fsl.data.image

This module provides the Nifti and Image classes, for representing NIFTI1 and NIFTI2 images. The nibabel package is used for file I/O.

It is very easy to load a NIFTI image:

from fsl.data.image import Image
myimg = Image('MNI152_T1_2mm.nii.gz')

A handful of other functions are also provided for working with image files and file names:

canonicalShape	Calculates a canonical shape, how the given shape should be presented.
looksLikeImage	Returns True if the given file looks like a NIFTI image, False otherwise.
addExt	Adds a file extension to the given file prefix.
splitExt	Splits the base name and extension for the given filename.
getExt	Gets the extension for the given file name.
removeExt	Removes the extension from the given file name.
defaultExt	Returns the default NIFTI file extension that should be used.

fsl.data.image.ALLOWED_EXTENSIONS = ['.nii.gz', '.nii', '.img', '.hdr', '.img.gz', '.hdr.gz']

The file extensions which we understand. This list is used as the default if the allowedExts parameter is not passed to any of the *Ext functions, or the looksLikeImage() function.

fsl.data.image.EXTENSION_DESCRIPTIONS = ['Compressed NIFTI images', 'NIFTI images', 'ANALYZE75 images', 'NIFTI/ANALYZE75 headers', 'Compressed NIFTI/ANALYZE75 images', 'Compressed NIFTI/ANALYZE75 headers']

Descriptions for each of the extensions in ALLOWED_EXTENSIONS.

fsl.data.image.FILE_GROUPS = [('.hdr', '.img'), ('.hdr.gz', '.img.gz')]

File suffix groups used by addExt() to resolve file path ambiguities - see fsl.utils.path.addExt().

exception fsl.data.image.PathError

Bases: Exception

Exception class raised by the functions defined in this module when something goes wrong.

__module__ = 'fsl.utils.path'

__weakref__

list of weak references to the object (if defined)

class fsl.data.image.Nifti(*args, **kwargs)

Bases: fsl.utils.notifier.Notifier, fsl.utils.meta.Meta

The Nifti class is intended to be used as a base class for things which either are, or are associated with, a NIFTI image. The Nifti class is intended to represent information stored in the header of a NIFTI file - if you want to load the data from a file, use the Image class instead.

When a Nifti instance is created, it adds the following attributes to itself:

header	The nibabel NIFTI1/NIFTI2/Analyze header object.
shape	A list/tuple containing the number of voxels along each image dimension.
pixdim	A list/tuple containing the length of one voxel along each image dimension.
voxToWorldMat	A 4*4 array specifying the affine transformation for transforming voxel coordinates into real world coordinates.
worldToVoxMat	A 4*4 array specifying the affine transformation for transforming real world coordinates into voxel coordinates.
intent	The NIFTI intent code specified in the header (or constants.NIFTI_INTENT_NONE for Analyze images).

The header field may either be a nifti1, nifti2, or analyze header object. Make sure to take this into account if you are writing code that should work with all three. Use the niftiVersion() property if you need to know what type of image you are dealing with.

The shape attribute may not precisely match the image shape as reported in the NIFTI header, because trailing dimensions of size 1 are squeezed out. See the __determineShape() and mapIndices() methods.

Affine transformations

The Nifti class is aware of three coordinate systems:

• The voxel coordinate system, used to access image data

• The world coordinate system, where voxel coordinates are transformed into a millimetre coordinate system, defined by the sform and/or qform elements of the NIFTI header.

• The fsl coordinate system, where voxel coordinates are scaled by the pixdim values in the NIFTI header, and the X axis is inverted if the voxel-to-world affine has a positive determinant.

The getAffine() method is a simple means of acquiring an affine which will transform between any of these coordinate systems.

See here for more details on the fsl coordinate system..

The Nifti class follows the same process as nibabel in determining the voxel to world affine (see http://nipy.org/nibabel/nifti_images.html#the-nifti-affines):

1. If sform_code != 0 (“unknown”) use the sform affine; else

2. If qform_code != 0 (“unknown”) use the qform affine; else

3. Use the fall-back affine.

However, the fall-back affine used by the Nifti class differs to that used by nibabel. In nibabel, the origin (world coordinates (0, 0, 0)) is set to the centre of the image. Here in the Nifti class, we set the world coordinate orign to be the corner of the image, i.e. the corner of voxel (0, 0, 0).

You may change the voxToWorldMat of a Nifti instance (unless it is an Analyze image). When you do so:

• Only the sform of the underlying Nifti1Header object is changed

• The qform is not modified.

• If the sform_code was previously set to NIFTI_XFORM_UNKNOWN, it is changed to NIFTI_XFORM_ALIGNED_ANAT. Otherwise, the sform_code is not modified.

ANALYZE support

A Nifti instance expects to be passed either a nibabel.nifti1.Nifti1Header or a nibabel.nifti2.Nifti2Header, but can also encapsulate a nibabel.analyze.AnalyzeHeader. In this case:

• The image voxel orientation is assumed to be R->L, P->A, I->S.

• The affine will be set to a diagonal matrix with the header pixdims as its elements (with the X pixdim negated), and an offset specified by the ANALYZE origin fields. Construction of the affine is handled by nibabel.

• The niftiVersion() method will return 0.

• The getXFormCode() method will return constants.NIFTI_XFORM_ANALYZE.

Metadata

The Image class inherits from the Meta class - its methods can be used to store and query any meta-data associated with the image.

Notification

The Nifti class implements the Notifier interface - listeners may register to be notified on the following topics:

'transform'	The affine transformation matrix has changed. This topic will occur when the voxToWorldMat() is changed.
'header'	A header field has changed. This will occur when the intent() is changed.

__init__(header)

Create a Nifti object.

Parameters

header – A nibabel.nifti1.Nifti1Header, nibabel.nifti2.Nifti2Header, or nibabel.analyze.AnalyzeHeader to be used as the image header.

__del__()

Clears the reference to the nibabel header object.

static determineShape(header)

This method is called by __init__(). It figures out the actual shape of the image data, and the zooms/pixdims for each data axis. Any empty trailing dimensions are squeezed, but the returned shape is guaranteed to be at least 3 dimensions. Returns:

• A sequence/tuple containing the image shape, as reported in the header.

• A sequence/tuple containing the effective image shape.

• A sequence/tuple containing the zooms/pixdims.

static determineAffine(header)

Called by __init__(). Figures out the voxel-to-world coordinate transformation matrix that is associated with this Nifti instance.

static generateAffines(voxToWorldMat, shape, pixdim)

Called by __init__(), and the voxToWorldMat() setter. Generates and returns a dictionary containing affine transformations between the voxel, fsl, and world coordinate systems. These affines are accessible via the getAffine() method.

Parameters

• voxToWorldMat – The voxel-to-world affine transformation

• shape – Image shape (number of voxels along each dimension

• pixdim – Image pixdims (size of one voxel along each dimension)

Returns

A tuple containing:

• a dictionary of affine transformations between each pair of coordinate systems

• True if the image is to be considered “neurological”, False otherwise - see the isNeurological() method.

static identifyAffine(image, xform, from_=None, to=None)

Attempt to identify the source or destination space for the given affine.

xform is assumed to be an affine transformation which can be used to transform coordinates between two coordinate systems associated with image.

If one of from_ or to is provided, the other will be derived. If neither are provided, both will be derived. See the Nifti.getAffine() method for details on the valild values that from_ and to may take.

Parameters

• image – Nifti instance associated with the affine.

• xform – (4, 4) numpy array encoding an affine transformation

• from – Label specifying the coordinate system which xform takes as input

• to – Label specifying the coordinate system which xform produces as output

Returns

A tuple containing: - A label for the from_ coordinate system - A label for the to coordinate system

strval(key)

Returns the specified NIFTI header field, converted to a python string, correctly null-terminated, and with non-printable characters removed.

This method is used to sanitise some NIFTI header fields. The default Python behaviour for converting a sequence of bytes to a string is to strip all termination characters (bytes with value of 0x00) from the end of the sequence.

This default behaviour does not handle the case where a sequence of bytes which did contain a long string is subsequently overwritten with a shorter string - the short string will be terminated, but that termination character will be followed by the remainder of the original string.

property header

Return a reference to the nibabel header object.

property niftiVersion

Returns the NIFTI file version:

• 0 for ANALYZE

• 1 for NIFTI1

• 2 for NIFTI2

property shape

Returns a tuple containing the image data shape.

property ndim

Returns the number of dimensions in this image. This number may not match the number of dimensions specified in the NIFTI header, as trailing dimensions of length 1 are ignored. But it is guaranteed to be at least 3.

property pixdim

Returns a tuple containing the image pixdims (voxel sizes).

property niftiDataType

Returns the NIFTI data type code of this image.

property intent

Returns the NIFTI intent code of this image.

property xyzUnits

Returns the NIFTI XYZ dimension unit code.

property timeUnits

Returns the NIFTI time dimension unit code.

getAffine(from_, to)

Return an affine transformation which can be used to transform coordinates from from_ to to.

Valid values for the from_ and to arguments are:

• 'voxel': The voxel coordinate system

• 'world': The world coordinate system, as defined by the image sform/qform

• 'fsl': The FSL coordinate system (scaled voxels, with a left-right flip if the sform/qform has a positive determinant)

Parameters

• from – Source coordinate system

• to – Destination coordinate system

Returns

A numpy array of shape (4, 4)

property worldToVoxMat

Returns a numpy array of shape (4, 4) containing an affine transformation from world coordinates to voxel coordinates.

property voxToWorldMat

Returns a numpy array of shape (4, 4) containing an affine transformation from voxel coordinates to world coordinates.

property voxToScaledVoxMat

Returns a transformation matrix which transforms from voxel coordinates into scaled voxel coordinates, with a left-right flip if the image appears to be stored in neurological order.

See http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT/FAQ#What_is_the _format_of_the_matrix_used_by_FLIRT.2C_and_how_does_it_relate_to _the_transformation_parameters.3F

property scaledVoxToVoxMat

Returns a transformation matrix which transforms from scaled voxels into voxels, the inverse of the voxToScaledVoxMat() transform.

mapIndices(sliceobj)

Adjusts the given slice object so that it may be used to index the underlying nibabel NIFTI image object.

See the __determineShape() method.

Parameters

sliceobj – Something that can be used to slice a multi-dimensional array, e.g. arr[sliceobj].

getXFormCode(code=None)

This method returns the code contained in the NIFTI header, indicating the space to which the (transformed) image is oriented.

The code parameter may be either sform (the default) or qform in which case the corresponding matrix is used.

Returns

one of the following codes: - NIFTI_XFORM_UNKNOWN - NIFTI_XFORM_SCANNER_ANAT - NIFTI_XFORM_ALIGNED_ANAT - NIFTI_XFORM_TALAIRACH - NIFTI_XFORM_MNI_152 - NIFTI_XFORM_ANALYZE

axisMapping(xform)

Returns the (approximate) correspondence of each axis in the source coordinate system to the axes in the destination coordinate system, where the source and destinations are defined by the given affine transformation matrix.

isNeurological()

Returns True if it looks like this Nifti object has a neurological voxel orientation, False otherwise. This test is purely based on the determinant of the voxel-to-mm transformation matrix - if it has a positive determinant, the image is assumed to be in neurological orientation, otherwise it is assumed to be in radiological orientation.

..warning:: This method will return True for images with an

unknown orientation (e.g. the sform_code and qform_code are both set to 0). Therefore, you must check the orientation via the getXFormCode() before trusting the result of this method.

See http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT/FAQ#What_is_the _format_of_the_matrix_used_by_FLIRT.2C_and_how_does_it_relate_to _the_transformation_parameters.3F

sameSpace(other)

Returns True if the other image (assumed to be a Nifti instance) has the same dimensions and is in the same space as this image.

getOrientation(axis, xform)

Returns a code representing the orientation of the specified axis in the input coordinate system of the given transformation matrix.

Parameters

xform –

A transformation matrix which is assumed to transform coordinates from some coordinate system (the one which you want an orientation for) into the image world coordinate system.

For example, if you pass in the voxel-to-world transformation matrix, you will get an orientation for axes in the voxel coordinate system.

This method returns one of the following values, indicating the direction in which coordinates along the specified axis increase:

• ORIENT_L2R: Left to right

• ORIENT_R2L: Right to left

• ORIENT_A2P: Anterior to posterior

• ORIENT_P2A: Posterior to anterior

• ORIENT_I2S: Inferior to superior

• ORIENT_S2I: Superior to inferior

• ORIENT_UNKNOWN: Orientation is unknown

The returned value is dictated by the XForm code contained in the image file header (see the getXFormCode() method). Basically, if the XForm code is unknown, this method will return ORIENT_UNKNOWN for all axes. Otherwise, it is assumed that the image is in RAS orientation (i.e. the X axis increases from left to right, the Y axis increases from posterior to anterior, and the Z axis increases from inferior to superior).

adjust(pixdim=None, shape=None, origin=None)

Return a new Nifti object with the specified pixdim or shape. The affine of the new Nifti is adjusted accordingly.

Only one of pixdim or shape can be specified.

See affine.rescale() for the meaning of the origin argument.

Only the spatial dimensions may be adjusted - use the functions in the image.resample module if you need to adjust non-spatial dimensions.

Parameters

• pixdim – New voxel dimensions

• shape – New image shape

• origin – Voxel grid alignment - either 'centre' (the default) or 'corner'

Returns

A new Nifti object based on this one, with adjusted pixdims, shape and affine.

__module__ = 'fsl.data.image'

class fsl.data.image.Image(*args, **kwargs)

Bases: fsl.data.image.Nifti

Class which represents a NIFTI image. Internally, the image is loaded/stored using a nibabel.nifti1.Nifti1Image or nibabel.nifti2.Nifti2Image, and data access managed by a ImageWrapper.

In addition to the attributes added by the Nifti.__init__() method, the following attributes/properties are present on an Image instance as properties (https://docs.python.org/2/library/functions.html#property):

name	The name of this Image - defaults to the image file name, sans-suffix.
dataSource	The data source of this Image - the name of the file from where it was loaded, or some other string describing its origin.
nibImage	A reference to the nibabel NIFTI image object.
saveState	A boolean value which is True if this image is saved to disk, False if it is in-memory, or has been edited.
dataRange	The minimum/maximum values in the image. Depending upon the value of the calcRange parameter to __init__(), this may be calculated when the Image is created, or may be incrementally updated as more image data is loaded from disk.

The Image class adds some Notifier topics to those which are already provided by the Nifti class - listeners may register to be notified of changes to the above properties, by registering on the following _topic_ names (see the Notifier class documentation):

'data'	This topic is notified whenever the image data changes (via the __setitem__() method). The indices/ slices of the portion of data that was modified is passed to registered listeners as the notification value (see Notifier.notify()).
'saveState'	This topic is notified whenever the saved state of the image changes (i.e. data or voxToWorldMat is edited, or the image saved to disk).
'dataRange'	This topic is notified whenever the image data range is changed/adjusted.

__init__(image, name=None, header=None, xform=None, loadData=True, calcRange=True, threaded=False, dataSource=None, loadMeta=False, **kwargs)

Create an Image object with the given image data or file name.

Parameters

• image – A string containing the name of an image file to load, or a numpy array, or a nibabel image object, or an Image object.

• name – A name for the image.

• header – If not None, assumed to be a nibabel.nifti1.Nifti1Header or nibabel.nifti2.Nifti2Header to be used as the image header. Not applied to images loaded from file, or existing nibabel images.

• xform – A \(4\times 4\) affine transformation matrix which transforms voxel coordinates into real world coordinates. If not provided, and a header is provided, the transformation in the header is used. If neither a xform nor a header are provided, an identity matrix is used. If both a xform and a header are provided, the xform is used in preference to the header transformation.

• loadData – If True (the default) the image data is loaded in to memory. Otherwise, only the image header information is read, and the image data is kept from disk. In either case, the image data is accessed through an ImageWrapper instance. The data may be loaded into memory later on via the loadData() method.

• calcRange – If True (the default), the image range is calculated immediately (vi a call to calcRange()). Otherwise, the image range is incrementally updated as more data is read from memory or disk.

• threaded – If True, the ImageWrapper will use a separate thread for data range calculation. Defaults to False. Ignored if loadData is True.

• dataSource – If image is not a file name, this argument may be used to specify the file from which the image was loaded.

• loadMeta – If True, any metadata contained in JSON sidecar files is loaded and attached to this Image via the Meta interface. if False, metadata can be loaded at a later stage via the loadMeta() function. Defaults to False.

All other arguments are passed through to the nibabel.load function (if it is called).

__hash__()

Returns a number which uniquely idenfities this Image instance (the result of id(self)).

__str__()

Return a string representation of this Image instance.

__repr__()

See the __str__() method.

__del__()

Closes any open file handles, and clears some references.

getImageWrapper()

Returns the ImageWrapper instance used to manage access to the image data.

property dataSource

Returns the data source (e.g. file name) that this Image was loaded from (None if this image only exists in memory).

property nibImage

Returns a reference to the nibabel NIFTI image instance. Note that if the image data has been modified through this Image, it will be out of sync with what is returned by the nibabel object, until a call to save() is made.

property data

Returns the image data as a numpy array.

Warning

Calling this method will cause the entire image to be loaded into memory.

property saveState

Returns True if this Image has been saved to disk, False otherwise.

property dataRange

Returns the image data range as a (min, max) tuple. If the calcRange parameter to __init__() was False, these values may not be accurate, and may change as more image data is accessed.

If the data range has not been no data has been accessed, (None, None) is returned.

property dtype

Returns the numpy data type of the image data.

property nvals

Returns the number of values per voxel in this image. This will usually be 1, but may be 3 or 4, for images of type NIFTI_TYPE_RGB24 or NIFTI_TYPE_RGBA32.

property iscomplex

Returns True if this image has a complex data type, False otherwise.

property voxToWorldMat

Returns a numpy array of shape (4, 4) containing an affine transformation from voxel coordinates to world coordinates.

__headerChanged(*args, **kwargs)

Called when header properties of this Nifti instance changes. Updates the saveState accordinbgly.

__dataRangeChanged(*args, **kwargs)

Called when the ImageWrapper data range changes. Notifies any listeners of this Image (registered through the Notifier interface) on the 'dataRange' topic.

calcRange(sizethres=None)

Forces calculation of the image data range.

Parameters

sizethres – If not None, specifies an image size threshold (total number of bytes). If the number of bytes in the image is greater than this threshold, the range is calculated on a sample (the first volume for a 4D image, or slice for a 3D image).

loadData()

Makes sure that the image data is loaded into memory. See ImageWrapper.loadData().

save(filename=None)

Saves this Image to the specifed file, or the dataSource if filename is None.

Note that calling save on an image with modified data will cause the entire image data to be loaded into memory if it has not already been loaded.

__getitem__(sliceobj)

Access the image data with the specified sliceobj.

Parameters

sliceobj – Something which can slice the image data.

__setitem__(sliceobj, values)

Set the image data at sliceobj to values.

Parameters

• sliceobj – Something which can slice the image data.

• values – New image data.

Note

Modifying image data will force the entire image to be loaded into memory if it has not already been loaded.

__module__ = 'fsl.data.image'

fsl.data.image.canonicalShape(shape)

Calculates a canonical shape, how the given shape should be presented. The shape is forced to be at least three dimensions, with any other trailing dimensions of length 1 ignored.

fsl.data.image.loadMetadata(image)

Searches for and loads any sidecar JSON files associated with the given Image.

If the image looks to be part of a BIDS data set, bids.loadMetadata() is used. Otherwise, if a JSON file with the same file prefix is present alongside the image, it is directly loaded.

Parameters

image – Image instance

Returns

Dict containing any metadata that was loaded.

fsl.data.image.looksLikeImage(filename, allowedExts=None)

Returns True if the given file looks like a NIFTI image, False otherwise.

Note

The filename cannot just be a file prefix - it must include the file suffix (e.g. myfile.nii.gz, not myfile).

Parameters

• filename – The file name to test.

• allowedExts – A list of strings containing the allowed file extensions - defaults to ALLOWED_EXTENSIONS.

fsl.data.image.addExt(prefix, mustExist=True, unambiguous=True)

Adds a file extension to the given file prefix. See addExt().

fsl.data.image.splitExt(filename)

Splits the base name and extension for the given filename. See splitExt().

fsl.data.image.getExt(filename)

Gets the extension for the given file name. See getExt().

fsl.data.image.removeExt(filename)

Removes the extension from the given file name. See removeExt().

fsl.data.image.fixExt(filename, **kwargs)

Fix the extension of filename.

For example, if a file name is passed in as file.nii.gz, but the file is actually file.nii, this function will fix the file name.

If filename already exists, it is returned unchanged.

All other arguments are passed through to addExt().

fsl.data.image.defaultExt()

Returns the default NIFTI file extension that should be used.

If the $FSLOUTPUTTYPE variable is set, its value is used. Otherwise, .nii.gz is returned.