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neurospin.utils.mask

Module: neurospin.utils.mask

Functions

nipy.neurospin.utils.mask.computeMaskIntra(inputFilename, outputFilename, copyFilename=None, m=0.20000000000000001, M=0.90000000000000002, cc=1)
Depreciated, see compute_mask_intra.
nipy.neurospin.utils.mask.computeMaskIntraArray(volumeMean, firstVolume, m=0.20000000000000001, M=0.90000000000000002, cc=1)
Depreciated, see compute_mask_intra.
nipy.neurospin.utils.mask.compute_mask(mean_volume, reference_volume=None, m=0.20000000000000001, M=0.90000000000000002, cc=1)

Compute a mask file from fMRI data in 3D or 4D ndarrays.

Compute and write the mask of an image based on the grey level This is based on an heuristic proposed by T.Nichols: find the least dense point of the histogram, between fractions m and M of the total image histogram.

In case of failure, it is usually advisable to increase m.

Parameters:

mean_volume : 3D ndarray

mean EPI image, used to compute the threshold for the mask.

reference_volume: 3D ndarray, optional :

reference volume used to compute the mask. If none is give, the mean volume is used.

m : float, optional

lower fraction of the histogram to be discarded.

M: float, optional :

upper fraction of the histogram to be discarded.

cc: boolean, optional :

if cc is True, only the largest connect component is kept.

Returns:

mask : 3D boolean ndarray

The brain mask

nipy.neurospin.utils.mask.compute_mask_files(input_filename, output_filename=None, return_mean=False, copy_filename=None, m=0.20000000000000001, M=0.90000000000000002, cc=1)

Compute a mask file from fMRI nifti file(s)

Compute and write the mask of an image based on the grey level This is based on an heuristic proposed by T.Nichols: find the least dense point of the histogram, between fractions m and M of the total image histogram.

In case of failure, it is usually advisable to increase m.

Parameters:

input_filename : string

nifti filename (4D) or list of filenames (3D).

output_filename : string or None, optional

path to save the output nifti image (if not None).

return_mean : boolean, optional

if True, and output_filename is None, return the mean image also, as a 3D array (2nd return argument).

copy_filename : string, optional

optionally, a copy of the original data saved as a single-file 4D nifti volume.

m : float, optional

lower fraction of the histogram to be discarded.

M: float, optional :

upper fraction of the histogram to be discarded.

cc: boolean, optional :

if cc is True, only the largest connect component is kept.

Returns:

mask : nifti.NiftiImage object

The brain mask

mean_image : 3d ndarray, optional

The main of all the images used to estimate the mask. Only provided if return_mean is True.

nipy.neurospin.utils.mask.compute_mask_intra(input_filename, output_filename=None, return_mean=False, copy_filename=None, m=0.20000000000000001, M=0.90000000000000002, cc=1)
See compute_mask_files.
nipy.neurospin.utils.mask.compute_mask_intra_array(volume_mean, reference_volume=None, m=0.20000000000000001, M=0.90000000000000002, cc=True)
Depreciated, see compute_mask.
nipy.neurospin.utils.mask.compute_mask_sessions(session_files, m=0.20000000000000001, M=0.90000000000000002, cc=1, threshold=0.5)

Compute a common mask for several sessions of fMRI data.

Uses the mask-finding algorithmes to extract masks for each session, and then keep only the main connected component of the a given fraction of the intersection of all the masks.
Parameters:

session_files : list of list of strings

A list of list of nifti filenames. Each inner list represents a session.

threshold : float, optional

the inter-session threshold: the fraction of the total number of session in for which a voxel must be in the mask to be kept in the common mask. threshold=1 corresponds to keeping the intersection of all masks, whereas threshold=0 is the union of all masks.

m : float, optional

lower fraction of the histogram to be discarded.

M: float, optional :

upper fraction of the histogram to be discarded.

cc: boolean, optional :

if cc is True, only the largest connect component is kept.

Returns:

mask : 3D boolean ndarray

The brain mask