Python library for converting dicom files to nifti
Author: | Arne Brys |
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Organization: | icometrix |
Repository: | https://github.com/icometrix/dicom2nifti |
API documentation: | http://dicom2nifti.readthedocs.io/en/latest |
pip install dicom2nifti
Should you have the need to use dicom2nifti in combination with pydicom 1.0.0 you have to install pydicom first from source before installing dicom2nifti. Once pydicom 1.0.0 is final and released on pypi this step will be obsolete.
pip install git+https://github.com/pydicom/pydicom.git
pip install dicom2nifti
pip install dicom2nifti --upgrade
dicom2nifti [--no-compression] [--no-reorientation] input_directory output_directory
for more information
dicom2nifti -h
Converting a directory with dicom files to nifti files
import dicom2nifti
dicom2nifti.convert_directory(dicom_directory, output_folder)
Converting a directory with only 1 series to 1 nifti file
import dicom2nifti
dicom2nifti.dicom_series_to_nifti(original_dicom_directory, output_file, reorient_nifti=True)
Most anatomical data for CT and MR should be supported as long as they are in classical dicom files.
Try avoiding "Implicit VR Endian" if possible as this makes converting non anatomical (i.e. DTI, fMRI, ...) much more difficult.
There is some vendor specific support, more specifically for 4D imaging like fMRI and DTI/DKI
Anatomical data should all be support. 4D images like fMRI and DTI/DKI are supported.
Anatomical data should all be support. 4D images like fMRI and DTI/DKI are supported.
For classic dicom files dicom2nifti support anatomical. For classic dicom files 4D images like fMRI and DTI/DKI are supported.
For "Philips Enhanced Dicom" there is no support for "Implicit VR Endian" transfer syntax. For the others we support anatomical and 4D images like fMRI and DTI/DKI.
Anatomical data should all be support. 4D images like fMRI and DTI/DKI are NOT supported. Anyone willing to share DTI and/or fMRI dicom form Hitachi scanners please contact us.
If you encounter unsupported data you can help the development of dicom2nifti by providing a dataset. This dataset should be anonymised (but leave as much of the private fields as possible).