Extract Geometric Properties of an Image

This function retrieves the geometric properties of a given image, such as dimensions and voxel size.

Retrieves the NeuroSpace object associated with an IndexLookupVol object.

Usage

space(x, ...)

# S4 method for class 'IndexLookupVol'
space(x)

# S4 method for class 'ROICoords'
space(x)

# S4 method for class 'NeuroObj'
space(x)

# S4 method for class 'NeuroSpace'
space(x)

Arguments

x

An IndexLookupVol object

...

Additional arguments, if needed.

Value

A NeuroSpace object representing the geometric space of x.

Examples

# Create a NeuroSpace object with dimensions (10, 10, 10) and voxel size (1, 1, 1)
x <- NeuroSpace(c(10, 10, 10), c(1, 1, 1))

# Create a NeuroVol object with random data and the specified NeuroSpace
vol <- NeuroVol(rnorm(10 * 10 * 10), x)

# Retrieve the geometric properties of the NeuroVol object
identical(x, space(vol))
#> [1] TRUE

space <- NeuroSpace(c(64, 64, 64), c(1, 1, 1), c(0, 0, 0))
ilv <- IndexLookupVol(space, c(1:100))
space(ilv)  # Get the associated NeuroSpace object
#> 
#>  NeuroSpace Object 
#> 
#>  >> Dimensions 
#>   Grid Size: 64 x 64 x 64
#>   Memory:   5.9 KB
#> 
#>  >> Spatial Properties 
#>   Spacing:   1.00 x 1.00 x 1.00 mm
#>   Origin:    0.00 x 0.00 x 0.00 mm
#> 
#>  >> Anatomical Orientation 
#>   X: Left-to-Right  |  Y: Posterior-to-Anterior  |  Z: Inferior-to-Superior 
#> 
#>  >> World Transformation 
#>   Forward (Voxel to World): 
#>     1.000  0.000  0.000  0.000
#> 0.000  1.000  0.000  0.000
#> 0.000  0.000  1.000  0.000
#> 0.000  0.000  0.000  1.000 
#>   Inverse (World to Voxel): 
#>     1.000  0.000  0.000  0.000
#> 0.000  1.000  0.000  0.000
#> 0.000  0.000  1.000  0.000
#> 0.000  0.000  0.000  1.000 
#> 
#>  >> Bounding Box 
#>   Min Corner: 0.0, 0.0, 0.0 mm
#>   Max Corner: 63.0, 63.0, 63.0 mm
#> 
#> ==================================================