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/*
//
// Copyright 2012-2014 SRI International
//
// This file is part of the Computational Morphometry Toolkit.
//
// http://www.nitrc.org/projects/cmtk/
//
// The Computational Morphometry Toolkit is free software: you can
// redistribute it and/or modify it under the terms of the GNU General Public
// License as published by the Free Software Foundation, either version 3 of
// the License, or (at your option) any later version.
//
// The Computational Morphometry Toolkit is distributed in the hope that it
// will be useful, but WITHOUT ANY WARRANTY; without even the implied
// warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License along
// with the Computational Morphometry Toolkit. If not, see
// <http://www.gnu.org/licenses/>.
//
// $Revision: 5436 $
//
// $LastChangedDate: 2018-12-10 19:01:20 -0800 (Mon, 10 Dec 2018) $
//
// $LastChangedBy: torstenrohlfing $
//
*/
#include "cmtkSphereDetectionNormalizedBipolarMatchedFilterFFT.h"
cmtk::SphereDetectionNormalizedBipolarMatchedFilterFFT::SphereDetectionNormalizedBipolarMatchedFilterFFT( const UniformVolume& image )
: m_NumberOfPixels( image.GetNumberOfPixels() ),
m_ImageDims( image.m_Dims ),
m_PixelSize( image.m_Delta ),
m_SphereRadius( 0 ),
m_MarginWidth( -1 ),
m_SumFilter( 0.0 ),
m_SumFilterMask( 0.0 )
{
this->m_ImageFT = static_cast<fftw_complex*>( fftw_malloc( sizeof( fftw_complex ) * this->m_NumberOfPixels ) );
this->m_ImageSquareFT = static_cast<fftw_complex*>( fftw_malloc( sizeof( fftw_complex ) * this->m_NumberOfPixels ) );
this->m_FilterFT = static_cast<fftw_complex*>( fftw_malloc( sizeof( fftw_complex ) * this->m_NumberOfPixels ) );
this->m_FilterMaskFT = static_cast<fftw_complex*>( fftw_malloc( sizeof( fftw_complex ) * this->m_NumberOfPixels ) );
this->m_FilterMaskFT2 = static_cast<fftw_complex*>( fftw_malloc( sizeof( fftw_complex ) * this->m_NumberOfPixels ) );
this->m_PlanFilter = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_FilterFT, this->m_FilterFT, FFTW_FORWARD, FFTW_ESTIMATE );
this->m_PlanFilterMask = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_FilterMaskFT, this->m_FilterMaskFT, FFTW_FORWARD, FFTW_ESTIMATE );
this->m_PlanBackward = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_FilterFT, this->m_FilterFT, FFTW_BACKWARD, FFTW_ESTIMATE );
this->m_PlanBackwardMask = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_FilterMaskFT, this->m_FilterMaskFT, FFTW_BACKWARD, FFTW_ESTIMATE );
this->m_PlanBackwardMask2 = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_FilterMaskFT2, this->m_FilterMaskFT2, FFTW_BACKWARD, FFTW_ESTIMATE );
// initialize image FT
fftw_plan plan_image = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_ImageFT, this->m_ImageFT, FFTW_FORWARD, FFTW_ESTIMATE );
fftw_plan plan_image_square = fftw_plan_dft_3d( this->m_ImageDims[2], this->m_ImageDims[1], this->m_ImageDims[0], this->m_ImageSquareFT, this->m_ImageSquareFT, FFTW_FORWARD, FFTW_ESTIMATE );
#pragma omp parallel for
for ( int n = 0; n < static_cast<int>( this->m_NumberOfPixels ); ++n )
{
this->m_ImageFT[n][0] = image.GetDataAt( n );
this->m_ImageFT[n][1] = 0;
this->m_ImageSquareFT[n][0] = this->m_ImageFT[n][0] * this->m_ImageFT[n][0];
this->m_ImageSquareFT[n][1] = 0;
}
fftw_execute( plan_image );
fftw_execute( plan_image_square );
fftw_destroy_plan( plan_image );
fftw_destroy_plan( plan_image_square );
}
cmtk::SphereDetectionNormalizedBipolarMatchedFilterFFT::~SphereDetectionNormalizedBipolarMatchedFilterFFT()
{
fftw_destroy_plan( this->m_PlanBackward );
fftw_destroy_plan( this->m_PlanBackwardMask );
fftw_destroy_plan( this->m_PlanBackwardMask2 );
fftw_destroy_plan( this->m_PlanFilter );
fftw_destroy_plan( this->m_PlanFilterMask );
fftw_free( this->m_FilterMaskFT2 );
fftw_free( this->m_FilterMaskFT );
fftw_free( this->m_FilterFT );
fftw_free( this->m_ImageFT );
}
cmtk::TypedArray::SmartPtr
cmtk::SphereDetectionNormalizedBipolarMatchedFilterFFT::GetFilteredImageData( const Types::Coordinate sphereRadius, const int marginWidth )
{
// check if the requested kernel parameters are the same we previously used.
if ( (sphereRadius == this->m_SphereRadius) && (marginWidth == this->m_MarginWidth ) )
return this->m_FilterResponse;
this->m_SphereRadius = sphereRadius;
this->m_MarginWidth = marginWidth;
memset( this->m_FilterFT, 0, sizeof( fftw_complex ) * this->m_NumberOfPixels );
memset( this->m_FilterMaskFT, 0, sizeof( fftw_complex ) * this->m_NumberOfPixels );
this->MakeFilter( sphereRadius, marginWidth );
const Types::DataItem denom2 = sqrt( this->m_SumFilterMask - (this->m_SumFilter*this->m_SumFilter) / this->m_SumFilterMask );
// compute filter kernel FT
fftw_execute( this->m_PlanFilter );
fftw_execute( this->m_PlanFilterMask );
// apply FT'ed filter to FT'ed image
#pragma omp parallel for
for ( int n = 0; n < static_cast<int>( this->m_NumberOfPixels ); ++n )
{
this->m_FilterMaskFT2[n][0] = this->m_FilterMaskFT[n][0];
this->m_FilterMaskFT2[n][1] = this->m_FilterMaskFT[n][1];
FFTW::MultiplyInPlace( this->m_FilterMaskFT[n], this->m_ImageFT[n] );
FFTW::MultiplyInPlace( this->m_FilterMaskFT2[n], this->m_ImageSquareFT[n] );
FFTW::MultiplyInPlace( this->m_FilterFT[n], this->m_ImageFT[n] );
}
// transform filtered spectral data back into space domain
fftw_execute( this->m_PlanBackward );
fftw_execute( this->m_PlanBackwardMask );
fftw_execute( this->m_PlanBackwardMask2 );
const double invNumberOfPixels = 1.0 / this->m_NumberOfPixels;
#pragma omp parallel for
for ( int n = 0; n < static_cast<int>( this->m_NumberOfPixels ); ++n )
{
for ( int c = 0; c < 2; ++c )
{
this->m_FilterMaskFT[n][c] *= invNumberOfPixels;
this->m_FilterMaskFT2[n][c] *= invNumberOfPixels;
this->m_FilterFT[n][c] *= invNumberOfPixels;
}
}
// return filter response data
if ( !this->m_FilterResponse )
this->m_FilterResponse = TypedArray::Create( cmtk::TYPE_ITEM, this->m_NumberOfPixels );
#pragma omp parallel for
for ( int n = 0; n < static_cast<int>( this->m_NumberOfPixels ); ++n )
{
const Types::DataItem num = FFTW::Magnitude( this->m_FilterFT[n] ) - (FFTW::Magnitude( this->m_FilterMaskFT[n] ) * this->m_SumFilter / this->m_SumFilterMask );
const Types::DataItem denom1 = sqrt( std::max<Types::DataItem>( 0, FFTW::Magnitude( this->m_FilterMaskFT2[n] ) - FFTW::SumOfSquares( this->m_FilterMaskFT[n] ) / this->m_SumFilterMask ) );
if ( (num == 0) || (denom1 ==0) )
this->m_FilterResponse->Set( 0, n );
else
this->m_FilterResponse->Set( num / (denom1*denom2), n );
}
return this->m_FilterResponse;
}
void
cmtk::SphereDetectionNormalizedBipolarMatchedFilterFFT::MakeFilter( const Types::Coordinate sphereRadius, const int marginWidth )
{
const int nRadius[3] = { 1 + marginWidth + static_cast<int>( sphereRadius / this->m_PixelSize[0] ),
1 + marginWidth + static_cast<int>( sphereRadius / this->m_PixelSize[1] ),
1 + marginWidth + static_cast<int>( sphereRadius / this->m_PixelSize[2] ) };
Types::DataItem sumFilter = 0, sumFilterMask = 0;
const Types::Coordinate sphereRadiusSq = MathUtil::Square( sphereRadius );
const Types::Coordinate outerRadiusSq = MathUtil::Square( sphereRadius+marginWidth );
// create a filter kernel for the sphere
#pragma omp parallel for reduction(+:sumFilter) reduction(+:sumFilterMask)
for ( int k = 0; k < nRadius[2]; ++k )
{
const Types::Coordinate dzSq = MathUtil::Square( k * this->m_PixelSize[2] );
for ( int j = 0; j < nRadius[1]; ++j )
{
const Types::Coordinate dyzSq = dzSq + MathUtil::Square( j * this->m_PixelSize[1] );
for ( int i = 0; i < nRadius[0]; ++i )
{
const Types::Coordinate distanceSq = dyzSq + MathUtil::Square( i * this->m_PixelSize[0] );
if ( distanceSq <= outerRadiusSq )
{
Types::DataItem value = 1;
if ( (distanceSq > sphereRadiusSq) )
{
value = -1;
}
for ( int kk = k; kk < this->m_ImageDims[2]; kk += (this->m_ImageDims[2]-1-2*k) )
for ( int jj = j; jj < this->m_ImageDims[1]; jj += (this->m_ImageDims[1]-1-2*j) )
for ( int ii = i; ii < this->m_ImageDims[0]; ii += (this->m_ImageDims[0]-1-2*i) )
{
const size_t ofs = ii+this->m_ImageDims[0] * (jj+this->m_ImageDims[1]*kk);
this->m_FilterFT[ofs][0] = value;
this->m_FilterMaskFT[ofs][0] = 1;
sumFilter += value;
sumFilterMask += 1;
}
}
}
}
}
this->m_SumFilter = sumFilter;
this->m_SumFilterMask = sumFilterMask;
}
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