mitkGraphCutImageFilter.h

/*=========================================================================

  Program:   3DMed
  Date:      $Date: 2014-02-25 18:30:00 +0800 $
  Version:   $Version: 4.6.0 $
  Copyright: MIPG, Institute of Automation, Chinese Academy of Sciences

=========================================================================*/


/* mitkGraphCutImageFilter - A class that implement graph cut segmentation method integrated with 
  three modeling methods: K-Means, Gaussian Mixture Model and Support Vector Machines.
*/
//=========================================================================
#ifndef __mitkGraphCutImageFilter_h
#define __mitkGraphCutImageFilter_h

#include "mitkSegmentationIncludes.h"
#include "mitkVolumeToVolumeFilter.h"
#include "mitkICVolume.h"

class Graph;
typedef void *  Graph_node_id;

class MITK_SEGMENTATION_API mitkGraphCutImageFilter :public mitkVolumeToVolumeFilter
{
public:
    
     MITK_TYPE(mitkGraphCutImageFilter,mitkVolumeToVolumeFilter)

    mitkGraphCutImageFilter();
    virtual ~mitkGraphCutImageFilter();

    virtual void PrintSelf(ostream& os){};

     typedef enum{
         KMC=0,              // K-Means method
         GMM=1,             // Gaussian Mixture Model method
    }valueMethod;
     
     typedef struct
     {
         double  weight;    // weight of model of GMM
         double  mu;         // mean of model of GMM
         double  sigma;     // variance of model of GMM
     }GMM_Para;
         
     typedef struct 
     {
         int x;                   
         int y;
         double grayValue;
     }PointIndex;           //coordinate and intensity of a point
     
     typedef vector<double> GrayArr;
     typedef vector<PointIndex> PointQueue;
     typedef vector<GMM_Para> paraArr;
     
     void  Initialize();

     void SetLabel(mitkICVolume* label)           {this->m_Label =label;}
     void SetOrder(int order)                         {this->m_Order=order;}
     void SetBeta(int beta)                             {this->m_Beta=beta;}
     void SetCurrentSlice(int cur)                    {this->m_CurrentSlice=cur;}
     void SetMethod(valueMethod method)   {m_Method = method;}   
     mitkICVolume* GetLabel()   {return this->m_Label;}

protected:

    // calculate the KMC parameters
     bool   KMeansCluster(PointQueue seedQueue, int numCluster, GrayArr& meanCluster); 

    // calculate the GMM parameters by EM algorithm
     bool   GaussianMixtureModel(PointQueue seedQueue, int numModel, paraArr& GMMPara, float delt, int ITER_MAX );

   // calculate the probability for a component of  GMM
    double G_Probability(double grayValue, GMM_Para para);

    // copy GMM model parameters
     bool   CopyPara( paraArr& dstPara, paraArr srcPara);     

     // initialize GMM model parameters
     void   InitGMMPara (int  order);
    
     // calculate the probability of a given sample using  GMM
     double Likelihood( paraArr GMMPara, PointQueue pointArr);
  
     template <typename T>    bool SetSeedPoint(mitkVolume * label, T *pInData);
     template <typename T>      bool  GraphCut(T* pInData, valueMethod method, double beta);
     template <typename T>      bool _tExecute(T* pInData, unsigned char* pOutData);
   
     virtual bool Execute();

private:
    mitkGraphCutImageFilter(const mitkGraphCutImageFilter&){};
    void operator=(const mitkGraphCutImageFilter&){};

private:

    int  m_Width, m_Height, m_CurrentSlice;    // width, height and currentSlice of the volume
    int m_Order;                                            // number of the model
    double m_Beta;                                        // tolerance
    valueMethod m_Method;                          // modeling method
    
    PointQueue seedQueueF, seedQueueB;    // seed points for foreground and background

   /*label for foreground or background    
      1 ----foreground  
      0 ----background   
     -1----unknown*/
    mitkICVolume *m_Label;
   // mitkICVolume *m_LabelUpdate;

    Graph *m_Graph;
    Graph_node_id **m_nodes;
    
    GrayArr m_meanCluster_f;  // KMC parameters for foreground
    GrayArr m_meanCluster_b;  // KMC parameters for background
    
    paraArr m_GMMPara_f;      // GMM parameters for foreground
    paraArr m_GMMPara_b;      // GMM parameters for background

};


#endif

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