:
Article
署名作者:
Cao, J; Worsley, KJ
署名单位:
AT&T; Alcatel-Lucent; Lucent Technologies; McGill University
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
发表日期:
1999
页码:
925-942
关键词:
excursion sets
topological analysis
images
brain
摘要:
This paper is motivated by the problem of detecting local changes or differences in shape between two samples of objects via the nonlinear deformations required to map each object to an atlas standard. Local shape changes are then detected by high Values of the random field of Hotelling's T-2 statistics for detecting a change in mean of the Vector deformations at each point in the object. To control the null probability of detecting a local shape change, we use the recent result of Adler that the probability that a random field crosses a high threshold is very accurately approximated by the expected Euler characteristic (EC) of the excursion set of the random field above the threshold. We give an exact expression for the expected EC of a Hotelling's T-2 field, and we study the behavior of the field near local extrema. This extends previous results for Gaussian random fields by Adler and chi(2), t and F fields by Worsley and Cao. For illustration, these results are applied to the detection of differences in brain shape between a sample of 29 males and 23 females.