#ifndef __bbSlicerRicianLMMSEImageFilter_h_INCLUDED__
#define __bbSlicerRicianLMMSEImageFilter_h_INCLUDED__

#include "bbSlicer_EXPORT.h"
#include "bbtkAtomicBlackBox.h"

#include <vector>
#include <cstdlib>
#include <dlfcn.h>
#include <sstream>
#include <fstream>
#include <iostream>

#include <ModuleDescriptionUtilities.h>
#include <ModuleDescriptionParser.h>
#include <ModuleParameterGroup.h>
#include <ModuleDescription.h>
#include <ModuleParameter.h>

#include "CreationTool.h"

namespace bbSlicer {

    class bbSlicer_EXPORT RicianLMMSEImageFilter
    :
    public bbtk::AtomicBlackBox {
        BBTK_BLACK_BOX_INTERFACE ( RicianLMMSEImageFilter , bbtk::AtomicBlackBox ) ;

        // GENERATED ARGS        
        
BBTK_DECLARE_INPUT ( iIterations , int );
BBTK_DECLARE_INPUT ( iRadiusEstimation , std::vector<int> );
BBTK_DECLARE_INPUT ( iRadiusFiltering , std::vector<int> );
BBTK_DECLARE_INPUT ( iMinimumNumberOfUsedVoxelsF , int );
BBTK_DECLARE_INPUT ( iMinimumNumberOfUsedVoxelsE , int );
BBTK_DECLARE_INPUT ( dMinSTD , int );
BBTK_DECLARE_INPUT ( dMaxSTD , int );
BBTK_DECLARE_INPUT ( dResFact , double );
BBTK_DECLARE_INPUT ( bUseAbsoluteValue , bool );
BBTK_DECLARE_INPUT ( inputVolume , std::string );
BBTK_DECLARE_INPUT ( outputVolume , std::string );

        // EO GENERATED ARGS

        BBTK_PROCESS ( Process ) ;
        void Process ( ) ;
    private:
        void execute ( std::string lib , int _argc , char * _argv[] ) ;
    } ;

    BBTK_BEGIN_DESCRIBE_BLACK_BOX ( RicianLMMSEImageFilter , bbtk::AtomicBlackBox ) ;
    BBTK_NAME ( "RicianLMMSEImageFilter" ) ;
    BBTK_AUTHOR ( "Antonio Tristan Vega, Santiago Aja Fernandez and Marc Niethammer. Partially founded by grant number TEC2007-67073/TCM from the Comision Interministerial de Ciencia y Tecnologia Spain." ) ;
    BBTK_DESCRIPTION ( "This module reduces noise or unwanted detail on a set of diffusion weighted images. For this, it filters the image in the mean squared error sense using a Rician noise model. Images corresponding to each gradient direction, including baseline, are processed individually. The noise parameter is automatically estimated noise estimation improved but slower.Note that this is a general purpose filter for MRi images. The module jointLMMSE has been specifically designed for DWI volumes and shows a better performance, so its use is recommended instead.A complete description of the algorithm in this module can be found in:S. Aja-Fernandez, M. Niethammer, M. Kubicki, M. Shenton, and C.-F. Westin. Restoration of DWI data using a Rician LMMSE estimator. IEEE Transactions on Medical Imaging, 2710: pp. 1389-1403, Oct. 2008." ) ;
    BBTK_CATEGORY ( "Diffusion.Denoising" ) ;

    // GENERATED DESCRPTION
    
BBTK_INPUT(RicianLMMSEImageFilter , iIterations , "iIterations" , int, "");
BBTK_INPUT(RicianLMMSEImageFilter , iRadiusEstimation , "iRadiusEstimation" , std::vector<int>, "");
BBTK_INPUT(RicianLMMSEImageFilter , iRadiusFiltering , "iRadiusFiltering" , std::vector<int>, "");
BBTK_INPUT(RicianLMMSEImageFilter , iMinimumNumberOfUsedVoxelsF , "iMinimumNumberOfUsedVoxelsF" , int, "");
BBTK_INPUT(RicianLMMSEImageFilter , iMinimumNumberOfUsedVoxelsE , "iMinimumNumberOfUsedVoxelsE" , int, "");
BBTK_INPUT(RicianLMMSEImageFilter , dMinSTD , "dMinSTD" , int, "");
BBTK_INPUT(RicianLMMSEImageFilter , dMaxSTD , "dMaxSTD" , int, "");
BBTK_INPUT(RicianLMMSEImageFilter , dResFact , "dResFact" , double, "");
BBTK_INPUT(RicianLMMSEImageFilter , bUseAbsoluteValue , "bUseAbsoluteValue" , bool, "");
BBTK_INPUT(RicianLMMSEImageFilter , inputVolume , "inputVolume" , std::string, "");
BBTK_INPUT(RicianLMMSEImageFilter , outputVolume , "outputVolume" , std::string, "");

    // EO GENERATED DESCRIPTION

    BBTK_END_DESCRIBE_BLACK_BOX ( RicianLMMSEImageFilter ) ;
}

#endif // __bbSlicerRicianLMMSEImageFilter_h_INCLUDED__