neuroim2 (version 0.8.5)

IndexLookupVol-class: IndexLookupVol Class

Description

A three-dimensional brain image class that serves as a map between 1D grid indices and a table of values. This class is primarily used in conjunction with the SparseNeuroVec class to efficiently represent and access sparse neuroimaging data.

The IndexLookupVol class provides efficient indexing and coordinate lookup functionality for 3D neuroimaging data. It maintains a mapping between linear indices and 3D coordinates, optimizing memory usage and access speed for sparse volumes.

Creates an IndexLookupVol object, which provides efficient bidirectional mapping between linear indices and 3D coordinates in a neuroimaging volume. This is particularly useful for working with masked or sparse brain volumes.

Usage

IndexLookupVol(space, indices)

Value

An object of class IndexLookupVol containing:

• A mapping between linear indices and sparse positions

• The original space information

• The subset of included voxel indices

Arguments

space

A NeuroSpace object defining the 3D space dimensions, spacing, and orientation.

indices

An integer vector containing the linear indices of the voxels to include in the lookup volume. These should be 1-based indices within the range of the space.

Slots

space

A NeuroSpace object representing the 3D space of the brain image.

indices

An integer vector containing the 1D indices of the non-zero voxels in the grid.

map

An integer vector containing the mapping between the 1D indices and the table of values.

Methods

This class inherits methods from NeuroVol. Additional methods specific to index lookup and mapping operations may be available.

Implementation Details

The class uses an integer mapping array for O(1) lookups between linear indices and their corresponding positions in the sparse representation.

Details

The IndexLookupVol class extends NeuroVol and provides a mechanism for efficient lookup and mapping of sparse 3D neuroimaging data. It stores only the indices of non-zero voxels and their corresponding mappings, allowing for memory-efficient representation of large, sparse brain images.

Create an IndexLookupVol Object

See Also

SparseNeuroVec-class for the primary class that utilizes IndexLookupVol. NeuroVol-class for the base volumetric image class.

IndexLookupVol for creating instances of this class

coords for coordinate lookup, lookup for index mapping, NeuroSpace for space representation

Examples

# Create a NeuroSpace object
space <- NeuroSpace(dim = c(2L, 2L, 2L), origin = c(0, 0, 0), spacing = c(1, 1, 1))

# Create a 3D mask
mask <- array(c(TRUE, FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE), dim = c(2, 2, 2))

# Create indices and map for the IndexLookupVol
indices <- which(mask)
map <- seq_along(indices)

# Create an IndexLookupVol object
ilv <- IndexLookupVol(space = space, indices = as.integer(indices))

# Access the indices
print(ilv@indices)

# Access the map
print(ilv@map)


# Create a 64x64x64 space
space <- NeuroSpace(c(64, 64, 64), c(1, 1, 1), c(0, 0, 0))

# Create a lookup volume with random indices
indices <- sample(1:262144, 10000)  # Select 10000 random voxels
ilv <- IndexLookupVol(space, indices)

# Look up coordinates for specific indices
coords <- coords(ilv, indices[1:10])