本文整理汇总了C++中image::Pointer::GetTimeSteps方法的典型用法代码示例。如果您正苦于以下问题：C++ Pointer::GetTimeSteps方法的具体用法？C++ Pointer::GetTimeSteps怎么用？C++ Pointer::GetTimeSteps使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类image::Pointer的用法示例。
在下文中一共展示了Pointer::GetTimeSteps方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: GetTargetSegmentationNode
void mitk::BinaryThresholdULTool::CreateNewSegmentationFromThreshold(DataNode* node)
{
if (node)
{
Image::Pointer feedBackImage = dynamic_cast<Image*>( m_ThresholdFeedbackNode->GetData() );
if (feedBackImage.IsNotNull())
{
// create a new image of the same dimensions and smallest possible pixel type
DataNode::Pointer emptySegmentation = GetTargetSegmentationNode();
if (emptySegmentation)
{
// actually perform a thresholding and ask for an organ type
for (unsigned int timeStep = 0; timeStep < feedBackImage->GetTimeSteps(); ++timeStep)
{
try
{
ImageTimeSelector::Pointer timeSelector = ImageTimeSelector::New();
timeSelector->SetInput( feedBackImage );
timeSelector->SetTimeNr( timeStep );
timeSelector->UpdateLargestPossibleRegion();
Image::Pointer feedBackImage3D = timeSelector->GetOutput();
if (feedBackImage3D->GetDimension() == 2)
{
AccessFixedDimensionByItk_2( feedBackImage3D, ITKSetVolume, 2, dynamic_cast<Image*>(emptySegmentation->GetData()), timeStep );
}
else
{
AccessFixedDimensionByItk_2( feedBackImage3D, ITKSetVolume, 3, dynamic_cast<Image*>(emptySegmentation->GetData()), timeStep );
}
}
catch(...)
{
Tool::ErrorMessage("Error accessing single time steps of the original image. Cannot create segmentation.");
}
}
//since we are maybe working on a smaller image, pad it to the size of the original image
if (m_OriginalImageNode.GetPointer() != m_NodeForThresholding.GetPointer())
{
mitk::PadImageFilter::Pointer padFilter = mitk::PadImageFilter::New();
padFilter->SetInput(0, dynamic_cast<mitk::Image*> (emptySegmentation->GetData()));
padFilter->SetInput(1, dynamic_cast<mitk::Image*> (m_OriginalImageNode->GetData()));
padFilter->SetBinaryFilter(true);
padFilter->SetUpperThreshold(1);
padFilter->SetLowerThreshold(1);
padFilter->Update();
emptySegmentation->SetData(padFilter->GetOutput());
}
m_ToolManager->SetWorkingData( emptySegmentation );
m_ToolManager->GetWorkingData(0)->Modified();
}
}
}
}示例2: catch
void mitk::BinaryThresholdULTool::CreateNewSegmentationFromThreshold(DataNode* node, const std::string& organName, const Color& color)
{
if (node)
{
Image::Pointer image = dynamic_cast<Image*>( m_NodeForThresholding->GetData() );
if (image.IsNotNull())
{
// create a new image of the same dimensions and smallest possible pixel type
DataNode::Pointer emptySegmentation = Tool::CreateEmptySegmentationNode( image, organName, color );
if (emptySegmentation)
{
// actually perform a thresholding and ask for an organ type
for (unsigned int timeStep = 0; timeStep < image->GetTimeSteps(); ++timeStep)
{
try
{
ImageTimeSelector::Pointer timeSelector = ImageTimeSelector::New();
timeSelector->SetInput( image );
timeSelector->SetTimeNr( timeStep );
timeSelector->UpdateLargestPossibleRegion();
Image::Pointer image3D = timeSelector->GetOutput();
AccessFixedDimensionByItk_2( image3D, ITKThresholding, 3, dynamic_cast<Image*>(emptySegmentation->GetData()), timeStep );
}
catch(...)
{
Tool::ErrorMessage("Error accessing single time steps of the original image. Cannot create segmentation.");
}
}
//since we are maybe working on a smaller image, pad it to the size of the original image
if (m_OriginalImageNode.GetPointer() != m_NodeForThresholding.GetPointer())
{
mitk::PadImageFilter::Pointer padFilter = mitk::PadImageFilter::New();
padFilter->SetInput(0, dynamic_cast<mitk::Image*> (emptySegmentation->GetData()));
padFilter->SetInput(1, dynamic_cast<mitk::Image*> (m_OriginalImageNode->GetData()));
padFilter->SetBinaryFilter(true);
padFilter->SetUpperThreshold(1);
padFilter->SetLowerThreshold(1);
padFilter->Update();
emptySegmentation->SetData(padFilter->GetOutput());
}
if (DataStorage* ds = m_ToolManager->GetDataStorage())
{
ds->Add( emptySegmentation, m_OriginalImageNode );
}
m_ToolManager->SetWorkingData( emptySegmentation );
}
}
}
}