niftynet.io.image_type module

This module defines images used by image reader, image properties are set by user or read from image header.

class niftynet.io.image_type.DataFromFile(file_path, name='loadable_data')

Bases: niftynet.io.image_type.Loadable

Data from file should have a valid file path (are files on hard drive) and a name

dtype

data type property of the input images :return: a tuple of input image data types

len(self.dtype) == len(self.file_path)

file_path

A tuple of valid image filenames, this property always returns a tuple, length of the tuple is one for single image, length of the tuple is larger than one for single image from multiple files. :return: a tuple of file paths

get_data()

name

A tuple of image names, this property always returns a tuple, length of the tuple is one for single image, length of the tuple is larger than one for single image from multiple files. :return: a tuple of image name tags

class niftynet.io.image_type.ImageFactory

Bases: object

Create image instance according to number of dimensions specified in image headers

INSTANCE_DICT = {2: <class 'niftynet.io.image_type.SpatialImage2D'>, 3: <class 'niftynet.io.image_type.SpatialImage3D'>, 4: <class 'niftynet.io.image_type.SpatialImage4D'>, 5: <class 'niftynet.io.image_type.SpatialImage5D'>}

classmethod create_instance(file_path, **kwargs)

Read image headers and create image instance :param file_path: a file path or a sequence of file paths :param kwargs: output properties for transforming the image data

array into a desired format

Returns:an image instance

class niftynet.io.image_type.Loadable

Bases: object

interface of loadable data

get_data()

loads a numpy array from the image object if the array has less than 5 dimensions it extends the array to 5d (corresponding to 3 spatial dimensions, temporal dim, modalities) ndims > 5 not currently supported

class niftynet.io.image_type.SpatialImage2D(file_path, name, interp_order, output_pixdim, output_axcodes)

Bases: niftynet.io.image_type.DataFromFile

2D images, axcodes specifications are ignored when loading. (Resampling to new pixdims is currently not supported)

get_data()

interp_order

interpolation order specified by user :return: a tuple of integers, with each element as an interpolation order of an image file

original_affine

affine info from the image header :return: a tuple of affine, with each element as an affine matrix of an image file

original_axcodes

axcodes info from the image header more info: http://nipy.org/nibabel/image_orientation.html :return: a tuple of axcodes, with each element as axcodes of an image file

original_pixdim

pixdim info from the image header :return: a tuple of pixdims, with each element as pixdims of an image file

output_axcodes

output axcodes info specified by user set to None for using the original axcodes in image header, otherwise get_data() change axes of the image array according to this value :return: a tuple of pixdims, with each element as pixdims of an image file

output_pixdim

output pixdim info specified by user set to None for using the original pixdim in image header otherwise get_data() transforms image array according to this value :return: a tuple of pixdims, with each element as pixdims of an image file

shape

This function read image shape info from the headers The lengths in the fifth dim of multiple images are summed as a multi-mod representation. The fourth dim corresponding to different time sequences is ignored. :return: a tuple of integers as image shape

class niftynet.io.image_type.SpatialImage3D(file_path, name, interp_order, output_pixdim, output_axcodes)

Bases: niftynet.io.image_type.SpatialImage2D

3D image from a single, supports resampling and reorientation (3D image from a set of 2D slices is currently not supported)

get_data()

output_axcodes

output_pixdim

shape

class niftynet.io.image_type.SpatialImage4D(file_path, name, interp_order, output_pixdim, output_axcodes)

Bases: niftynet.io.image_type.SpatialImage3D

4D image from a set of 3D volumes, supports resampling and reorientation

The 3D volumes are concatenated in the fifth dim (modality dim) (4D image from a single file is currently not supported)

get_data()

class niftynet.io.image_type.SpatialImage5D(file_path, name, interp_order, output_pixdim, output_axcodes)

Bases: niftynet.io.image_type.SpatialImage3D

5D image from a single file, resampling and reorientation are implemented as operations on each 3D slice individually

(5D image from a set of 4D files is currently not supported)

get_data()