文章基本信息

标题：A Bayesian Approach to Statistical Shape Analysis via the Projected Normal Distribution
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作者：Luis Gutiérrez ; Eduardo Gutiérrez-Peña ; Ramsés H. Mena 等
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2019
卷号：14
期号：2
页码：427-447
DOI：10.1214/18-BA1113
语种：English
出版社：International Society for Bayesian Analysis
摘要：This work presents a Bayesian predictive approach to statistical shape analysis. A modeling strategy that starts with a Gaussian distribution on the con- figuration space, and then removes the effects of location, rotation and scale, is studied. This boils down to an application of the projected normal distribution to model the configurations in the shape space, which together with certain identifiability constraints, facilitates parameter interpretation. Having better control over the parameters allows us to generalize the model to a regression setting where the effect of predictors on shapes can be considered. The methodology is illustrated and tested using both simulated scenarios and a real data set concerning eight anatomical landmarks on a sagittal plane of the corpus callosum in patients with autism and in a group of controls.
关键词：Bookstein coordinates; identifiability; medical image; shape regression.