NeuroSlice: 2D Neuroimaging Data Container

Creates a NeuroSlice object representing a two-dimensional slice of neuroimaging data with associated spatial information. This class is particularly useful for working with individual slices from volumetric neuroimaging data or for visualizing 2D cross-sections.

Usage

NeuroSlice(data, space, indices = NULL)

Arguments

data: A vector or matrix containing the slice data values.
space: An object of class NeuroSpace defining the spatial properties (dimensions, spacing, origin) of the slice.
indices: Optional integer vector. When data is provided as a 1D vector, indices specifies the linear indices where the data values should be placed in the 2D slice. Useful for creating sparse slices. Default is NULL.

Value

A new object of class NeuroSlice.

Details

Two-Dimensional Neuroimaging Data Slice

Input Validation

The function performs several validation checks:

Verifies that space is 2-dimensional
Ensures data dimensions are compatible with space
Validates indices when provided for sparse initialization

Data Handling

The function supports two initialization modes:

Dense mode (indices = NULL):
- Data is reshaped if necessary to match space dimensions
- Dimensions must match exactly after reshaping
Sparse mode (indices provided):
- Creates a zero-initialized matrix matching space dimensions
- Places data values at specified indices

Examples

# Create a 64x64 slice space
slice_space <- NeuroSpace(c(64, 64), spacing = c(2, 2))

# Example 1: Dense slice from matrix
slice_data <- matrix(rnorm(64*64), 64, 64)
dense_slice <- NeuroSlice(slice_data, slice_space)

# Example 2: Dense slice from vector
vec_data <- rnorm(64*64)
vec_slice <- NeuroSlice(vec_data, slice_space)

# Example 3: Sparse slice with specific values
n_points <- 100
sparse_data <- rnorm(n_points)
sparse_indices <- sample(1:(64*64), n_points)
sparse_slice <- NeuroSlice(sparse_data, slice_space, indices = sparse_indices)