%global _empty_manifest_terminate_build 0 Name: python-DicomRTTool Version: 2.0.8 Release: 1 Summary: Services for reading dicom files, RT structures, and dose files, as well as tools for converting numpy prediction masks back to an RT structure License: GNU Affero General Public License v3 URL: https://github.com/brianmanderson/Dicom_RT_and_Images_to_Mask Source0: https://mirrors.nju.edu.cn/pypi/web/packages/fd/68/778eac11a2991c66bb6e23ff80cf5b91717b125d0d282c016b868640d7cb/DicomRTTool-2.0.8.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-matplotlib Requires: python3-opencv-python Requires: python3-openpyxl Requires: python3-pandas Requires: python3-Pillow Requires: python3-pydicom Requires: python3-scikit-image Requires: python3-scipy Requires: python3-SimpleITK Requires: python3-six Requires: python3-xlrd Requires: python3-check-manifest Requires: python3-tqdm Requires: python3-pytest Requires: python3-PlotScrollNumpyArrays Requires: python3-setuptools %description # We're published! Please check out the Technical Note here: https://www.sciencedirect.com/science/article/abs/pii/S1879850021000485 and reference this work if you find it useful ### DOI:https://doi.org/10.1016/j.prro.2021.02.003 ## This code provides functionality for turning dicom images and RT structures into nifti files as well as turning prediction masks back into RT structures ## Installation guide pip install DicomRTTool ### Highly recommend to go through the jupyter notebook in the Examples folder and to read the Wiki ### Quick use guide from DicomRTTool.ReaderWriter import DicomReaderWriter, ROIAssociationClass Dicom_path = r'.some_path_to_dicom' Dicom_reader = DicomReaderWriter(description='Examples', arg_max=True) Dicom_reader.walk_through_folders(Dicom_path) # This will parse through all DICOM present in the folder and subfolders all_rois = Dicom_reader.return_rois(print_rois=True) # Return a list of all rois present Contour_names = ['tumor'] # Define what rois you want associations = [ROIAssociationClass('tumor', ['tumor_mr', 'tumor_ct'])] # Any list of roi associations Dicom_reader.set_contour_names_and_assocations(contour_names=Contour_names, associations=associations) Dicom_reader.get_images_and_mask() image_numpy = Dicom_reader.ArrayDicom mask_numpy = Dicom_reader.mask image_sitk_handle = Dicom_reader.dicom_handle mask_sitk_handle = Dicom_reader.annotation_handle ### Other interesting additions ### Adding information to the Dicom_reader.series_instances_dictionary from DicomRTTool.ReaderWriter import Tag plan_pydicom_string_keys = {"MyNamedRTPlan": Tag((0x300a, 0x002))} image_sitk_string_keys = {"MyPatientName": "0010|0010"} Dicom_reader = DicomReaderWriter(description='Examples', arg_max=True, plan_pydicom_string_keys=plan_pydicom_string_keys, image_sitk_string_keys=image_sitk_string_keys) ##### If you find this code useful, please provide a reference to my github page for others www.github.com/brianmanderson , thank you! ###### Ring update allows for multiple rings to be represented correctly ![multiple_rings.png](./Images/multiple_rings.png) #### Works on oblique images for masks and predictions* %package -n python3-DicomRTTool Summary: Services for reading dicom files, RT structures, and dose files, as well as tools for converting numpy prediction masks back to an RT structure Provides: python-DicomRTTool BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-DicomRTTool # We're published! Please check out the Technical Note here: https://www.sciencedirect.com/science/article/abs/pii/S1879850021000485 and reference this work if you find it useful ### DOI:https://doi.org/10.1016/j.prro.2021.02.003 ## This code provides functionality for turning dicom images and RT structures into nifti files as well as turning prediction masks back into RT structures ## Installation guide pip install DicomRTTool ### Highly recommend to go through the jupyter notebook in the Examples folder and to read the Wiki ### Quick use guide from DicomRTTool.ReaderWriter import DicomReaderWriter, ROIAssociationClass Dicom_path = r'.some_path_to_dicom' Dicom_reader = DicomReaderWriter(description='Examples', arg_max=True) Dicom_reader.walk_through_folders(Dicom_path) # This will parse through all DICOM present in the folder and subfolders all_rois = Dicom_reader.return_rois(print_rois=True) # Return a list of all rois present Contour_names = ['tumor'] # Define what rois you want associations = [ROIAssociationClass('tumor', ['tumor_mr', 'tumor_ct'])] # Any list of roi associations Dicom_reader.set_contour_names_and_assocations(contour_names=Contour_names, associations=associations) Dicom_reader.get_images_and_mask() image_numpy = Dicom_reader.ArrayDicom mask_numpy = Dicom_reader.mask image_sitk_handle = Dicom_reader.dicom_handle mask_sitk_handle = Dicom_reader.annotation_handle ### Other interesting additions ### Adding information to the Dicom_reader.series_instances_dictionary from DicomRTTool.ReaderWriter import Tag plan_pydicom_string_keys = {"MyNamedRTPlan": Tag((0x300a, 0x002))} image_sitk_string_keys = {"MyPatientName": "0010|0010"} Dicom_reader = DicomReaderWriter(description='Examples', arg_max=True, plan_pydicom_string_keys=plan_pydicom_string_keys, image_sitk_string_keys=image_sitk_string_keys) ##### If you find this code useful, please provide a reference to my github page for others www.github.com/brianmanderson , thank you! ###### Ring update allows for multiple rings to be represented correctly ![multiple_rings.png](./Images/multiple_rings.png) #### Works on oblique images for masks and predictions* %package help Summary: Development documents and examples for DicomRTTool Provides: python3-DicomRTTool-doc %description help # We're published! Please check out the Technical Note here: https://www.sciencedirect.com/science/article/abs/pii/S1879850021000485 and reference this work if you find it useful ### DOI:https://doi.org/10.1016/j.prro.2021.02.003 ## This code provides functionality for turning dicom images and RT structures into nifti files as well as turning prediction masks back into RT structures ## Installation guide pip install DicomRTTool ### Highly recommend to go through the jupyter notebook in the Examples folder and to read the Wiki ### Quick use guide from DicomRTTool.ReaderWriter import DicomReaderWriter, ROIAssociationClass Dicom_path = r'.some_path_to_dicom' Dicom_reader = DicomReaderWriter(description='Examples', arg_max=True) Dicom_reader.walk_through_folders(Dicom_path) # This will parse through all DICOM present in the folder and subfolders all_rois = Dicom_reader.return_rois(print_rois=True) # Return a list of all rois present Contour_names = ['tumor'] # Define what rois you want associations = [ROIAssociationClass('tumor', ['tumor_mr', 'tumor_ct'])] # Any list of roi associations Dicom_reader.set_contour_names_and_assocations(contour_names=Contour_names, associations=associations) Dicom_reader.get_images_and_mask() image_numpy = Dicom_reader.ArrayDicom mask_numpy = Dicom_reader.mask image_sitk_handle = Dicom_reader.dicom_handle mask_sitk_handle = Dicom_reader.annotation_handle ### Other interesting additions ### Adding information to the Dicom_reader.series_instances_dictionary from DicomRTTool.ReaderWriter import Tag plan_pydicom_string_keys = {"MyNamedRTPlan": Tag((0x300a, 0x002))} image_sitk_string_keys = {"MyPatientName": "0010|0010"} Dicom_reader = DicomReaderWriter(description='Examples', arg_max=True, plan_pydicom_string_keys=plan_pydicom_string_keys, image_sitk_string_keys=image_sitk_string_keys) ##### If you find this code useful, please provide a reference to my github page for others www.github.com/brianmanderson , thank you! ###### Ring update allows for multiple rings to be represented correctly ![multiple_rings.png](./Images/multiple_rings.png) #### Works on oblique images for masks and predictions* %prep %autosetup -n DicomRTTool-2.0.8 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-DicomRTTool -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 2.0.8-1 - Package Spec generated