def __eq__(self, other): # SAME DATA POINTS
""" same data points """
if (np.array_equal(self.x, other.x)
and np.array_equal(self.y, other.y)
and self.meta == other.meta):
return True
else:
return False
def require_patient_orientation(ds, patient_orientation):
if not np.array_equal(ds.ImageOrientationPatient,
np.array(
IMAGE_ORIENTATION_MAP[patient_orientation])):
raise ValueError("The supplied dataset has a patient "
f"orientation other than {patient_orientation}.")
def xyz_axes_from_dataset(ds, coord_system="DICOM"):
r"""Returns the x, y and z axes of a DICOM dataset's
pixel array in the specified coordinate system.
For DICOM RT Dose datasets, these are the x, y, z axes of the
dose grid.
Parameters
----------
ds : pydicom.dataset.Dataset
A DICOM dataset that contains pixel data. Supported modalities
include 'CT' and 'RTDOSE'.
coord_system : str, optional
The coordinate system in which to return the `x`, `y` and `z`
axes of the DICOM dataset. The accepted, case-insensitive
values of `coord_system` are:
'DICOM' or 'd':
Return axes in the DICOM coordinate system.
'patient', 'IEC patient' or 'p':
Return axes in the IEC patient coordinate system.
'fixed', 'IEC fixed' or 'f':
Return axes in the IEC fixed coordinate system.
Returns
-------
(x, y, z)
A tuple containing three `numpy.ndarray`s corresponding to the `x`,
`y` and `z` axes of the DICOM dataset's pixel array in the
specified coordinate system.
Notes
-----
Supported scan orientations [1]_:
=========================== ==========================
Orientation ds.ImageOrientationPatient
=========================== ==========================
Feet First Decubitus Left [0, 1, 0, 1, 0, 0]
Feet First Decubitus Right [0, -1, 0, -1, 0, 0]
Feet First Prone [1, 0, 0, 0, -1, 0]
Feet First Supine [-1, 0, 0, 0, 1, 0]
Head First Decubitus Left [0, -1, 0, 1, 0, 0]
Head First Decubitus Right [0, 1, 0, -1, 0, 0]
Head First Prone [-1, 0, 0, 0, -1, 0]
Head First Supine [1, 0, 0, 0, 1, 0]
=========================== ==========================
References
----------
.. [1] O. McNoleg, "Generalized coordinate transformations for Monte
Carlo (DOSXYZnrc and VMC++) verifications of DICOM compatible
radiotherapy treatment plans", arXiv:1406.0014, Table 1,
https://arxiv.org/ftp/arxiv/papers/1406/1406.0014.pdf
"""
position = np.array(ds.ImagePositionPatient)
orientation = np.array(ds.ImageOrientationPatient)
if not (
np.array_equal(np.abs(orientation), np.array([1, 0, 0, 0, 1, 0]))
or np.array_equal(np.abs(orientation), np.array([0, 1, 0, 1, 0, 0]))
):
raise ValueError(
"Dose grid orientation is not supported. Dose "
"grid slices must be aligned along the "
"superoinferior axis of patient."
)
is_decubitus = orientation[0] == 0
is_head_first = _orientation_is_head_first(orientation, is_decubitus)
di = float(ds.PixelSpacing[0])
dj = float(ds.PixelSpacing[1])
col_range = np.arange(0, ds.Columns * di, di)
row_range = np.arange(0, ds.Rows * dj, dj)
if is_decubitus:
x_dicom_fixed = orientation[1] * position[1] + col_range
y_dicom_fixed = orientation[3] * position[0] + row_range
else:
x_dicom_fixed = orientation[0] * position[0] + col_range
y_dicom_fixed = orientation[4] * position[1] + row_range
if is_head_first:
z_dicom_fixed = position[2] + np.array(ds.GridFrameOffsetVector)
else:
z_dicom_fixed = -position[2] + np.array(ds.GridFrameOffsetVector)
if coord_system.upper() in ("FIXED", "IEC FIXED", "F"):
x = x_dicom_fixed
y = z_dicom_fixed
z = -np.flip(y_dicom_fixed)
elif coord_system.upper() in ("DICOM", "D", "PATIENT", "IEC PATIENT", "P"):
if orientation[0] == 1:
x = x_dicom_fixed
elif orientation[0] == -1:
x = np.flip(x_dicom_fixed)
elif orientation[1] == 1:
y_d = x_dicom_fixed
elif orientation[1] == -1:
y_d = np.flip(x_dicom_fixed)
if orientation[4] == 1:
y_d = y_dicom_fixed
elif orientation[4] == -1:
y_d = np.flip(y_dicom_fixed)
elif orientation[3] == 1:
x = y_dicom_fixed
elif orientation[3] == -1:
x = np.flip(y_dicom_fixed)
if not is_head_first:
z_d = np.flip(z_dicom_fixed)
else:
z_d = z_dicom_fixed
if coord_system.upper() in ("DICOM", "D"):
y = y_d
z = z_d
elif coord_system.upper() in ("PATIENT", "IEC PATIENT", "P"):
y = z_d
z = -np.flip(y_d)
return (x, y, z)
def require_patient_orientation_be_HFS(ds):
if not np.array_equal(ds.ImageOrientationPatient,
np.array([1, 0, 0, 0, 1, 0])):
raise ValueError("The supplied dataset has a patient "
"orientation other than head-first supine.")