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.
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 )
| 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 |
List of objects