Excerpt of 3D Slicer module logic code to essentially export the "Red" slice view image to a single slice DICOM file

exportRedSliceToDICOM.py

class SomeModuleLogic(ScriptedLoadableModuleLogic):
    def exportRedSliceAsDicom(self, patientNameSH, xRangeMm=150, yRangeMm=150, zRangeMm=0.5, outputFolderPath=None, dicomTagDict=None):
        """ This function creates an ROI centered on the center of the Red slice view, and 
        with axes aligned with that slice view's slice, and with thickness specified by zRangeMm.
        This ROI is then used to crop the red slice's current background image volume to slices
        in this orientation (I choose the zRange such that this results in a single slice by 
        setting it to close to the minimum voxel side length), and export the result to DICOM.
        In order to export to DICOM, a patient and study need to be created in the subject hierarchy,
        these are done the subject name given in patientNameSH and with study name "SingleSliceExport".
        The DICOM file(s) are exported to the supplied outputFolderPath. DICOM tags in the export
        can be suppled via a dictionary with tag names as keys and tag values as values (this has not
        been extensively tested, but should probably work and would be a way to force things like UIDs
        to desired vaues). If no tag dictionary is supplied, then by default the DICOM tags "PatientName"
        and "StudyDescription" are set to patientNameSH just as a simple and minimal way to keep track.
        """
        redSliceNode = slicer.mrmlScene.GetNodeByID('vtkMRMLSliceNodeRed')
        sliceTransformMatrix = redSliceNode.GetSliceToRAS()
        roi = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLMarkupsROINode', 'SliceExportROI')
        roiTransformMatrix = vtk.vtkMatrix4x4()
        roiTransformMatrix.DeepCopy(sliceTransformMatrix)
        # The DICOM viewer I was using ended up showing most of the slices I was extracting as
        # flipped LR compared to the view in Slicer (though some were flipped on both axes)
        # There are lots of reasons this could happen, and this is not proof of a bug in either
        # Slicer or the viewer (the angle from which an image is viewed is not fully
        # prescribed in the DICOM header, only it's location in space).  I just wanted a quick
        # hack fix which resulted in images which ended up oriented the same.  Through trial
        # and error, I found that inverting the second axis of the ROI did this for my image
        # orientation.  Your mileage may vary. IMPORTNANT NOTE: Inverting a single axis is NOT appropriate
        # if you are exporting more than one slice!!  Changing a single axis direction in 3D space
        # is equivalent to a mirror reflection, and the "handedness" of any non-mirror symmetric 
        # 3D structure will be inverted compared to reality.  It's OK for a single slice because 
        # there can't be any "handedness" to a 2D structure (a reflection is equivalent to looking at
        # the same plane from the other side). 
        for row in range(4):
            for col in [1]: # invert second axis
                roiTransformMatrix.SetElement(row, col, -1 * roiTransformMatrix.GetElement(row,col))
        # Position and orient ROI
        roi.SetAndObserveObjectToNodeMatrix(roiTransformMatrix)
        # Size ROI
        roi.SetSize([xRangeMm, yRangeMm, zRangeMm])
        # Get Volume Node to crop (background volume of red slice)
        sliceLogic = slicer.app.applicationLogic().GetSliceLogic(redSliceNode)
        compositeNode = sliceLogic.GetSliceCompositeNode()
        volNodeID = compositeNode.GetBackgroundVolumeID()
        volNode = slicer.mrmlScene.GetNodeByID(volNodeID)
        # Crop using ROI
        croppedNode = self.cropVolumeUsingROI(volNode, roi, interpolation_mode='linear', isotropic=True)
        # Export to DICOM
        patientItemID, studyItemID = self.createSubjectHierarchyPatientAndStudy(patientNameSH,'SingleSliceExport')
        self.putImageVolumeUnderStudy(croppedNode, studyItemID)
        if dicomTagDict is None:
            dicomTagDict = {"PatientName": patientNameSH, "StudyDescription": patientNameSH}
            # "StudyID" seems to be automatically overwritten to "SLICER10001" for some reason
        self.exportImageVolumeToDICOM(croppedNode, os.path.join(outputFolderPath, patientNameSH), tagDictionary=dicomTagDict)
        # Clean up 
        slicer.mrmlScene.RemoveNode(roi)

        return

    def exportImageVolumeToDICOM(self, volNode, outputDirectory=None, tagDictionary={"PatientID":"anon", "StudyID":"testStudy"}):
        """ Export a supplied scalar volume node to DICOM, setting DICOM tags using a dictionary,
        and saving to a supplied outputDirectory. 
        """
        if outputDirectory is None:
            # Ask user where to output (TODO)
            slicer.util.errorDisplay('No output directory specified') 
            return

        import DICOMScalarVolumePlugin
        exporter = DICOMScalarVolumePlugin.DICOMScalarVolumePluginClass()
        # Get image volume's subject hierarchy ID
        shNode = slicer.vtkMRMLSubjectHierarchyNode.GetSubjectHierarchyNode(slicer.mrmlScene)
        volumeShItemID = shNode.GetItemByDataNode(volNode)
        # Break the volume into individual exportable slices (?)
        exportables = exporter.examineForExport(volumeShItemID)
        # For each slice, set the needed tags and the output directory
        for exp in exportables:
            # Set output folder
            exp.directory = outputDirectory
            for tagName, tagValue in tagDictionary.items():
                exp.setTag(tagName, tagValue)
        # Do the export
        exporter.export(exportables)


    def putImageVolumeUnderStudy(self, volNode, studySubjectHierarchyID):
        """ Place an image volume under a dicom study in the slicer subject hierarchy
        """
        shNode = slicer.vtkMRMLSubjectHierarchyNode.GetSubjectHierarchyNode(slicer.mrmlScene)
        volumeSubjectHierarchyID = shNode.GetItemByDataNode(volNode)
        shNode.SetItemParent(volumeSubjectHierarchyID, studySubjectHierarchyID)

    def createSubjectHierarchyPatientAndStudy(self, subjectNameInSH, studyNameInSH):
        """
        """
        shNode = slicer.vtkMRMLSubjectHierarchyNode.GetSubjectHierarchyNode(slicer.mrmlScene)
        # set IDs. Note: these IDs are not specifying DICOM tags, but only the names that appear in the hierarchy tree
        patientItemID = shNode.CreateSubjectItem(shNode.GetSceneItemID(), subjectNameInSH)
        studyItemID = shNode.CreateStudyItem(patientItemID, studyNameInSH)
        return patientItemID, studyItemID

    def cropVolumeUsingROI(self, input_volume_node, roi_node, output_volume_node=None, 
            interpolation_mode='linear', fill_value=0, isotropic=True):
        """ Run Crop Volume using input ROI
        """
        cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
        cropVolumeNode.SetScene(slicer.mrmlScene)
        cropVolumeNode.SetName("MyCropVolumeParametersNode")
        cropVolumeNode.SetIsotropicResampling(isotropic)
        if interpolation_mode=='linear':
            interp_mode = cropVolumeNode.InterpolationLinear
        elif interpolation_mode=='nn':
            interp_mode = cropVolumeNode.InterpolationNearestNeighbor
        
        cropVolumeNode.SetInterpolationMode(interp_mode)
        
        cropVolumeNode.SetFillValue(fill_value)
        cropVolumeNode.SetROINodeID(roi_node.GetID())  # roi
        slicer.mrmlScene.AddNode(cropVolumeNode)
        if output_volume_node is None:
            output_volume_node = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLScalarVolumeNode', input_volume_node.GetName() + '_roiCropped')
        
        cropVolumeNode.SetInputVolumeNodeID(input_volume_node.GetID())  # input
        cropVolumeNode.SetOutputVolumeNodeID(output_volume_node.GetID())  # output
        slicer.modules.cropvolume.logic().Apply(cropVolumeNode)  # do the crop
        slicer.mrmlScene.RemoveNode(cropVolumeNode)
        return output_volume_node