mimosa_data: MIMoSA Training Data Frame

In neuroconductor-devel/mimosa: 'MIMoSA': A Method for Inter-Modal Segmentation Analysis

Description

This function creates the training vectors from a single MRI study that has FLAIR, T1, T2, and PD volumes as well as binary masks of lesions. The function can create a tissue mask for the data (or the user can supply a brain mask), the candidate voxels for lesion segmentation, smoothed volumes, and coupling maps. The user may supply already normalized data if they wish to use an alternative normalization method.

Usage

mimosa_data(brain_mask, FLAIR, T1, T2 = NULL, PD = NULL,
  tissue = FALSE, gold_standard = NULL, normalize = "no",
  cand_mask = NULL, slices = NULL, orientation = c("axial",
  "coronal", "sagittal"), cores = 1, verbose = TRUE)

Arguments

brain_mask	brain or tissue mask of class nifti
FLAIR	volume of class nifti
T1	volume of class nifti
T2	volume of class nifti. If not available use NULL.
PD	volume of class nifti. If not available use NULL.
tissue	is a logical value that determines whether the brain mask is a full brain mask or tissue mask (excludes CSF), should be FALSE unless you provide the tissue mask as the brain_mask object
gold_standard	gold standard lesion segmentation mask of class nifti
normalize	is 'no' by default and will not perform any normalization on data. To normalize data specify 'Z' for z-score normalization or 'WS' for WhiteStripe normalization
cand_mask	is NULL to use candidate mask procedure proposed with method or a nifti object to be used as the candidate mask
slices	vector of desired slices to train on, if NULL then train over the entire brain mask
orientation	string value telling which orientation the training slices are specified in, can take the values of "axial", "sagittal", or "coronal"
cores	1 numeric indicating the number of cores to be used (no more than 4 is useful for this software implementation)
verbose	logical indicating printing diagnostic output

Value

List of objects

neuroconductor-devel/mimosa documentation built on Sept. 21, 2019, 6:24 p.m.