Series Class

Series – a multidimensional array of medical imaging pixels.

The Series class is a subclassed Numpy.ndarray enhancing the ndarray with relevant medical image methods and attributes. Most ndarray methods are inheritied, and are available with the Series class.

See: https://numpy.org/doc/stable/ for documentation on NumPy.

class imagedata.series.Series(data, input_order='none', opts=None, shape=(0, ), dtype=<class 'float'>, buffer=None, offset=0, strides=None, order=None, template=None, geometry=None, axes=None)

Series – a multidimensional array of medical imaging pixels.

The Series class is a subclassed Numpy.ndarray enhancing the ndarray with relevant medical image methods and attributes.

Series(data, input_order=’none’, opts=None, shape=(0,), dtype=float, order=None, template=None, geometry=None)

Examples

Read the contents of an input directory

>>> image = Series('directory/')

Make a Series instance from a Numpy.ndarray

>>> a = np.eye(128)
>>> image = Series(a)

Parameters

• data – (array_like or URL) Input data, either explicit as np.ndarray, np.uint16, np.float32, or by URL to input data.

• input_order (str) – How to sort the input data. Typical values are: * ‘none’ : 3D volume or 2D slice (default). * ‘time’ : Time-resolved data. * ‘b’ : Diffusion data with variable b values. * ‘te’ : Varying echo times. * ‘fa’ : Varying flip angles.

• opts – Dict of input options, mostly for format specific plugins (argparse.Namespace or dict)

• shape – Tuple of ints, specifying shape of input data.

• dtype – Numpy data type. Default: float

• template – Input data to use as template for DICOM header (Series, array_like or URL)

• geometry – Input data to use as template for geometry (Series, array_like or URL)

• order – Row-major (C-style) or column-major (Fortran-style) order, {‘C’, ‘F’}, optional

Returns

Series instance

property DicomHeaderDict

DICOM header dictionary

DicomHeaderDict[slice].tuple(tagvalue, filename, dicomheader)

Raises

ValueError – when DICOM header is not set.

Examples

Get values for slice=0:

>>> tagvalue, filename, dicomheader = image.DicomHeaderDict()[0]

Type

dict

property SOPClassUID

DICOM SOP Class UID

Raises

ValueError – when SOP Class UID is not set

property accessionNumber

Accession number

DICOM accession number

Raises

• ValueError – when accession number is not set

• TypeError – When accno is not printable

Type

str

property axes

axes objects

Raises

ValueError – when the axes are not set.

Type

list of Axis

property bvalues

b-values in s/mm2, as numpy array of floats

Length of array is number of tags.

Raises

ValueError – tags for dataset is not b tags

Type

numpy.array

property color

Color interpretation

Whether the array stores a color image, and the last index represents the color components

Raises

• ValueError – when color interpretation is not set

• TypeError – When color is not bool

Type

bool

property columns

Number of columns

Raises

ValueError – when number of columns is not defined.

Type

int

find_axis(name)

Find axis with given name

Parameters

name – Axis name to search for

Returns

axis object with given name

Raises

ValueError – when no axis object has given name

Usage:

>>> axis = si.find_axis('slice')

property frameOfReferenceUID

Frame of reference UID

DICOM frame of reference UID

Raises

• ValueError – when frame of reference UID is not set

• TypeError – When uid is not printable

Type

str

getDicomAttribute(keyword, slice=0, tag=0)

Get named DICOM attribute.

Parameters

• keyword (str) – name or dicom tag

• slice (int) – optional slice to get attribute from (default: 0)

• tag (int) – optional tag to get attribute from (default: 0)

Returns

DICOM attribute

getPositionForVoxel(r, transformation=None)

Get patient position for center of given voxel r

Use Patient Position and Image Orientation to calculate world coordinates for given voxel

Parameters

• r (numpy.array) – (s,r,c) of voxel in voxel coordinates

• transformation (numpy.array, optional) – transformation matrix when different from self.transformationMatrix

Returns

position of voxel in world coordinates (mm)

Return type

numpy.array((z,y,x))

getVoxelForPosition(p, transformation=None)

Get voxel for given patient position p

Use Patient Position and Image Orientation to calculate world coordinates for given voxel

Parameters

• p (numpy.array) – (z,y,x) of voxel in world coordinates (mm)

• transformation (numpy.array, optional) – transformation matrix when different from self.transformationMatrix

Returns

of voxel in voxel coordinates

Return type

numpy.array((s,r,c))

get_roi(roi=None, color='r', follow=False, vertices=False, im2=None, fig=None, cmap='gray', window=None, level=None, link=False)

Let user draw ROI on image

Parameters

• roi – Predefined vertices (optional). Dict of slices, index as [tag,slice] or [slice], each is list of (x,y) pairs.

• color (str) – Color of polygon ROI. Default: ‘r’.

• follow – (bool) Copy ROI to next tag. Default: False.

• vertices (bool) – Return both grid mask and dictionary of vertices. Default: False.

• im2 (Series or list of Series) – Series or list of Series which will be displayed in addition to self.

• fig (matplotlib.plt.Figure, optional) –

• cmap (str) – colour map for display. Default: ‘gray’

• window (number) – window width of signal intensities. Default is DICOM Window Width.

• level (number) – window level of signal intensities. Default is DICOM Window Center.

• link (bool) – whether scrolling is linked between displayed objects. Default: False.

Returns

If vertices, tuple of grid mask and vertices_dict. Otherwise, grid mask only.

• grid mask: Series object with voxel=1 inside ROI. Series object with shape (nz,ny,nx) from original image, dtype ubyte. Voxel inside ROI is 1, 0 outside.

• vertices_dict: if vertices: Dictionary of vertices.

Raises

• ValueError – when image is not a subclass of Series, or too many viewports are requested.

• IndexError – when there is a mismatch with images and viewports.

get_transformation_components_xyz()

Get origin and direction from transformation matrix in xyz convention.

Returns

Tuple of

• Origin np.array size 3.

• Orientation np.array size 6 (row, then column directional cosines) (DICOM convention).

• Normal vector np.array size 3 (slice direction).

Return type

tuple

property imagePositions

imagePositions

The [z,y,x] coordinates of the upper left hand corner (first pixel) of each slice.

dict(imagePositions[slice]) of [z,y,x] in mm, as numpy array

When setting, the position list is added to existing imagePositions. Overlapping dict keys will replace exisiting imagePosition for given slice.

Examples

>>> z,y,x = si.imagePositions[slice]

Examples

>>> for slice in range(slices):
>>>     si.imagePositions = {
>>>         slice: si.getPositionForVoxel(np.array([slice,0,0]))
>>>     }

Raises

• ValueError – when imagePositions are not set.

• AssertionError – when positions have wrong shape or datatype.

Type

dict of numpy.array([z,y,x])

property imageType

Image type

DICOM image type

Raises

• ValueError – when image type is not set.

• TypeError – When imagetype is not printable.

Type

list of str

property input_format

Input format

Possible input formats depend on the available formats plugins, and include ‘dicom’, ‘itk’ and ‘nifti’.

Type

str

property input_order

Input order

How to sort input files:

• INPUT_ORDER_NONE (‘none’): No sorting.

• INPUT_ORDER_TIME (‘time’): Sort on image time (acquisition time or trigger time).

• INPUT_ORDER_B (‘b’): Sort on b value.

• INPUT_ORDER_FA (‘fa’): Sort on flip angle.

• INPUT_ORDER_TE (‘te’): Sort on echo time.

• INPUT_ORDER_FAULTY (‘faulty’): Correct erroneous attributes.

Returns

Current input order.

Raises

ValueError – when order is illegal.

Type

str

property input_sort

Input order

How to sort output files:

• SORT_ON_SLICE: Run over slices first

• SORT_ON_TAG : Run over input order first, then slices

Returns

The input order.

Raises

ValueError – when input order is not defined.

Type

int

property orientation

Orientation

The direction cosines of the first row and the first column with respect to the patient. These attributes shall be provided as a pair. Row value (column index) for the z,y,x axes respectively, followed by the column value (row index) for the z,y,x axes respectively.

Raises

• ValueError – when orientation is not set.

• AssertionError – when len(orient) != 6

Type

numpy.array

property patientBirthDate

Patient birth date

DICOM patient birth date

Raises

• ValueError – when patient birth date is not set.

• TypeError – When patient birth date is not printable.

Type

str

property patientID

Patient ID

DICOM patient ID

Raises

• ValueError – when patient ID is not set

• TypeError – When patID is not printable

Type

str

property patientName

Patient name

DICOM patient name

Raises

• ValueError – when patient name is not set

• TypeError – When patnam is not printable

Type

str

property photometricInterpretation

Photometric Interpretation

DICOM Photometric Interpretation

Raises

• ValueError – when photometric interpretation is not set

• TypeError – When photometric interpretation is not printable

Type

str

property rows

Number of rows

Raises

ValueError – when number of rows is not defined.

Type

int

property seriesDescription

Series description

DICOM series description.

Raises

• ValueError – When series description is not set.

• AssertionError – when series description is not str

Type

str

property seriesInstanceUID

Series instance UID

DICOM series instance UID

Raises

• ValueError – when series instance UID is not set

• TypeError – When uid is not printable

Type

str

property seriesNumber

Series number

DICOM series number.

Raises

• ValueError – when series number is not set.

• ValueError – when series number cannot be converted to int.

Type

int

setDicomAttribute(keyword, value, slice=None, tag=None)

Set named DICOM attribute.

Parameters

• keyword (str) – name or dicom tag

• value – new value for DICOM attribute

• slice (int) – optional slice to set attribute for (default: all)

• tag (int) – optional tag to set attribute for (default: all)

Raises

ValueError – When no DICOM tag is set.

property shape

Matrix shape

Raises

IndexError – always when set (do not set shape). Should set axes instead.

Type

tuple

show(im2=None, fig=None, cmap='gray', window=None, level=None, link=False)

Show image

With ideas borrowed from Erlend Hodneland (2021).

Parameters

• im2 (Series or list of Series) – Series or list of Series which will be displayed in addition to self.

• fig (matplotlib.plt.Figure, optional) – if already exist

• cmap (str) – color map for display. Default: ‘gray’

• window (number) – window width of signal intensities. Default is DICOM Window Width.

• level (number) – window level of signal intensities. Default is DICOM Window Center.

• link (bool) – whether scrolling is linked between displayed images. Default: False

Raises

• ValueError – when image is not a subclass of Series, or too many viewports are requested.

• IndexError – when there is a mismatch with images and viewports.

property sliceLocations

Slice locations

Sorted numpy array of slice locations, in mm.

Raises

ValueError – When no slice locations are defined.

Type

numpy.array

property slices

Number of slices

Raises

• ValueError – when number of slices is not defined.

• DoNotSetSlicesError – Always (do not set slices)

Type

int

property sort_on

Output order

How to sort output files:

• SORT_ON_SLICE: Run over slices first

• SORT_ON_TAG : Run over input order first, then slices

Returns

Current output order.

Raises

ValueError – when output order is not defined.

Type

int

property spacing

spacing

Given as ds,dr,dc in mm. 2D image will return ds=1.

Raises

• ValueError – when spacing is not set.

• ValueError – when spacing is not a tuple of 3 coordinates

Usage:

>>> ds, dr, dc = si.spacing
>>> si.spacing = ds, dr, dc

Type

numpy.array([ds,dr,dc])

property studyID

Study ID

DICOM study ID

Raises

• ValueError – when study ID is not set.

• TypeError – When id is not printable

Type

str

property studyInstanceUID

Study instance UID

DICOM study instance UID

Raises

• ValueError – when study instance UID is not set.

• TypeError – When uid is not printable.

Type

str

property tags

Image tags for each slice

Image tags can be an array of:

• time points

• diffusion weightings (b values)

• flip angles

Setting the tags will adjust the tags in DicomHeaderDict too.

tags is a dict with (slice keys, tag array)

dict[slice] is np.array(tags)

Examples

>>>self.tags[slice][tag]

Raises

ValueError – when tags are not set.

Type

dict[slice] of numpy.array(tags)

property timeline

Timeline in seconds, as numpy array of floats

Delta time is given as seconds. First image is t=0. Length of array is number of tags.

Raises

ValueError – tags for dataset is not time tags

Type

numpy.array

to_rgb()

Create an RGB color image of self.

Returns

RGB Series object

Return type

Series

property transformationMatrix

Transformation matrix

If the transformation matrix is not set, an attempt will be made to calculate it from spacing, imagePositions and orientation.

When setting the transformation matrix, spacing and slices must be set in advance. A new transformation matrix will also impact orientation and imagePositions.

Raises

ValueError – Transformation matrix cannot be constructed.

Type

numpy.array

write(url, opts=None, formats=None)

Write Series image

Parameters

• self – Series array

• directory_name – directory name

• filename_template – template including %d for image number

• opts – Output options (argparse.Namespace or dict)

• formats – list of output formats, overriding opts.output_format (list or str)