Generates dummy medical image data with realistic headers to be used in image handling tests
Project description
Generates dummy medical images, with junk image data but realistic headers, to test imaging handling pipelines
Installation
Medimage4tests is available on PyPI so to install, simply use pip
$ pip3 install medimages4testsor include in your package’s test_requires.
Usage
Create a pytest fixture consisting of a dummy image with field-map metadata in DICOM format
# Import medimages4tests generator functions
from medimages4tests.dummy.dicom.mri.fmap.ge.discovery_mr888.dv26_0_r05_2008a import get_image
# Return generated images in pytest fixtures (or alternative test framework)
@pytest.fixture()
def ge_dicom_fmap():
return get_image()Create a dummy NIfTI image
import numpy
# Import `get_image` function
from medimages4tests.dummy.nifti import get_image
# Create dummy nifti image of 10x10x10 containing all ones
@pytest.fixture()
def ones_nifti():
return get_image(
data=numpy.ones((10, 10, 10))
)Access real T1-weighted from OpenNeuro.org
from medimages4tests.mri.neuro.t1w import get_image
@pytest.fixture()
def t1w_nifti():
return get_image(sample="ds004130-ON01016")Acknowledgements
The authors acknowledge the facilities and scientific and technical assistance of the National Imaging Facility, a National Collaborative Research Infrastructure Strategy (NCRIS) capability.
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