Bold_spatial_preprocessing3 pipeline¶

An example of fMRI data pre-processing¶

Pipeline insight

The Bold_spatial_preprocessing2 pipeline combines the following bricks:

- Realign

- Slice timing

- NewSegment

- Coregister Estimate

(default values: jobtype = ‘estimate’)

- Normalize12 Write (for T1w data)

(default values:

jobtype = ‘write’, write_interp = 4,
write_bounding_box = [[-78.0, -112.0, -70.0], [78.0, 76.0, 85.0]],
write_voxel_size = [1.0, 1.0, 1.0]

)

- Normalize12 Write (for functional data)

(default values:

jobtype = ‘write’, write_interp = 4,
write_bounding_box = [[-78.0, -112.0, -70.0], [78.0, 76.0, 85.0]],
write_voxel_size = [3.0, 3.0, 3.0]

)

- Smooth

Inputs parameters

anat_file (an existing uncompressed file):
An anatomical image (valid extensions: [.nii]). Ex. 3D T1 sequence sush as T1 turbo field echo.
ex. '/home/username/data/raw_data/Anat.nii'
func_files (A list of items which are an existing uncompressed file)
Functional images (valid extensions: [.nii]). Ex. 4D T2* sequence sush as echo planar imaging.
ex. ['/home/username/data/raw_data/Func.nii']

Inputs parameters with default values

st_acquistion (a string, default is sequential ascending)
Type of the acquisition, either sequential ascending, sequential descending, interleaved (middle-top), interleaved (bottom-up) or interleaved (top-down). Slice ordering is assumed to be from foot to head and bottom slice = 1.
ex. 'sequential ascending'
func_out_voxel_sizes(a list of three integer, default is [3.0, 3.0, 3.0])
Voxel size of the out functional data (used for write_voxel_size in Normalize12 Write for functional data)
ex. [3.0, 3.0, 3.0]
anat_out_voxel_sizes(a list of three integer, default is [1.0, 1.0, 1.0])
Voxel size of the out anatomical data (used for write_voxel_size in Normalize12 Write for anatomical data)
ex. [1.0, 1.0, 1.0]

Outputs parameters:

bias_corrected_images (a list of items which are a pathlike object or string representing an existing file)
The bias corrected images.
ex. '/home/username/data/derived_data/mAnat.nii'
bias_field_images (a list of items which are a pathlike object or string representing an existing file)
The estimated bias field.
ex. '/home/username/data/derived_data/bias.nii'

native_class_images (a list of items which are a list of items which are a pathlike object or string representing an existing file)

Native space probability maps .

ex. [['/home/username/data/derived_data/c1Anat.nii'],
    ['/home/username/data/derived_data/c2Anat.nii'],
    ['/home/username/data/derived_data/c3Anat.nii'],
    ['/home/username/data/derived_data/c4Anat.nii'],
    ['/home/username/data/derived_data/c5Anat.nii']]

forward_deformation_field (a list of items which are a pathlike object or string representing an existing file)
Forward deformation field. Could be used for spatially normalising images to MNI space.
ex. '/home/username/data/derived_data/y_Anat.nii'
realignment_parameters (a list of items which are a pathlike object or string representing an existing file)
The estimated translation and rotation parameters during the realign stage.
ex. '/home/username/data/derived_data/rp_Func.txt'
normalized_anat (a list of items which are a pathlike object or string representing an existing file)
The final normalised anatomical image .
ex. '/home/username/data/derived_data/wAnat.nii'
normalized_func (a list of items which are an existing file name)
Functional images, realigned, registered with the anatomical image and normalized.
ex. '/home/username/data/derived_data/wrFunc.nii'
smoothed_func (a list of items which are an existing file name)
The final, realigned then registered with the anatomical image, then normalised then smoothed, functional images .
ex. '/home/username/data/derived_data/swrFunc.nii'