Wraps command analyzeheader
Create or read an Analyze 7.5 header file.
Analyze image header, provides support for the most common header fields. Some fields, such as patient_id, are not currently supported. The program allows three nonstandard options: the field image_dimension.funused1 is the image scale. The intensity of each pixel in the associated .img file is (image value from file) * scale. Also, the origin of the Talairach coordinates (midline of the anterior commisure) are encoded in the field data_history.originator. These changes are included for compatibility with SPM.
All headers written with this program are big endian by default.
>>> import nipype.interfaces.camino as cmon
>>> hdr = cmon.AnalyzeHeader()
>>> hdr.inputs.in_file = 'tensor_fitted_data.Bfloat'
>>> hdr.inputs.scheme_file = 'A.scheme'
>>> hdr.inputs.data_dims = [256,256,256]
>>> hdr.inputs.voxel_dims = [1,1,1]
>>> hdr.run()
Inputs:
[Mandatory]
datatype : ('byte' or 'char' or '[u]short' or '[u]int' or 'float' or 'complex' or 'double')
The char datatype is 8 bit (not the 16 bit char of Java), as specified by the Analyze 7.5 standard. The byte, ushort and uint types are not part of the Analyze specification but are supported by SPM.
in_file : (an existing file name)
Tensor-fitted data filename
[Optional]
args : (a string)
Additional parameters to the command
centre : (a list of from 3 to 3 items which are an integer)
Voxel specifying origin of Talairach coordinate system for SPM, default [0 0 0].
data_dims : (a list of from 3 to 3 items which are an integer)
data dimensions in voxels
description : (a string)
Short description - No spaces, max length 79 bytes. Will be null terminated automatically.
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
greylevels : (a list of from 2 to 2 items which are an integer)
Minimum and maximum greylevels. Stored as shorts in the header.
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
initfromheader : (an existing file name)
Reads header information from file and intializes a new header with the valuesread from the file. You may replace any combination of fields in the new header by specifyingsubsequent options.
intelbyteorder : (a boolean)
Write header in intel byte order (little-endian).
networkbyteorder : (a boolean)
Write header in network byte order (big-endian). This is the default for new headers.
nimages : (an integer)
Number of images in the img file. Default 1.
offset : (an integer)
According to the Analyze 7.5 standard, this is the byte offset in the .img fileat which voxels start. This value can be negative to specify that the absolute value isapplied for every image in the file.
out_file : (a file name)
Unknown
picoseed : (a list of from 3 to 3 items which are an integer)
Voxel specifying the seed (for PICo maps), default [0 0 0].
printbigendian : (an existing file name)
Prints 1 if the header is big-endian, 0 otherwise.
printimagedims : (an existing file name)
Prints image data and voxel dimensions as Camino arguments and exits.
printintelbyteorder : (an existing file name)
Prints 1 if the header is little-endian, 0 otherwise.
printprogargs : (an existing file name)
Prints data dimension (and type, if relevant) arguments for a specific Caminoprogram, where prog is one of shredder, scanner2voxel, vcthreshselect, pdview, track.
readheader : (an existing file name)
Reads header information from file and prints to stdout. If this option is notspecified, then the program writes a header based on the other arguments.
scaleinter : (a float)
Constant to add to the image intensities. Used by SPM and MRIcro.
scaleslope : (a float)
Intensities in the image are scaled by this factor by SPM and MRICro. Default is 1.0.
scheme_file : (an existing file name)
Camino scheme file (b values / vectors, see camino.fsl2scheme)
voxel_dims : (a list of from 3 to 3 items which are a float)
voxel dimensions in mm
Outputs:
header : (an existing file name)
Analyze header
Wraps command dt2nii
Converts camino tensor data to NIfTI format
Reads Camino diffusion tensors, and converts them to NIFTI format as three .nii files.
Inputs:
[Mandatory]
header_file : (an existing file name)
A Nifti .nii or .hdr file containing the header information
in_file : (an existing file name)
tract file
[Optional]
args : (a string)
Additional parameters to the command
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
output_root : (a file name)
filename root prepended onto the names of three output files.
Outputs:
dt : (an existing file name)
diffusion tensors in NIfTI format
exitcode : (an existing file name)
exit codes from Camino reconstruction in NIfTI format
lns0 : (an existing file name)
estimated lns0 from Camino reconstruction in NIfTI format
Wraps command image2voxel
Converts Analyze / NIFTI / MHA files to voxel order.
Converts scanner-order data in a supported image format to voxel-order data. Either takes a 4D file (all measurements in single image) or a list of 3D images.
>>> import nipype.interfaces.camino as cmon
>>> img2vox = cmon.Image2Voxel()
>>> img2vox.inputs.in_file = '4d_dwi.nii'
>>> img2vox.run()
Inputs:
[Mandatory]
in_file : (an existing file name)
4d image file
[Optional]
args : (a string)
Additional parameters to the command
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
out_file : (a file name)
Unknown
out_type : ('float' or 'char' or 'short' or 'int' or 'long' or 'double')
"i.e. Bfloat". Can be "char", "short", "int", "long", "float" or "double"
Outputs:
voxel_order : (an existing file name)
path/name of 4D volume in voxel order
Wraps command niftidt2camino
Converts NIFTI-1 diffusion tensors to Camino format. The program reads the NIFTI header but does not apply any spatial transformations to the data. The NIFTI intensity scaling parameters are applied.
The output is the tensors in Camino voxel ordering: [exit, ln(S0), dxx, dxy, dxz, dyy, dyz, dzz].
The exit code is set to 0 unless a background mask is supplied, in which case the code is 0 in brain voxels and -1 in background voxels.
The value of ln(S0) in the output is taken from a file if one is supplied, otherwise it is set to 0.
NOTE FOR FSL USERS - FSL’s dtifit can output NIFTI tensors, but they are not stored in the usual way (which is using NIFTI_INTENT_SYMMATRIX). FSL’s tensors follow the ITK / VTK “upper-triangular” convention, so you will need to use the -uppertriangular option to convert these correctly.
Inputs:
[Mandatory]
in_file : (an existing file name)
A NIFTI-1 dataset containing diffusion tensors. The tensors are assumed to be in lower-triangular order as specified by the NIFTI standard for the storage of symmetric matrices. This file should be either a .nii or a .hdr file.
[Optional]
args : (a string)
Additional parameters to the command
bgmask : (an existing file name)
Binary valued brain / background segmentation, may be a raw binary file (specify type with -maskdatatype) or a supported image file.
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
lns0_file : (an existing file name)
File containing the log of the unweighted signal for each voxel, may be a raw binary file (specify type with -inputdatatype) or a supported image file.
out_file : (a file name)
Unknown
s0_file : (an existing file name)
File containing the unweighted signal for each voxel, may be a raw binary file (specify type with -inputdatatype) or a supported image file.
scaleinter : (a float)
A value v in the diffusion tensor is scaled to v * s + i. This is applied after any scaling specified by the input image. Default is 0.0.
scaleslope : (a float)
A value v in the diffusion tensor is scaled to v * s + i. This is applied after any scaling specified by the input image. Default is 1.0.
uppertriangular : (a boolean)
Specifies input in upper-triangular (VTK style) order.
Outputs:
out_file : (a file name)
diffusion tensors data in Camino format
Wraps command procstreamlines
Process streamline data
>>> import nipype.interfaces.camino as cmon
>>> proc = cmon.ProcStreamlines()
>>> proc.inputs.in_file = 'tract_data.Bfloat'
>>> proc.inputs.outputtracts = 'oogl'
>>> proc.run()
Inputs:
[Mandatory]
in_file : (an existing file name)
data file
[Optional]
allowmultitargets : (a boolean)
Allows streamlines to connect to multiple target volumes.
args : (a string)
Additional parameters to the command
datadims : (a list of from 3 to 3 items which are an integer)
data dimensions in voxels
directional : (a list of from 3 to 3 items which are an integer)
Splits the streamlines at the seed point and computes separate connection probabilities for each segment. Streamline segments are grouped according to their dot product with the vector (X, Y, Z). The ideal vector will be tangential to the streamline trajectory at the seed, such that the streamline projects from the seed along (X, Y, Z) and -(X, Y, Z). However, it is only necessary for the streamline trajectory to not be orthogonal to (X, Y, Z).
discardloops : (a boolean)
This option allows streamlines to enter a waypoint exactly once. After the streamline leaves the waypoint, the entire streamline is discarded upon a second entry to the waypoint.
endpointfile : (a file name)
Image containing endpoint ROIs. This should be an Analyze 7.5 header / image file.hdr and file.img.
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
exclusionfile : (a file name)
Image containing exclusion ROIs. This should be an Analyze 7.5 header / image file.hdr and file.img.
gzip : (a boolean)
save the output image in gzip format
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
inputmodel : ('raw' or 'voxels')
input model type (raw or voxels)
iterations : (a float)
Number of streamlines generated for each seed. Not required when outputting streamlines, but needed to create PICo images. The default is 1 if the output is streamlines, and 5000 if the output is connection probability images.
maxtractlength : (an integer)
maximum length of tracts
maxtractpoints : (an integer)
maximum number of tract points
mintractlength : (an integer)
minimum length of tracts
mintractpoints : (an integer)
minimum number of tract points
noresample : (a boolean)
Disables resampling of input streamlines. Resampling is automatically disabled if the input model is voxels.
out_file : (a file name)
Unknown
outputacm : (a boolean)
output all tracts in a single connection probability map (Analyze image)
outputcbs : (a boolean)
outputs connectivity-based segmentation maps; requires target outputfile
outputcp : (a boolean)
output the connection probability map (Analyze image, float)
outputroot : (a file name)
root directory for output
outputsc : (a boolean)
output the connection probability map (raw streamlines, int)
outputtracts : ('raw' or 'voxels' or 'oogl')
output tract file type
regionindex : (an integer)
index of specific region to process
resamplestepsize : (a float)
Each point on a streamline is tested for entry into target, exclusion or waypoint volumes. If the length between points on a tract is not much smaller than the voxel length, then streamlines may pass through part of a voxel without being counted. To avoid this, the program resamples streamlines such that the step size is one tenth of the smallest voxel dimension in the image. This increases the size of raw or oogl streamline output and incurs some performance penalty. The resample resolution can be controlled with this option or disabled altogether by passing a negative step size or by passing the -noresample option.
seedfile : (a file name)
Image Containing Seed Points
seedpointmm : (a list of from 3 to 3 items which are an integer)
The coordinates of a single seed point for tractography in mm
seedpointvox : (a list of from 3 to 3 items which are an integer)
The coordinates of a single seed point for tractography in voxels
targetfile : (a file name)
Image containing target volumes.
truncateinexclusion : (a boolean)
Retain segments of a streamline before entry to an exclusion ROI.
truncateloops : (a boolean)
This option allows streamlines to enter a waypoint exactly once. After the streamline leaves the waypoint, it is truncated upon a second entry to the waypoint.
voxeldims : (a list of from 3 to 3 items which are an integer)
voxel dimensions in mm
waypointfile : (a file name)
Image containing waypoints. Waypoints are defined as regions of the image with the same intensity, where 0 is background and any value > 0 is a waypoint.
Outputs:
proc : (an existing file name)
Processed Streamlines
Wraps command tractshredder
Extracts bunches of streamlines.
tractshredder works in a similar way to shredder, but processes streamlines instead of scalar data. The input is raw streamlines, in the format produced by track or procstreamlines.
The program first makes an initial offset of offset tracts. It then reads and outputs a group of bunchsize tracts, skips space tracts, and repeats until there is no more input.
>>> import nipype.interfaces.camino as cmon
>>> shred = cmon.TractShredder()
>>> shred.inputs.in_file = 'tract_data.Bfloat'
>>> shred.inputs.offset = 0
>>> shred.inputs.bunchsize = 1
>>> shred.inputs.space = 2
>>> shred.run()
Inputs:
[Mandatory]
in_file : (an existing file name)
tract file
[Optional]
args : (a string)
Additional parameters to the command
bunchsize : (an integer)
reads and outputs a group of bunchsize tracts
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
offset : (an integer)
initial offset of offset tracts
out_file : (a file name)
Unknown
space : (an integer)
skips space tracts
Outputs:
shredded : (an existing file name)
Shredded tract file
Wraps command vtkstreamlines
Use vtkstreamlines to convert raw or voxel format streamlines to VTK polydata
>>> import nipype.interfaces.camino as cmon
>>> vtk = cmon.VtkStreamlines()
>>> vtk.inputs.in_file = 'tract_data.Bfloat'
>>> vtk.inputs.voxeldims = [1,1,1]
>>> vtk.run()
Inputs:
[Mandatory]
in_file : (an existing file name)
data file
[Optional]
args : (a string)
Additional parameters to the command
colourorient : (a boolean)
Each point on the streamline is coloured by the local orientation.
environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
Environment variables
ignore_exception : (a boolean)
Print an error message instead of throwing an exception in case the interface fails to run
inputmodel : ('raw' or 'voxels')
input model type (raw or voxels)
interpolate : (a boolean)
the scalar value at each point on the streamline is calculated by trilinear interpolation
interpolatescalars : (a boolean)
the scalar value at each point on the streamline is calculated by trilinear interpolation
out_file : (a file name)
Unknown
scalar_file : (a file name)
image that is in the same physical space as the tracts
seed_file : (a file name)
image containing seed points
target_file : (a file name)
image containing integer-valued target regions
voxeldims : (a list of from 3 to 3 items which are an integer)
voxel dimensions in mm
Outputs:
vtk : (an existing file name)
Streamlines in VTK format