Reading and writing of DICOM-SEG medical image segmentation storage files using pydicom as DICOM serialization/deserialization library. For detailed explanations about supported functionality and usage please have a look at the documentation.
Converting DICOM-SEG files into ITK compatible data formats, commonly used for
research, is made possible by the dcmqi
project for some time. However, the project is written in C++ and offers only
access to the conversion via the binaries itkimage2segimage and
segimage2itkimage. After a conversion of a DICOM-SEG file to ITK NRRD file
format, the user has to scan the output directory for generated files, load
them individually and potentially combine multiple files to the desired format.
This library aims to make this process much easier, by providing a Python
native implementation of reading and writing functionality with support for
numpy and SimpleITK. Additionally, common use cases like loading
multi-class segmentations are supported out-of-the-box.
pip install pydicom-segThis package uses Poetry (version >= 1.0.5) as build system.
git clone \
--recurse-submodules \
https://github.com/razorx89/pydicom-seg.git
cd pydicom-seg
poetry build
pip install dist/pydicom_seg-<version>-py3-none-any.whlAfter cloning the repository, please install the git pre-commit hook to
enforce code style and run static code analysis on every git commit.
git clone \
--recurse-submodules \
https://github.com/razorx89/pydicom-seg.git
cd pydicom-seg
poetry install
poetry run pre-commit installimport pydicom
import pydicom_seg
import SimpleITK as sitk
dcm = pydicom.dcmread('segmentation.dcm')
reader = pydicom_seg.SegmentReader()
result = reader.read(dcm)
for segment_number in result.available_segments:
image_data = result.segment_data(segment_number) # directly available
image = result.segment_image(segment_number) # lazy construction
sitk.WriteImage(image, f'/tmp/segmentation-{segment_number}.nrrd', True)dcm = pydicom.dcmread('segmentation.dcm')
reader = pydicom_seg.MultiClassReader()
result = reader.read(dcm)
image_data = result.data # directly available
image = result.image # lazy construction
sitk.WriteImage(image, '/tmp/segmentation.nrrd', True)Please generate a metainfo.json for the segments you want to serialize using the
web-based editor from dcmqi.
segmentation: SimpleITK.Image = ... # A segmentation image with integer data type
# and a single component per voxel
dicom_series_paths = [...] # Paths to an imaging series related to the segmentation
source_images = [
pydicom.dcmread(x, stop_before_pixels=True)
for x in dicom_series_paths
]
template = pydicom_seg.template.from_dcmqi_metainfo('metainfo.json')
writer = pydicom_seg.MultiClassWriter(
template=template,
inplane_cropping=False, # Crop image slices to the minimum bounding box on
# x and y axes. Maybe not supported by other frameworks.
skip_empty_slices=True, # Don't encode slices with only zeros
skip_missing_segment=False, # If a segment definition is missing in the
# template, then raise an error instead of
# skipping it.
)
dcm = writer.write(segmentation, source_images)
dcm.save_as('segmentation.dcm')pydicom-seg is distributed under the MIT license.