We propose a novel Bayesian nonparametric scalar-on-image regression model that utilises the spatial coordinates of the voxels to group voxels with similar effects on the response to have a common coefcient. We employ the Potts-Gibbs random partition model as the prior for the random partition ...
Code for Bayesian scalar-on-image regression with a relaxed-thresholded Gaussian process prior. - annamenacher/RTGP
Permutation Test for Image-on-Scalar Regression With an Application to Breast Cancerhypothesis testingimage analysisinferencepermutationImage based screening is now routinely available for early detection of cancer and other diseases. Quantitative analysis for effects of risk factors on digital images is ...
Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regressiondoi:10.1101/853341Marco PalmaShahin TavakoliJulia BrettschneiderThomas E. NicholsCold Spring Harbor Laboratory
The aim of this article is to develop a Bayesian scalar-on-image regression model to integrate high-dimensional imaging data and clinical data to predict cognitive, behavioral, or emotional outcomes, while allowing for nonignorable missing outcomes. Such a nonignorable nonresponse consideration is ...
We address the impact of model assumptions in the case of scalar-on-image regression. This paper gives a systematic overview of the main approaches and their assumptions. We propose to categorize the latter into underlying and parametric assumptions and develop measures to quantify the degree to ...
Smooth scalar-on-image regression via spatial Bayesian variable selection - Goldsmith, Huang, et al. - 2012 () Citation Context ...he physical characteristics of the experiment. Hence Bayesian methods in neuroimaging have received a fair amount of recent attention (see e.g Bowman et al., 2008...
M. (2014). Smooth scalar-on-image regression via spatial Bayesian variable selection. J. Comput. Graph. Statist. 23 46-64. MR3173760GOLDSMITH, J., HUANG, L. and CRAINICEANU, C. M. (2014). Smooth scalar-on-image regression via spatial Bayesian variable selection. J. Comput. Graph. ...
Regressing Scalar Outcomes on Image Predictors via Functional Principal Component RegressionBerkeley Electronic Press Selected WorksPhilip T. ReissHarvard School of Public Health Department of Biostatistics
Generalized scalar-on-image regressionPredictionTotal variation(2017). Generalized Scalar-on-Image Regression Models via Total Variation. Journal of the American Statistical Association. Ahead of Print. doi: 10.1080/01621459.2016.1194846doi:10.1080/01621459.2016.1194846...