cxConnectedThresholdImageFilter.cpp

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/*=========================================================================
This file is part of CustusX, an Image Guided Therapy Application.
                 
Copyright (c) SINTEF Department of Medical Technology.
All rights reserved.
                 
CustusX is released under a BSD 3-Clause license.
                 
See Lisence.txt (https://github.com/SINTEFMedtek/CustusX/blob/master/License.txt) for details.
=========================================================================*/

#include "cxConnectedThresholdImageFilter.h"

#include "itkConnectedThresholdImageFilter.h"
#include "cxLogger.h"
#include "cxTypeConversions.h"
#include "cxAlgorithmHelpers.h"
#include "cxRegistrationTransform.h"
#include "cxImage.h"
#include "cxPatientModelService.h"
#include "cxVolumeHelpers.h"
#include "cxVisServices.h"

namespace cx
{

ConnectedThresholdImageFilter::ConnectedThresholdImageFilter(VisServicesPtr services) :
        ThreadedTimedAlgorithm<vtkImageDataPtr>("segmenting", 10),
        mServices(services)
{
}

ConnectedThresholdImageFilter::~ConnectedThresholdImageFilter()
{
}

void ConnectedThresholdImageFilter::setInput(ImagePtr image, QString outputBasePath, float lowerThreshold, float upperThreshold, int replaceValue, itkImageType::IndexType seed)
{
        mInput = image;
        mOutputBasePath = outputBasePath;

        mLowerThreshold = lowerThreshold;
        mUpperTheshold = upperThreshold;
        mReplaceValue = replaceValue;
        mSeed = seed;

        this->generate();
}

ImagePtr ConnectedThresholdImageFilter::getOutput()
{
        return mOutput;
}

void ConnectedThresholdImageFilter::postProcessingSlot()
{
        //get the result from the thread
        vtkImageDataPtr rawResult = this->getResult();

        if(!rawResult)
        {
                reportError("Segmentation failed.");
                return;
        }

        //generate a new name and unique id for the newly created object
        QString uid = mInput->getUid() + "_seg%1";
        QString name = mInput->getName()+" seg%1";

        //create a Image
        ImagePtr result = createDerivedImage(mServices->patient(),
                                                                                 uid, name,
                                                                                 rawResult, mInput);
        mOutput->resetTransferFunctions();

        mServices->patient()->insertData(mOutput);

        //let the user know you are finished
        reportSuccess("Done segmenting: \"" + mOutput->getName()+"\"");

        //let the system know you're finished
        //  emit finished();
}

vtkImageDataPtr ConnectedThresholdImageFilter::calculate()
{
        //Connected Thresholding

        //Documentation:
        // http://www.na-mic.org/svn/Slicer3-lib-mirrors/trunk/Insight/Examples/Segmentation/ConnectedThresholdImageFilter.cxx

        //  The ConnectedThresholdImageFilter has two main parameters to be
        //  defined. They are the lower and upper thresholds of the interval in
        //  which intensity values should fall in order to be included in the
        //  region. Setting these two values too close will not allow enough
        //  flexibility for the region to grow. Setting them too far apart will
        //  result in a region that engulfs the image.

        //  The output of this filter is a binary image with zero-value pixels
        //  everywhere except on the extracted region. The intensity value set
        //  inside the region is selected with the method SetReplaceValue()

        //  The initialization of the algorithm requires the user to provide a seed
        //  point. It is convenient to select this point to be placed in a
        //  typical region of the anatomical structure to be segmented. The
        //  seed is passed in the form of a IndexType to the SetSeed()
        //  method.

        //  Another option for segmenting regions is to take advantage of the
        //  functionality provided by the ConnectedThresholdImageFilter for
        //  managing multiple seeds. The seeds can be passed one by one to the
        //  filter using the AddSeed() method. You could imagine a user
        //  interface in which an operator clicks on multiple points of the object
        //  to be segmented and each selected point is passed as a seed to this
        //  filter.

        itkImageType::ConstPointer itkImage = AlgorithmHelper::getITKfromSSCImage(mInput);

        typedef itk::ConnectedThresholdImageFilter<itkImageType, itkImageType> thresholdFilterType;
        thresholdFilterType::Pointer thresholdFilter = thresholdFilterType::New();
        thresholdFilter->SetInput(itkImage);

        //set thresholds
        thresholdFilter->SetLower(mLowerThreshold);
        thresholdFilter->SetUpper(mUpperTheshold);
        thresholdFilter->SetReplaceValue(mReplaceValue);

        //set seeds
        thresholdFilter->SetSeed(mSeed);

        //calculate
        try
        {
                thresholdFilter->Update();
        }
        catch( itk::ExceptionObject & excep )
        {
                reportError("Error when setting seed for Connected Threshold Image Filter:");
                reportError(qstring_cast(excep.GetDescription()));
        }

        itkImage = thresholdFilter->GetOutput();

        //Convert ITK to VTK
        itkToVtkFilterType::Pointer itkToVtkFilter = itkToVtkFilterType::New();
        itkToVtkFilter->SetInput(itkImage);
        itkToVtkFilter->Update();

        vtkImageDataPtr rawResult = vtkImageDataPtr::New();
        rawResult->DeepCopy(itkToVtkFilter->GetOutput());
        // TODO: possible memory problem here - check debug mem system of itk/vtk

        return rawResult;
}

}