make_subcort: Make the subcortical components of a '"xifti"'

In ciftiTools: Tools for Reading, Writing, Viewing and Manipulating CIFTI Files

Make the subcortical components of a "xifti"

Description

Coerce subcortical data into valid entries for xifti$data$subcort and xifti$meta$subcort. The data arguments can be matrices/arrays or NIFTI file paths. If the mask is not provided, it will be inferred from the labels.

Usage

make_subcort(vol, labs, mask = NULL, idx = NULL, validate_mask = FALSE)

Arguments

vol	represents the data values of the subcortex. It is either a NIFTI file path, 3D/4D data array (i \times j \times k \times T), or a vectorized data matrix (V_S voxels by T measurements). If it's vectorized, the voxels should be in spatial order.
labs	represents the brainstructure labels of each voxel: see substructure_table. It is either a NIFTI file path, a 3D data array (i \times j \times k) of numeric brainstructure indices, or a V_S length vector in spatial order with brainstructure names as factors or integer indices. The indices should be 3-22 (2 and 3 correspond to left and right cortex, respectively) or 1-19 (cortex labels omitted), with 0 representing out-of-mask voxels.
mask	is a NIFTI file path or logical 3D data array (i \times j \times k) where TRUE values indicate subcortical voxels (in-mask). If it is not provided, the mask will be inferred from voxels with labels 0 or NA in subcortLabs. If subcortLabs are vectorized and subcortMask is not provided, the mask cannot be inferred so an error will occur.
idx	Only applies if vol is a NIFTI file path. This is a numeric vector indicating the data indices to read. If NULL (default), read all the data. Must be a subset of the indices present in the file, or an error will occur.
validate_mask	If mask is provided, set this to TRUE to check that the mask only removes voxels with NA and 0 values in vol and labs. Default: FALSE (saves time).

Details

To read in the labels as the primary data, use the labels NIFTI for both vol and labs.

Value

A list with components "data", "labels", "mask", and "trans_mat". The first two will be vectorized and ordered spatially.

The volume can be recovered using: vol <- unvec_vol(data, mask, fill=NA) labs <- unvec_vol(labels, mask, fill=0)

Label Levels

xifti$meta$subcort$labels is a factor with the following levels:

1. Cortex-L

2. Cortex-R

3. Accumbens-L

4. Accumbens-R

5. Amygdala-L

6. Amygdala-R

7. Brain Stem

8. Caudate-L

9. Caudate-R

10. Cerebellum-L

11. Cerebellum-R

12. Diencephalon-L

13. Diencephalon-R

14. Hippocampus-L

15. Hippocampus-R

16. Pallidum-L

17. Pallidum-R

18. Putamen-L

19. Putamen-R

20. Thalamus-L

21. Thalamus-R

These correspond to the same structures as given by ft_read_cifti in the cifti-matlab MATLAB toolbox. Note that the first two levels (left and right cortex) are not used.

ciftiTools documentation built on Oct. 4, 2024, 1:12 a.m.