comp_images_corr: Compute voxel-wise correlations between two groups of images

In kangjian2016/SpatCorrImage: Spatial Adaptive Varying Corraltion Analysis for for Multimodal Neuroimaging Data

Description

This function is to compute voxel-wise spatially varying correlation between two groups of 3D images

Usage

comp_images_corr(img_1, img_2, mask = NULL)

Arguments

img_1	a matrix of multiple images
img_2	a matrix of multiple images
mask	a vector of mask taking logical values. The default is NULL.
coords	a matrix of spatial coords of the images. The default is NULL.

Value

a vector of the correlation values

Author(s)

Jian Kang <[e-mail]>

Examples

set.seed(1000)
dim_img = c(10,10,10)
n = 50
grids <- lapply(1:3,function(i) seq(-round(dim_img[i]/2)+1,round(dim_img[i]/2),length=dim_img[i]))
coords <- expand.grid(grids)
num_voxels <- prod(dim_img)
img_1 <- array(rnorm(num_voxels*n),dim=c(num_voxels,n))
img_2 <- array(rnorm(num_voxels*n),dim=c(num_voxels,n))
cor_region <- create_sphere_mask(grids,radius=2)
cor_region_list <- array(c(cor_region),dim=dim(img_2))
img_2 <- ifelse(cor_region_list,img_1+rnorm(num_voxels*n,sd=0.5),img_2)
mask <- create_sphere_mask(grids,radius=4)
cor_map <- comp_images_corr(img_1,img_2,c(mask))
plot_3D_image_slices(array(cor_map,dim=dim_img),grids,c(-2,2))

kangjian2016/SpatCorrImage documentation built on Oct. 22, 2021, 1:21 a.m.