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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkParallelSparseFieldLevelSetImageFilter_hxx
#define itkParallelSparseFieldLevelSetImageFilter_hxx
#include "itkParallelSparseFieldLevelSetImageFilter.h"
#include "itkZeroCrossingImageFilter.h"
#include "itkShiftScaleImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkNumericTraits.h"
#include "itkNeighborhoodAlgorithm.h"
#include <iostream>
#include <fstream>
#include "itkMath.h"
namespace itk
{
template< typename TNeighborhoodType >
ParallelSparseFieldCityBlockNeighborList< TNeighborhoodType >
::ParallelSparseFieldCityBlockNeighborList()
{
typedef typename NeighborhoodType::ImageType ImageType;
typename ImageType::Pointer dummy_image = ImageType::New();
unsigned int i, nCenter;
int d;
OffsetType zero_offset;
for ( i = 0; i < Dimension; ++i )
{
m_Radius[i] = 1;
zero_offset[i] = 0;
}
NeighborhoodType it( m_Radius, dummy_image, dummy_image->GetRequestedRegion() );
nCenter = it.Size() / 2;
m_Size = 2 * Dimension;
m_ArrayIndex.reserve(m_Size);
m_NeighborhoodOffset.reserve(m_Size);
for ( i = 0; i < m_Size; ++i )
{
m_NeighborhoodOffset.push_back(zero_offset);
}
for ( d = Dimension - 1, i = 0; d >= 0; --d, ++i )
{
m_ArrayIndex.push_back( nCenter - it.GetStride(d) );
m_NeighborhoodOffset[i][d] = -1;
}
for ( d = 0; d < static_cast< int >( Dimension ); ++d, ++i )
{
m_ArrayIndex.push_back( nCenter + it.GetStride(d) );
m_NeighborhoodOffset[i][d] = 1;
}
for ( i = 0; i < Dimension; ++i )
{
m_StrideTable[i] = it.GetStride(i);
}
}
template< typename TNeighborhoodType >
void
ParallelSparseFieldCityBlockNeighborList< TNeighborhoodType >
::Print(std::ostream & os) const
{
os << "ParallelSparseFieldCityBlockNeighborList: " << std::endl;
for ( unsigned i = 0; i < this->GetSize(); ++i )
{
os << "m_ArrayIndex[" << i << "]: " << m_ArrayIndex[i] << std::endl
<< "m_NeighborhoodOffset[" << i << "]: " << m_NeighborhoodOffset[i] << std::endl;
}
}
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::ValueType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_ValueOne = NumericTraits< typename ParallelSparseFieldLevelSetImageFilter< TInputImage,
TOutputImage >::ValueType >::OneValue();
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::ValueType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_ValueZero = NumericTraits< typename ParallelSparseFieldLevelSetImageFilter< TInputImage,
TOutputImage >::ValueType >::ZeroValue();
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::StatusType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_StatusNull = NumericTraits< typename ParallelSparseFieldLevelSetImageFilter< TInputImage,
TOutputImage >::StatusType >::
NonpositiveMin();
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::StatusType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_StatusChanging = -1;
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::StatusType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_StatusActiveChangingUp = -2;
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::StatusType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_StatusActiveChangingDown = -3;
template< typename TInputImage, typename TOutputImage >
typename ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::StatusType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::m_StatusBoundaryPixel = -4;
template< typename TInputImage, typename TOutputImage >
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ParallelSparseFieldLevelSetImageFilter() :
m_ConstantGradientValue(1.0),
m_NumberOfLayers(ImageDimension),
m_IsoSurfaceValue(m_ValueZero),
m_NumOfThreads(0),
m_SplitAxis(0),
m_ZSize(0),
m_BoundaryChanged(false),
m_Boundary(ITK_NULLPTR),
m_GlobalZHistogram(ITK_NULLPTR),
m_MapZToThreadNumber(ITK_NULLPTR),
m_ZCumulativeFrequency(ITK_NULLPTR),
m_Data(ITK_NULLPTR),
m_Stop(false),
m_InterpolateSurfaceLocation(true),
m_BoundsCheckingActive(false)
{
this->SetRMSChange( static_cast< double >( m_ValueOne ) );
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::GenerateData()
{
if ( !this->m_IsInitialized )
{
// Clean up any memory from any aborted previous filter executions.
this->DeallocateData();
// Allocate the output image
m_OutputImage = this->GetOutput();
m_OutputImage->SetBufferedRegion( m_OutputImage->GetRequestedRegion() );
m_OutputImage->Allocate();
// Copy the input image to the output image. Algorithms will operate
// directly on the output image
this->CopyInputToOutput();
// Perform any other necessary pre-iteration initialization.
this->Initialize();
this->SetElapsedIterations(0);
//NOTE: Cannot set state to initialized yet since more initialization is
//done in the Iterate method.
}
// Evolve the surface
this->Iterate();
// Clean up
if ( this->GetManualReinitialization() == false )
{
this->DeallocateData();
// Reset the state once execution is completed
this->m_IsInitialized = false;
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::CopyInputToOutput()
{
// This method is the first step in initializing the level-set image, which
// is also the output of the filter. The input is passed through a
// zero crossing filter, which produces zero's at pixels closest to the zero
// level set and one's elsewhere. The actual zero level set values will be
// adjusted in the Initialize() step to more accurately represent the
// position of the zero level set.
// First need to subtract the iso-surface value from the input image.
typedef ShiftScaleImageFilter< InputImageType, OutputImageType > ShiftScaleFilterType;
typename ShiftScaleFilterType::Pointer shiftScaleFilter = ShiftScaleFilterType::New();
shiftScaleFilter->SetInput( this->GetInput() );
shiftScaleFilter->SetShift(-m_IsoSurfaceValue);
// keep a handle to the shifted output
m_ShiftedImage = shiftScaleFilter->GetOutput();
typename ZeroCrossingImageFilter< OutputImageType, OutputImageType >::Pointer
zeroCrossingFilter = ZeroCrossingImageFilter< OutputImageType, OutputImageType >::New();
zeroCrossingFilter->SetInput(m_ShiftedImage);
zeroCrossingFilter->GraftOutput(m_OutputImage);
zeroCrossingFilter->SetBackgroundValue(m_ValueOne);
zeroCrossingFilter->SetForegroundValue(m_ValueZero);
zeroCrossingFilter->SetNumberOfThreads(1);
zeroCrossingFilter->Update();
// Here the output is the result of zerocrossings
this->GraftOutput( zeroCrossingFilter->GetOutput() );
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::Initialize()
{
unsigned int i;
// A node pool used during initialization of the level set.
m_LayerNodeStore = LayerNodeStorageType::New();
m_LayerNodeStore->SetGrowthStrategyToExponential();
// Allocate the status image.
m_StatusImage = StatusImageType::New();
m_StatusImage->SetRegions( m_OutputImage->GetRequestedRegion() );
m_StatusImage->Allocate();
// Initialize the status image to contain all m_StatusNull values.
ImageRegionIterator< StatusImageType > statusIt( m_StatusImage,
m_StatusImage->GetRequestedRegion() );
for ( statusIt.GoToBegin(); !statusIt.IsAtEnd(); ++statusIt )
{
statusIt.Set(m_StatusNull);
}
// Initialize the boundary pixels in the status images to
// m_StatusBoundaryPixel values. Uses the face calculator to find all of the
// region faces.
typedef NeighborhoodAlgorithm::ImageBoundaryFacesCalculator< StatusImageType >
BFCType;
BFCType faceCalculator;
typename BFCType::FaceListType faceList;
typename BFCType::SizeType sz;
typename BFCType::FaceListType::iterator fit;
sz.Fill(1);
faceList = faceCalculator(m_StatusImage, m_StatusImage->GetRequestedRegion(),
sz);
fit = faceList.begin();
for ( ++fit; fit != faceList.end(); ++fit ) // skip the first (nonboundary)
// region
{
statusIt = ImageRegionIterator< StatusImageType >(m_StatusImage, *fit);
for ( statusIt.GoToBegin(); !statusIt.IsAtEnd(); ++statusIt )
{
statusIt.Set(m_StatusBoundaryPixel);
}
}
// Allocate the layers of the sparse field.
m_Layers.reserve(2 * m_NumberOfLayers + 1);
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; ++i )
{
m_Layers.push_back( LayerType::New() );
}
// always the "Z" dimension
m_SplitAxis = m_OutputImage->GetImageDimension() - 1;
if ( m_OutputImage->GetImageDimension() < 1 )
{
// cannot split
itkDebugMacro ("Unable to choose an axis for workload distribution among threads");
return;
}
typename OutputImageType::SizeType requestedRegionSize =
m_OutputImage->GetRequestedRegion().GetSize();
m_ZSize = requestedRegionSize[m_SplitAxis];
// Histogram of number of pixels in each Z plane for the entire 3D volume
m_GlobalZHistogram = new int[m_ZSize];
for ( i = 0; i < m_ZSize; i++ )
{
m_GlobalZHistogram[i] = 0;
}
// Construct the active layer and initialize the first layers inside and
// outside of the active layer
this->ConstructActiveLayer();
// Construct the rest of the non active set layers using the first two
// layers. Inside layers are odd numbers, outside layers are even numbers.
for ( i = 1; i < m_Layers.size() - 2; ++i )
{
this->ConstructLayer(i, i + 2);
}
// Set the values in the output image for the active layer.
this->InitializeActiveLayerValues();
// Initialize layer values using the active layer as seeds.
this->PropagateAllLayerValues();
// Initialize pixels inside and outside the sparse field layers to positive
// and negative values, respectively. This is not necessary for the
// calculations, but is useful for presenting a more intuitive output to the
// filter. See PostProcessOutput method for more information.
this->InitializeBackgroundPixels();
m_NumOfThreads = this->GetNumberOfThreads();
// Cumulative frequency of number of pixels in each Z plane for the entire 3D
// volume
m_ZCumulativeFrequency = new int[m_ZSize];
for ( i = 0; i < m_ZSize; i++ )
{
m_ZCumulativeFrequency[i] = 0;
}
// The mapping from a z-value to the thread in whose region the z-value lies
m_MapZToThreadNumber = new unsigned int[m_ZSize];
for ( i = 0; i < m_ZSize; i++ )
{
m_MapZToThreadNumber[i] = 0;
}
// The boundaries defining thread regions
m_Boundary = new unsigned int[m_NumOfThreads];
for ( i = 0; i < m_NumOfThreads; i++ )
{
m_Boundary[i] = 0;
}
// A boolean variable stating if the boundaries had been changed during
// CheckLoadBalance()
m_BoundaryChanged = false;
// A global barrier for all threads.
m_Barrier = Barrier::New();
m_Barrier->Initialize(m_NumOfThreads);
// Allocate data for each thread.
m_Data = new ThreadData[m_NumOfThreads];
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ConstructActiveLayer()
{
// We find the active layer by searching for 0's in the zero crossing image
// (output image). The first inside and outside layers are also constructed
// by searching the neighbors of the active layer in the (shifted) input
// image.
// Negative neighbors not in the active set are assigned to the inside,
// positive neighbors are assigned to the outside.
NeighborhoodIterator< OutputImageType > shiftedIt( m_NeighborList.GetRadius(),
m_ShiftedImage, m_OutputImage->GetRequestedRegion() );
NeighborhoodIterator< OutputImageType > outputIt ( m_NeighborList.GetRadius(),
m_OutputImage, m_OutputImage->GetRequestedRegion() );
NeighborhoodIterator< StatusImageType > statusIt ( m_NeighborList.GetRadius(),
m_StatusImage, m_OutputImage->GetRequestedRegion() );
IndexType center_index, offset_index;
LayerNodeType *node;
bool bounds_status = true;
ValueType value;
StatusType layer_number;
typename OutputImageType::SizeType regionSize =
m_OutputImage->GetRequestedRegion().GetSize();
typename OutputImageType::IndexType startIndex =
m_OutputImage->GetRequestedRegion().GetIndex();
typedef IndexValueType StartIndexValueType;
for ( outputIt.GoToBegin(); !outputIt.IsAtEnd(); ++outputIt )
{
bounds_status = true;
if ( Math::ExactlyEquals(outputIt.GetCenterPixel(), m_ValueZero) )
{
// Grab the neighborhood in the status image.
center_index = outputIt.GetIndex();
statusIt.SetLocation(center_index);
for ( unsigned int j = 0; j < ImageDimension; j++ )
{
if ( ( center_index[j] ) <= ( startIndex[j] )
|| ( center_index[j] ) >= startIndex[j]
+ static_cast< StartIndexValueType >( regionSize[j] - 1 ) )
{
bounds_status = false;
break;
}
}
if ( bounds_status == true )
{
// Here record the hisgram information
m_GlobalZHistogram[center_index[m_SplitAxis]]++;
// Borrow a node from the store and set its value.
node = m_LayerNodeStore->Borrow();
node->m_Index = center_index;
// Add the node to the active list and set the status in the status
// image.
m_Layers[0]->PushFront(node);
statusIt.SetCenterPixel(0);
// Grab the neighborhood in the image of shifted input values.
shiftedIt.SetLocation(center_index);
// Search the neighborhood pixels for first inside & outside layer
// members. Construct these lists and set status list values.
for ( unsigned int i = 0; i < m_NeighborList.GetSize(); ++i )
{
offset_index = center_index + m_NeighborList.GetNeighborhoodOffset(i);
if ( Math::NotExactlyEquals(outputIt.GetPixel( m_NeighborList.GetArrayIndex(i) ), m_ValueZero)
&& statusIt.GetPixel( m_NeighborList.GetArrayIndex(i) ) == m_StatusNull )
{
value = shiftedIt.GetPixel( m_NeighborList.GetArrayIndex(i) );
if ( value < m_ValueZero ) // Assign to first outside layer.
{
layer_number = 1;
}
else // Assign to first inside layer
{
layer_number = 2;
}
statusIt.SetPixel(m_NeighborList.GetArrayIndex(i), layer_number, bounds_status);
if ( bounds_status == true ) // In bounds
{
node = m_LayerNodeStore->Borrow();
node->m_Index = offset_index;
m_Layers[layer_number]->PushFront(node);
} // else do nothing.
}
}
}
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ConstructLayer(const StatusType& from, const StatusType& to)
{
LayerNodeType *node;
bool boundary_status;
typename LayerType::ConstIterator fromIt;
NeighborhoodIterator< StatusImageType > statusIt( m_NeighborList.GetRadius(), m_StatusImage,
m_OutputImage->GetRequestedRegion() );
// For all indices in the "from" layer...
for ( fromIt = m_Layers[from]->Begin(); fromIt != m_Layers[from]->End(); ++fromIt )
{
// Search the neighborhood of this index in the status image for
// unassigned indices. Push those indices onto the "to" layer and
// assign them values in the status image. Status pixels outside the
// boundary will be ignored.
statusIt.SetLocation(fromIt->m_Index);
for ( unsigned int i = 0; i < m_NeighborList.GetSize(); ++i )
{
if ( statusIt.GetPixel( m_NeighborList.GetArrayIndex(i) ) == m_StatusNull )
{
statusIt.SetPixel(m_NeighborList.GetArrayIndex(i), to, boundary_status);
if ( boundary_status == true ) // in bounds
{
node = m_LayerNodeStore->Borrow();
node->m_Index = statusIt.GetIndex() + m_NeighborList.GetNeighborhoodOffset(i);
m_Layers[to]->PushFront(node);
}
}
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::InitializeActiveLayerValues()
{
const ValueType CHANGE_FACTOR = m_ConstantGradientValue / 2.0;
ValueType MIN_NORM = 1.0e-6;
if ( this->GetUseImageSpacing() )
{
SpacePrecisionType minSpacing = NumericTraits< SpacePrecisionType >::max();
for ( unsigned int i = 0; i < ImageDimension; i++ )
{
minSpacing = std::min(minSpacing, this->GetInput()->GetSpacing()[i]);
}
MIN_NORM *= minSpacing;
}
typename LayerType::ConstIterator activeIt;
ConstNeighborhoodIterator< OutputImageType > shiftedIt ( m_NeighborList.GetRadius(), m_ShiftedImage,
m_OutputImage->GetRequestedRegion() );
unsigned int center = shiftedIt.Size() / 2;
unsigned int stride;
const NeighborhoodScalesType neighborhoodScales = this->GetDifferenceFunction()->ComputeNeighborhoodScales();
ValueType dx_forward, dx_backward, length, distance;
// For all indices in the active layer...
for ( activeIt = m_Layers[0]->Begin(); activeIt != m_Layers[0]->End(); ++activeIt )
{
// Interpolate on the (shifted) input image values at this index to
// assign an active layer value in the output image.
shiftedIt.SetLocation(activeIt->m_Index);
length = m_ValueZero;
for ( unsigned int i = 0; i < static_cast< unsigned int >( ImageDimension ); ++i )
{
stride = shiftedIt.GetStride(i);
dx_forward = ( shiftedIt.GetPixel(center + stride) - shiftedIt.GetCenterPixel() ) * neighborhoodScales[i];
dx_backward =
( shiftedIt.GetCenterPixel() - shiftedIt.GetPixel(center - stride) ) * neighborhoodScales[i];
if ( itk::Math::abs(dx_forward) > itk::Math::abs(dx_backward) )
{
length += dx_forward * dx_forward;
}
else
{
length += dx_backward * dx_backward;
}
}
length = std::sqrt(length) + MIN_NORM;
distance = shiftedIt.GetCenterPixel() / length;
m_OutputImage->SetPixel( activeIt->m_Index,
std::min(std::max(-CHANGE_FACTOR, distance), CHANGE_FACTOR) );
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::PropagateAllLayerValues()
{
// Update values in the first inside and first outside layers using the
// active layer as a seed. Inside layers are odd numbers, outside layers are
// even numbers.
this->PropagateLayerValues (0, 1, 3, 1); // first inside
this->PropagateLayerValues (0, 2, 4, 0); // first outside
// Update the rest of the layers.
for ( unsigned int i = 1; i < m_Layers.size() - 2; ++i )
{
this->PropagateLayerValues (i, i + 2, i + 4, ( i + 2 ) % 2);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::PropagateLayerValues(const StatusType& from,
const StatusType& to,
const StatusType& promote,
unsigned int InOrOut)
{
unsigned int i;
ValueType value, value_temp, delta;
bool found_neighbor_flag;
LayerNodeType *node;
StatusType past_end = static_cast< StatusType >( m_Layers.size() ) - 1;
// Are we propagating values inward (more negative) or outward (more
// positive)?
if ( InOrOut == 1 )
{
delta = -m_ConstantGradientValue; // inward
}
else
{
delta = m_ConstantGradientValue;
}
NeighborhoodIterator< OutputImageType > outputIt ( m_NeighborList.GetRadius(), m_OutputImage,
m_OutputImage->GetRequestedRegion() );
NeighborhoodIterator< StatusImageType > statusIt ( m_NeighborList.GetRadius(), m_StatusImage,
m_OutputImage->GetRequestedRegion() );
typename LayerType::Iterator toIt = m_Layers[to]->Begin();
while ( toIt != m_Layers[to]->End() )
{
statusIt.SetLocation(toIt->m_Index);
// Is this index marked for deletion? If the status image has
// been marked with another layer's value, we need to delete this node
// from the current list then skip to the next iteration.
if ( statusIt.GetCenterPixel() != to )
{
node = toIt.GetPointer();
++toIt;
m_Layers[to]->Unlink(node);
m_LayerNodeStore->Return(node);
continue;
}
outputIt.SetLocation(toIt->m_Index);
value = m_ValueZero;
found_neighbor_flag = false;
for ( i = 0; i < m_NeighborList.GetSize(); ++i )
{
// If this neighbor is in the "from" list, compare its absolute value
// to any previous values found in the "from" list. Keep the value
// that will cause the next layer to be closest to the zero level set.
if ( statusIt.GetPixel( m_NeighborList.GetArrayIndex(i) ) == from )
{
value_temp = outputIt.GetPixel( m_NeighborList.GetArrayIndex(i) );
if ( found_neighbor_flag == false )
{
value = value_temp;
}
else
{
if ( itk::Math::abs(value_temp + delta) < itk::Math::abs(value + delta) )
{
// take the value closest to zero
value = value_temp;
}
}
found_neighbor_flag = true;
}
}
if ( found_neighbor_flag == true )
{
// Set the new value using the smallest magnitude
// found in our "from" neighbors.
outputIt.SetCenterPixel(value + delta);
++toIt;
}
else
{
// Did not find any neighbors on the "from" list, then promote this
// node. A "promote" value past the end of my sparse field size
// means delete the node instead. Change the status value in the
// status image accordingly.
node = toIt.GetPointer();
++toIt;
m_Layers[to]->Unlink(node);
if ( promote > past_end )
{
m_LayerNodeStore->Return(node);
statusIt.SetCenterPixel(m_StatusNull);
}
else
{
m_Layers[promote]->PushFront(node);
statusIt.SetCenterPixel(promote);
}
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::InitializeBackgroundPixels()
{
// Assign background pixels INSIDE the sparse field layers to a new level set
// with value less than the innermost layer. Assign background pixels
// OUTSIDE the sparse field layers to a new level set with value greater than
// the outermost layer.
const ValueType max_layer = static_cast< ValueType >( m_NumberOfLayers );
const ValueType outside_value = ( max_layer + 1 ) * m_ConstantGradientValue;
const ValueType inside_value = -( max_layer + 1 ) * m_ConstantGradientValue;
ImageRegionConstIterator< StatusImageType > statusIt( m_StatusImage,
this->GetOutput()->GetRequestedRegion() );
ImageRegionIterator< OutputImageType > outputIt( this->GetOutput(),
this->GetOutput()->GetRequestedRegion() );
ImageRegionConstIterator< OutputImageType > shiftedIt( m_ShiftedImage,
this->GetOutput()->GetRequestedRegion() );
for ( outputIt.GoToBegin(), statusIt.GoToBegin(),
shiftedIt.GoToBegin();
!outputIt.IsAtEnd(); ++outputIt, ++statusIt, ++shiftedIt )
{
if ( statusIt.Get() == m_StatusNull || statusIt.Get() == m_StatusBoundaryPixel )
{
if ( shiftedIt.Get() > m_ValueZero )
{
outputIt.Set(outside_value);
}
else
{
outputIt.Set(inside_value);
}
}
}
// deallocate the shifted-image
m_ShiftedImage = ITK_NULLPTR;
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ComputeInitialThreadBoundaries()
{
// NOTE: Properties of the boundary computation algorithm
// 1. Thread-0 always has something to work on.
// 2. If a particular thread numbered i has the m_Boundary = (mZSize -
// 1) then ALL threads numbered > i do NOT have anything to work on.
// Compute the cumulative frequency distribution using the global histogram.
unsigned int i, j;
m_ZCumulativeFrequency[0] = m_GlobalZHistogram[0];
for ( i = 1; i < m_ZSize; i++ )
{
m_ZCumulativeFrequency[i] = m_ZCumulativeFrequency[i - 1] + m_GlobalZHistogram[i];
}
// Now define the regions that each thread will process and the corresponding
// boundaries.
m_Boundary[m_NumOfThreads - 1] = m_ZSize - 1; // special case: the upper
// bound for the last thread
for ( i = 0; i < m_NumOfThreads - 1; i++ )
{
// compute m_Boundary[i]
float cutOff = 1.0 * ( i + 1 ) * m_ZCumulativeFrequency[m_ZSize - 1] / m_NumOfThreads;
// find the position in the cumulative freq dist where this cutoff is met
for ( j = ( i == 0 ? 0 : m_Boundary[i - 1] ); j < m_ZSize; j++ )
{
if ( cutOff > m_ZCumulativeFrequency[j] )
{
continue;
}
else
{
// Optimize a little.
// Go further FORWARD and find the first index (k) in the cumulative
// freq distribution s.t. m_ZCumulativeFrequency[k] !=
// m_ZCumulativeFrequency[j] This is to be done because if we have a
// flat patch in the cumulative freq. dist. then we can choose
// a bound midway in that flat patch .
unsigned int k;
for ( k = 1; j + k < m_ZSize; k++ )
{
if ( m_ZCumulativeFrequency[j + k] != m_ZCumulativeFrequency[j] )
{
break;
}
}
//
m_Boundary[i] = static_cast< unsigned int >( ( j + k / 2 ) );
break;
}
}
}
// Initialize the local histograms using the global one and the boundaries
// Also initialize the mapping from the Z value --> the thread number
// i.e. m_MapZToThreadNumber[]
// Also divide the lists up according to the boundaries
for ( i = 0; i <= m_Boundary[0]; i++ )
{
// this Z belongs to the region associated with thread-0
m_MapZToThreadNumber[i] = 0;
}
for ( unsigned int t = 1; t < m_NumOfThreads; t++ )
{
for ( i = m_Boundary[t - 1] + 1; i <= m_Boundary[t]; i++ )
{
// this Z belongs to the region associated with thread-0
m_MapZToThreadNumber[i] = t;
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedAllocateData(ThreadIdType ThreadId)
{
static ITK_CONSTEXPR_VAR float SAFETY_FACTOR = 4.0;
unsigned int i, j;
m_Data[ThreadId].m_Condition[0] = ConditionVariable::New();
m_Data[ThreadId].m_Condition[1] = ConditionVariable::New();
m_Data[ThreadId].m_Semaphore[0] = 0;
m_Data[ThreadId].m_Semaphore[1] = 0;
// Allocate the layers for the sparse field.
m_Data[ThreadId].m_Layers.reserve(2 * m_NumberOfLayers + 1);
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; ++i )
{
m_Data[ThreadId].m_Layers.push_back( LayerType::New() );
}
// Throw an exception if we don't have enough layers.
if ( m_Data[ThreadId].m_Layers.size() < 3 )
{
itkExceptionMacro(<< "Not enough layers have been allocated for the sparse"
<< "field. Requires at least one layer.");
}
// Layers used as buffers for transferring pixels during load balancing
m_Data[ThreadId].m_LoadTransferBufferLayers =
new LayerListType[2 * m_NumberOfLayers + 1];
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
m_Data[ThreadId].m_LoadTransferBufferLayers[i].reserve(m_NumOfThreads);
for ( j = 0; j < m_NumOfThreads; j++ )
{
m_Data[ThreadId].m_LoadTransferBufferLayers[i].push_back( LayerType::New() );
}
}
// Every thread allocates a local node pool (improving memory locality)
m_Data[ThreadId].m_LayerNodeStore = LayerNodeStorageType::New();
m_Data[ThreadId].m_LayerNodeStore->SetGrowthStrategyToExponential();
// The SAFETY_FACTOR simple ensures that the number of nodes created
// is larger than those required to start with for each thread.
unsigned int nodeNum = static_cast< unsigned int >( SAFETY_FACTOR * m_Layers[0]->Size()
* ( 2 * m_NumberOfLayers + 1 ) / m_NumOfThreads );
m_Data[ThreadId].m_LayerNodeStore->Reserve(nodeNum);
m_Data[ThreadId].m_RMSChange = m_ValueZero;
// UpLists and Downlists
for ( i = 0; i < 2; ++i )
{
m_Data[ThreadId].UpList[i] = LayerType::New();
m_Data[ThreadId].DownList[i] = LayerType::New();
}
// Used during the time when status lists are being processed (in
// ThreadedApplyUpdate() )
// for the Uplists
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[0] =
new LayerPointerType *[m_NumberOfLayers + 1];
// for the Downlists
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[1] =
new LayerPointerType *[m_NumberOfLayers + 1];
for ( i = 0; i < static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[0][i] =
new LayerPointerType[m_NumOfThreads];
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[1][i] =
new LayerPointerType[m_NumOfThreads];
}
for ( i = 0; i < static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
for ( j = 0; j < m_NumOfThreads; j++ )
{
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[0][i][j] =
LayerType::New();
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[1][i][j] =
LayerType::New();
}
}
// Local histogram for every thread (used during Iterate() )
m_Data[ThreadId].m_ZHistogram = new int[m_ZSize];
for ( i = 0; i < m_ZSize; i++ )
{
m_Data[ThreadId].m_ZHistogram[i] = 0;
}
// Every thread must have its own copy of the the GlobalData struct.
m_Data[ThreadId].globalData =
this->GetDifferenceFunction()->GetGlobalDataPointer();
//
m_Data[ThreadId].m_SemaphoreArrayNumber = 0;
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedInitializeData(ThreadIdType ThreadId,
const ThreadRegionType & ThreadRegion)
{
// divide the lists based on the boundaries
LayerNodeType *nodePtr, *nodeTempPtr;
for ( unsigned int i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
typename LayerType::Iterator layerIt = m_Layers[i]->Begin();
typename LayerType::Iterator layerEnd = m_Layers[i]->End();
while ( layerIt != layerEnd )
{
nodePtr = layerIt.GetPointer();
++layerIt;
unsigned int k = this->GetThreadNumber(nodePtr->m_Index[m_SplitAxis]);
if ( k != ThreadId )
{
continue; // some other thread's node => ignore
}
// Borrow a node from the specific thread's layer so that MEMORY LOCALITY
// is maintained.
// NOTE : We already pre-allocated more than enough
// nodes for each thread implying no new nodes are created here.
nodeTempPtr = m_Data[ThreadId].m_LayerNodeStore->Borrow ();
nodeTempPtr->m_Index = nodePtr->m_Index;
// push the node on the approproate layer
m_Data[ThreadId].m_Layers[i]->PushFront(nodeTempPtr);
// for the active layer (layer-0) build the histogram for each thread
if ( i == 0 )
{
// this Z histogram value should be given to thread-0
m_Data[ThreadId].m_ZHistogram[( nodePtr->m_Index )[m_SplitAxis]] =
m_Data[ThreadId].m_ZHistogram[( nodePtr->m_Index )[m_SplitAxis]] + 1;
}
}
}
// Copy from the current status/output images to the new ones and let each
// thread do the copy of its own region.
// This will make each thread be the FIRST to write to "it's" data in the new
// images and hence the memory will get allocated
// in the corresponding thread's memory-node.
ImageRegionConstIterator< StatusImageType > statusIt(m_StatusImage, ThreadRegion);
ImageRegionIterator< StatusImageType > statusItNew (m_StatusImageTemp, ThreadRegion);
ImageRegionConstIterator< OutputImageType > outputIt(m_OutputImage, ThreadRegion);
ImageRegionIterator< OutputImageType > outputItNew(m_OutputImageTemp, ThreadRegion);
for ( outputIt.GoToBegin(), statusIt.GoToBegin(),
outputItNew.GoToBegin(), statusItNew.GoToBegin();
!outputIt.IsAtEnd(); ++outputIt, ++statusIt, ++outputItNew, ++statusItNew )
{
statusItNew.Set ( statusIt.Get() );
outputItNew.Set ( outputIt.Get() );
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::DeallocateData()
{
unsigned int i;
// Delete data structures used for load distribution and balancing.
delete[] m_GlobalZHistogram;
m_GlobalZHistogram = ITK_NULLPTR;
delete[] m_ZCumulativeFrequency;
m_ZCumulativeFrequency = ITK_NULLPTR;
delete[] m_MapZToThreadNumber;
m_MapZToThreadNumber = ITK_NULLPTR;
delete[] m_Boundary;
m_Boundary = ITK_NULLPTR;
// Deallocate the status image.
m_StatusImage = ITK_NULLPTR;
// Remove the barrier from the system.
// m_Barrier->Remove ();
// Delete initial nodes, the node pool, the layers.
if ( !m_Layers.empty() )
{
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
// return all the nodes in layer i to the main node pool
LayerNodeType * nodePtr = ITK_NULLPTR;
LayerPointerType layerPtr = m_Layers[i];
while ( !layerPtr->Empty() )
{
nodePtr = layerPtr->Front();
layerPtr->PopFront();
m_LayerNodeStore->Return (nodePtr);
}
}
}
if ( m_LayerNodeStore )
{
m_LayerNodeStore->Clear();
m_Layers.clear();
}
if ( m_Data != ITK_NULLPTR )
{
// Deallocate the thread local data structures.
for ( ThreadIdType ThreadId = 0; ThreadId < m_NumOfThreads; ThreadId++ )
{
delete[] m_Data[ThreadId].m_ZHistogram;
if ( m_Data[ThreadId].globalData != ITK_NULLPTR )
{
this->GetDifferenceFunction()->ReleaseGlobalDataPointer (m_Data[ThreadId].globalData);
m_Data[ThreadId].globalData = ITK_NULLPTR;
}
// 1. delete nodes on the thread layers
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
// return all the nodes in layer i to thread-i's node pool
LayerNodeType * nodePtr;
LayerPointerType layerPtr = m_Data[ThreadId].m_Layers[i];
while ( !layerPtr->Empty() )
{
nodePtr = layerPtr->Front();
layerPtr->PopFront();
m_Data[ThreadId].m_LayerNodeStore->Return(nodePtr);
}
}
m_Data[ThreadId].m_Layers.clear();
// 2. cleanup the LoadTransferBufferLayers: empty all and return the nodes
// to the pool
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
for ( ThreadIdType tid = 0; tid < m_NumOfThreads; tid++ )
{
if ( tid == ThreadId )
{
// a thread does NOT pass nodes to istelf
continue;
}
LayerNodeType * nodePtr;
LayerPointerType layerPtr = m_Data[ThreadId].m_LoadTransferBufferLayers[i][tid];
while ( !layerPtr->Empty() )
{
nodePtr = layerPtr->Front();
layerPtr->PopFront();
m_Data[ThreadId].m_LayerNodeStore->Return (nodePtr);
}
}
m_Data[ThreadId].m_LoadTransferBufferLayers[i].clear();
}
delete[] m_Data[ThreadId].m_LoadTransferBufferLayers;
// 3. clear up the nodes in the last layer of
// m_InterNeighborNodeTransferBufferLayers (if any)
for ( i = 0; i < m_NumOfThreads; i++ )
{
LayerNodeType *nodePtr;
for ( unsigned int InOrOut = 0; InOrOut < 2; InOrOut++ )
{
LayerPointerType layerPtr =
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[InOrOut][m_NumberOfLayers][i];
while ( !layerPtr->Empty() )
{
nodePtr = layerPtr->Front();
layerPtr->PopFront();
m_Data[ThreadId].m_LayerNodeStore->Return(nodePtr);
}
}
}
// check if all last layers are empty and then delete them
for ( i = 0; i < static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
delete[] m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[0][i];
delete[] m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[1][i];
}
delete[] m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[0];
delete[] m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[1];
// 4. check if all the uplists and downlists are empty
// 5. delete all nodes in the node pool
m_Data[ThreadId].m_LayerNodeStore->Clear();
}
delete[] m_Data;
} // if m_data != 0
m_Data = ITK_NULLPTR;
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedInitializeIteration( ThreadIdType itkNotUsed(ThreadId) )
{
// If child classes need an entry point to the start of every iteration step
// they can override this method.
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::Iterate()
{
// Set up for multithreaded processing
ParallelSparseFieldLevelSetThreadStruct str;
str.Filter = this;
str.TimeStep = NumericTraits< TimeStepType >::ZeroValue();
this->GetMultiThreader()->SetNumberOfThreads (m_NumOfThreads);
// Initialize the list of time step values that will be generated by the
// various threads. There is one distinct slot for each possible thread,
// so this data structure is thread-safe.
str.TimeStepList.resize( m_NumOfThreads );
str.ValidTimeStepList.resize( m_NumOfThreads, true );
// Multithread the execution
this->GetMultiThreader()->SetSingleMethod(this->IterateThreaderCallback, &str);
// It is this method that will results in the creation of the threads
this->GetMultiThreader()->SingleMethodExecute ();
}
template< typename TInputImage, typename TOutputImage >
ITK_THREAD_RETURN_TYPE
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::IterateThreaderCallback(void *arg)
{
// Controls how often we check for balance of the load among the threads and
// perform
// load balancing (if needed) by redistributing the load.
const unsigned int LOAD_BALANCE_ITERATION_FREQUENCY = 30;
unsigned int i;
ThreadIdType ThreadId = ( (MultiThreader::ThreadInfoStruct *)( arg ) )->ThreadID;
ParallelSparseFieldLevelSetThreadStruct *str =
(ParallelSparseFieldLevelSetThreadStruct *)
( ( (MultiThreader::ThreadInfoStruct *)( arg ) )->UserData );
// allocate thread data: every thread allocates its own data
// We do NOT assume here that malloc is thread safe: hence make threads
// allocate data serially
if ( !str->Filter->m_IsInitialized )
{
if ( ThreadId == 0 )
{
str->Filter->ComputeInitialThreadBoundaries ();
// Create the temporary status image
str->Filter->m_StatusImageTemp = StatusImageType::New();
str->Filter->m_StatusImageTemp->SetRegions( str->Filter->m_OutputImage->GetRequestedRegion() );
str->Filter->m_StatusImageTemp->Allocate();
// Create the temporary output image
str->Filter->m_OutputImageTemp = OutputImageType::New();
str->Filter->m_OutputImageTemp->CopyInformation(str->Filter->m_OutputImage);
str->Filter->m_OutputImageTemp->SetRegions( str->Filter->m_OutputImage->GetRequestedRegion() );
str->Filter->m_OutputImageTemp->Allocate();
}
str->Filter->WaitForAll();
// Data allocation performed serially.
for ( i = 0; i < str->Filter->m_NumOfThreads; i++ )
{
if ( ThreadId == i )
{
str->Filter->ThreadedAllocateData (ThreadId);
}
str->Filter->WaitForAll();
}
// Data initialization performed in parallel.
str->Filter->GetThreadRegionSplitByBoundary(ThreadId,
str->Filter->m_Data[ThreadId].ThreadRegion);
str->Filter->ThreadedInitializeData(ThreadId,
str->Filter->m_Data[ThreadId].ThreadRegion);
str->Filter->WaitForAll();
if ( ThreadId == 0 )
{
str->Filter->m_StatusImage = ITK_NULLPTR;
str->Filter->m_StatusImage = str->Filter->m_StatusImageTemp;
str->Filter->m_StatusImageTemp = ITK_NULLPTR;
str->Filter->m_OutputImage = ITK_NULLPTR;
str->Filter->m_OutputImage = str->Filter->m_OutputImageTemp;
str->Filter->m_OutputImageTemp = ITK_NULLPTR;
//
str->Filter->GraftOutput(str->Filter->m_OutputImage);
}
str->Filter->WaitForAll();
str->Filter->m_IsInitialized = true;
}
unsigned int iter = str->Filter->GetElapsedIterations();
while ( !( str->Filter->ThreadedHalt(arg) ) )
{
str->Filter->ThreadedInitializeIteration(ThreadId);
// Threaded Calculate Change
str->Filter->m_Data[ThreadId].TimeStep =
str->Filter->ThreadedCalculateChange(ThreadId);
str->Filter->WaitForAll();
// Handle AbortGenerateData()
if ( str->Filter->m_NumOfThreads == 1 || ThreadId == 0 )
{
if ( str->Filter->GetAbortGenerateData() )
{
str->Filter->InvokeEvent( IterationEvent() );
str->Filter->ResetPipeline();
ProcessAborted e(__FILE__, __LINE__);
e.SetDescription("Process aborted.");
e.SetLocation(ITK_LOCATION);
throw e;
}
}
// Calculate the timestep (no need to do this when there is just 1 thread)
if ( str->Filter->m_NumOfThreads == 1 )
{
if ( iter != 0 )
{
// Update the RMS difference here
str->Filter->SetRMSChange( static_cast< double >( str->Filter->m_Data[0].m_RMSChange ) );
unsigned int count = str->Filter->m_Data[0].m_Count;
if ( count != 0 )
{
str->Filter->SetRMSChange( static_cast< double >( std::sqrt(
( static_cast< float >( str->Filter->GetRMSChange() ) )
/ count) ) );
}
}
// this is done by the thread0
str->Filter->InvokeEvent( IterationEvent() );
str->Filter->InvokeEvent( ProgressEvent () );
str->Filter->SetElapsedIterations(++iter);
// (works for the 1-thread case else redefined below)
str->TimeStep = str->Filter->m_Data[0].TimeStep;
}
else
{
if ( ThreadId == 0 )
{
if ( iter != 0 )
{
// Update the RMS difference here
unsigned int count = 0;
str->Filter->SetRMSChange( static_cast< double >( m_ValueZero ) );
for ( i = 0; i < str->Filter->m_NumOfThreads; i++ )
{
str->Filter->SetRMSChange(str->Filter->GetRMSChange() + str->Filter->m_Data[i].m_RMSChange);
count += str->Filter->m_Data[i].m_Count;
}
if ( count != 0 )
{
str->Filter->SetRMSChange( static_cast< double >( std::sqrt( ( static_cast< float >( str->Filter->
m_RMSChange ) )
/ count ) ) );
}
}
// Should we stop iterating ? (in case there are too few pixels to
// process for every thread)
str->Filter->m_Stop = true;
for ( i = 0; i < str->Filter->m_NumOfThreads; i++ )
{
if ( str->Filter->m_Data[i].m_Layers[0]->Size() > 10 )
{
str->Filter->m_Stop = false;
break;
}
}
str->Filter->InvokeEvent ( IterationEvent() );
str->Filter->InvokeEvent ( ProgressEvent () );
str->Filter->SetElapsedIterations (++iter);
}
if ( ThreadId == 0 )
{
for ( i = 0; i < str->Filter->m_NumOfThreads; i++ )
{
str->TimeStepList[i] = str->Filter->m_Data[i].TimeStep;
}
str->TimeStep = str->Filter->ResolveTimeStep(str->TimeStepList,
str->ValidTimeStepList );
}
}
str->Filter->WaitForAll();
// The active layer is too small => stop iterating
if ( str->Filter->m_Stop == true )
{
return ITK_THREAD_RETURN_VALUE;
}
// Threaded Apply Update
str->Filter->ThreadedApplyUpdate(str->TimeStep, ThreadId);
// We only need to wait for neighbors because ThreadedCalculateChange
// requires information only from the neighbors.
str->Filter->SignalNeighborsAndWait(ThreadId);
if ( str->Filter->GetElapsedIterations()
% LOAD_BALANCE_ITERATION_FREQUENCY == 0 )
{
str->Filter->WaitForAll();
// change boundaries if needed
if ( ThreadId == 0 )
{
str->Filter->CheckLoadBalance();
}
str->Filter->WaitForAll();
if ( str->Filter->m_BoundaryChanged == true )
{
str->Filter->ThreadedLoadBalance (ThreadId);
str->Filter->WaitForAll();
}
}
}
// post-process output
str->Filter->GetThreadRegionSplitUniformly(ThreadId,
str->Filter->m_Data[ThreadId].ThreadRegion);
str->Filter->ThreadedPostProcessOutput(
str->Filter->m_Data[ThreadId].ThreadRegion);
return ITK_THREAD_RETURN_VALUE;
}
template< typename TInputImage, typename TOutputImage >
typename
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::TimeStepType
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedCalculateChange(ThreadIdType ThreadId)
{
typename FiniteDifferenceFunctionType::Pointer df = this->GetDifferenceFunction();
typename FiniteDifferenceFunctionType::FloatOffsetType offset;
ValueType norm_grad_phi_squared, dx_forward, dx_backward;
ValueType centerValue, forwardValue, backwardValue;
ValueType MIN_NORM = 1.0e-6;
if ( this->GetUseImageSpacing() )
{
SpacePrecisionType minSpacing = NumericTraits< SpacePrecisionType >::max();
for ( unsigned int i = 0; i < ImageDimension; i++ )
{
minSpacing = std::min(minSpacing, this->GetInput()->GetSpacing()[i]);
}
MIN_NORM *= minSpacing;
}
ConstNeighborhoodIterator< OutputImageType > outputIt ( df->GetRadius(), m_OutputImage,
m_OutputImage->GetRequestedRegion() );
if ( m_BoundsCheckingActive == false )
{
outputIt.NeedToUseBoundaryConditionOff();
}
unsigned int i, center = outputIt.Size() / 2;
this->GetDifferenceFunction()->ComputeNeighborhoodScales();
// Calculates the update values for the active layer indices in this
// iteration. Iterates through the active layer index list, applying
// the level set function to the output image (level set image) at each
// index.
typename LayerType::Iterator layerIt = m_Data[ThreadId].m_Layers[0]->Begin();
typename LayerType::Iterator layerEnd = m_Data[ThreadId].m_Layers[0]->End();
for (; layerIt != layerEnd; ++layerIt )
{
outputIt.SetLocation(layerIt->m_Index);
// Calculate the offset to the surface from the center of this
// neighborhood. This is used by some level set functions in sampling a
// speed, advection, or curvature term.
if ( this->m_InterpolateSurfaceLocation
&& Math::NotExactlyEquals(( centerValue = outputIt.GetCenterPixel() ), NumericTraits< ValueType >::ZeroValue()) )
{
// Surface is at the zero crossing, so distance to surface is:
// phi(x) / norm(grad(phi)), where phi(x) is the center of the
// neighborhood. The location is therefore
// (i,j,k) - ( phi(x) * grad(phi(x)) ) / norm(grad(phi))^2
norm_grad_phi_squared = 0.0;
for ( i = 0; i < static_cast< unsigned int >( ImageDimension ); ++i )
{
forwardValue = outputIt.GetPixel( center + m_NeighborList.GetStride(i) );
backwardValue = outputIt.GetPixel( center - m_NeighborList.GetStride(i) );
if ( forwardValue * backwardValue >= 0 )
{
// 1. both neighbors have the same sign OR at least one of them is
// ZERO
dx_forward = forwardValue - centerValue;
dx_backward = centerValue - backwardValue;
// take the one-sided derivative with the larger magnitude
if ( itk::Math::abs(dx_forward) > itk::Math::abs(dx_backward) )
{
offset[i] = dx_forward;
}
else
{
offset[i] = dx_backward;
}
}
else
{
// 2. neighbors have opposite sign
// take the one-sided derivative using the neighbor that has the
// opposite sign w.r.t. oneself
if ( centerValue * forwardValue < 0 )
{
offset[i] = forwardValue - centerValue;
}
else
{
offset[i] = centerValue - backwardValue;
}
}
norm_grad_phi_squared += offset[i] * offset[i];
}
for ( i = 0; i < static_cast< unsigned int >( ImageDimension ); ++i )
{
offset[i] = ( offset[i] * outputIt.GetCenterPixel() )
/ ( norm_grad_phi_squared + MIN_NORM );
}
layerIt->m_Value = df->ComputeUpdate (outputIt, (void *)m_Data[ThreadId].globalData, offset);
}
else // Don't do interpolation
{
layerIt->m_Value = df->ComputeUpdate (outputIt, (void *)m_Data[ThreadId].globalData);
}
}
TimeStepType timeStep = df->ComputeGlobalTimeStep ( (void *)m_Data[ThreadId].globalData );
return timeStep;
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedApplyUpdate(const TimeStepType& dt, ThreadIdType ThreadId)
{
this->ThreadedUpdateActiveLayerValues(dt,
m_Data[ThreadId].UpList[0],
m_Data[ThreadId].DownList[0],
ThreadId);
// We need to update histogram information (because some pixels are LEAVING
// layer-0 (the active layer)
this->SignalNeighborsAndWait(ThreadId);
// Process status lists and update value for first inside/outside layers
this->ThreadedProcessStatusList(0, 1, 2, 1, 1, 0, ThreadId);
this->ThreadedProcessStatusList(0, 1, 1, 2, 0, 0, ThreadId);
this->SignalNeighborsAndWait(ThreadId);
// Update first layer value, process first layer
this->ThreadedProcessFirstLayerStatusLists(1, 0, 3, 1, 1, ThreadId);
this->ThreadedProcessFirstLayerStatusLists(1, 0, 4, 0, 1, ThreadId);
// We need to update histogram information (because some pixels are ENTERING
// layer-0
this->SignalNeighborsAndWait(ThreadId);
StatusType up_to = 1, up_search = 5;
StatusType down_to = 2, down_search = 6;
unsigned char j = 0, k = 1;
// The 3D case: this loop is executed at least once
while ( down_search < 2 * m_NumberOfLayers + 1 )
{
this->ThreadedProcessStatusList(j, k, up_to, up_search, 1,
( up_search - 1 ) / 2, ThreadId);
this->ThreadedProcessStatusList(j, k, down_to, down_search, 0,
( up_search - 1 ) / 2, ThreadId);
this->SignalNeighborsAndWait(ThreadId);
up_to += 2;
down_to += 2;
up_search += 2;
down_search += 2;
// Swap the lists so we can re-use the empty one.
j = k;
k = 1 - j;
}
// now up_search = 2 * m_NumberOfLayers + 1 (= 7 if m_NumberOfLayers = 3)
// now down_search = 2 * m_NumberOfLayers + 2 (= 8 if m_NumberOfLayers = 3)
// Process the outermost inside/outside layers in the sparse field
this->ThreadedProcessStatusList(j, k, up_to, m_StatusNull, 1,
( up_search - 1 ) / 2, ThreadId);
this->ThreadedProcessStatusList(j, k, down_to, m_StatusNull, 0,
( up_search - 1 ) / 2, ThreadId);
this->SignalNeighborsAndWait(ThreadId);
this->ThreadedProcessOutsideList(k, ( 2 * m_NumberOfLayers + 1 ) - 2, 1,
( up_search + 1 ) / 2, ThreadId);
this->ThreadedProcessOutsideList(k, ( 2 * m_NumberOfLayers + 1 ) - 1, 0,
( up_search + 1 ) / 2, ThreadId);
if ( m_OutputImage->GetImageDimension() < 3 )
{
this->SignalNeighborsAndWait(ThreadId);
}
// A synchronize is NOT required here because in 3D case we have at least 7
// layers, thus ThreadedProcessOutsideList() works on layers 5 & 6 while
// ThreadedPropagateLayerValues() works on 0, 1, 2, 3, 4 only. => There can
// NOT be any dependencies amoing different threads.
// Finally, we update all of the layer VALUES (excluding the active layer,
// which has already been updated)
this->ThreadedPropagateLayerValues(0, 1, 3, 1, ThreadId); // first inside
this->ThreadedPropagateLayerValues(0, 2, 4, 0, ThreadId); // first outside
this->SignalNeighborsAndWait (ThreadId);
// Update the rest of the layer values
unsigned int N = ( 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1 ) - 2;
for ( unsigned int i = 1; i < N; i += 2 )
{
j = i + 1;
this->ThreadedPropagateLayerValues(i, i + 2, i + 4, 1, ThreadId);
this->ThreadedPropagateLayerValues(j, j + 2, j + 4, 0, ThreadId);
this->SignalNeighborsAndWait (ThreadId);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedUpdateActiveLayerValues(const TimeStepType& dt, LayerType *UpList,
LayerType *DownList, ThreadIdType ThreadId)
{
// This method scales the update buffer values by the time step and adds
// them to the active layer pixels. New values at an index which fall
// outside of the active layer range trigger that index to be placed on the
// "up" or "down" status list. The neighbors of any such index are then
// assigned new values if they are determined to be part of the active list
// for the next iteration (i.e. their values will be raised or lowered into
// the active range).
ValueType LOWER_ACTIVE_THRESHOLD = -( m_ConstantGradientValue / 2.0 );
ValueType UPPER_ACTIVE_THRESHOLD = m_ConstantGradientValue / 2.0;
LayerNodeType *release_node;
bool flag;
IndexType centerIndex;
PixelType centerValue;
typename TOutputImage::SizeValueType counter = 0;
float new_value;
float rms_change_accumulator = m_ValueZero;
unsigned int Neighbor_Size = m_NeighborList.GetSize();
typename LayerType::Iterator layerIt =
m_Data[ThreadId].m_Layers[0]->Begin();
typename LayerType::Iterator layerEnd =
m_Data[ThreadId].m_Layers[0]->End();
while ( layerIt != layerEnd )
{
centerIndex = layerIt->m_Index;
centerValue = m_OutputImage->GetPixel(centerIndex);
new_value = this->ThreadedCalculateUpdateValue(ThreadId, centerIndex, dt,
centerValue, layerIt->m_Value);
// If this index needs to be moved to another layer, then search its
// neighborhood for indices that need to be pulled up/down into the
// active layer. Set those new active layer values appropriately,
// checking first to make sure they have not been set by a more
// influential neighbor.
// ...But first make sure any neighbors in the active layer are not
// moving to a layer in the opposite direction. This step is necessary
// to avoid the creation of holes in the active layer. The fix is simply
// to not change this value and leave the index in the active set.
if ( new_value > UPPER_ACTIVE_THRESHOLD )
{
// This index will move UP into a positive (outside) layer
// First check for active layer neighbors moving in the opposite
// direction
flag = false;
for ( unsigned int i = 0; i < Neighbor_Size; ++i )
{
if ( m_StatusImage->GetPixel( centerIndex + m_NeighborList.GetNeighborhoodOffset(i) )
== m_StatusActiveChangingDown )
{
flag = true;
break;
}
}
if ( flag == true )
{
++layerIt;
continue;
}
rms_change_accumulator += itk::Math::sqr( static_cast< float >( new_value - centerValue ) );
// update the value of the pixel
m_OutputImage->SetPixel (centerIndex, new_value);
// Now remove this index from the active list.
release_node = layerIt.GetPointer();
++layerIt;
m_Data[ThreadId].m_Layers[0]->Unlink(release_node);
m_Data[ThreadId].m_ZHistogram[release_node->m_Index[m_SplitAxis]] =
m_Data[ThreadId].m_ZHistogram[release_node->m_Index[m_SplitAxis]] - 1;
// add the release_node to status up list
UpList->PushFront(release_node);
//
m_StatusImage->SetPixel(centerIndex, m_StatusActiveChangingUp);
}
else if ( new_value < LOWER_ACTIVE_THRESHOLD )
{
// This index will move DOWN into a negative (inside) layer.
// First check for active layer neighbors moving in the opposite direction
flag = false;
for ( unsigned int i = 0; i < Neighbor_Size; ++i )
{
if ( m_StatusImage->GetPixel( centerIndex + m_NeighborList.GetNeighborhoodOffset(i) )
== m_StatusActiveChangingUp )
{
flag = true;
break;
}
}
if ( flag == true )
{
++layerIt;
continue;
}
rms_change_accumulator += itk::Math::sqr( static_cast< float >( new_value - centerValue ) );
// update the value of the pixel
m_OutputImage->SetPixel(centerIndex, new_value);
// Now remove this index from the active list.
release_node = layerIt.GetPointer();
++layerIt;
m_Data[ThreadId].m_Layers[0]->Unlink(release_node);
m_Data[ThreadId].m_ZHistogram[release_node->m_Index[m_SplitAxis]] =
m_Data[ThreadId].m_ZHistogram[release_node->m_Index[m_SplitAxis]] - 1;
// now add release_node to status down list
DownList->PushFront(release_node);
m_StatusImage->SetPixel(centerIndex, m_StatusActiveChangingDown);
}
else
{
rms_change_accumulator += itk::Math::sqr( static_cast< float >( new_value - centerValue ) );
// update the value of the pixel
m_OutputImage->SetPixel(centerIndex, new_value);
++layerIt;
}
++counter;
}
// Determine the average change during this iteration
if ( counter == 0 )
{
m_Data[ThreadId].m_RMSChange = m_ValueZero;
}
else
{
m_Data[ThreadId].m_RMSChange = rms_change_accumulator;
}
m_Data[ThreadId].m_Count = counter;
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::CopyInsertList(ThreadIdType ThreadId, LayerPointerType FromListPtr,
LayerPointerType ToListPtr)
{
typename LayerType::Iterator layerIt = FromListPtr->Begin();
typename LayerType::Iterator layerEnd = FromListPtr->End();
LayerNodeType *nodePtr;
LayerNodeType *nodeTempPtr;
while ( layerIt != layerEnd )
{
// copy the node
nodePtr = layerIt.GetPointer();
++layerIt;
nodeTempPtr = m_Data[ThreadId].m_LayerNodeStore->Borrow();
nodeTempPtr->m_Index = nodePtr->m_Index;
// insert
ToListPtr->PushFront (nodeTempPtr);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ClearList(ThreadIdType ThreadId, LayerPointerType ListPtr)
{
LayerNodeType *nodePtr;
while ( !ListPtr->Empty() )
{
nodePtr = ListPtr->Front();
// remove node from layer
ListPtr->PopFront();
// return node to node-pool
m_Data[ThreadId].m_LayerNodeStore->Return (nodePtr);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::CopyInsertInterNeighborNodeTransferBufferLayers(
ThreadIdType ThreadId, LayerPointerType List,
unsigned int InOrOut, unsigned int BufferLayerNumber)
{
if ( ThreadId != 0 )
{
CopyInsertList(ThreadId,
m_Data[this->GetThreadNumber(m_Boundary[ThreadId
- 1])].m_InterNeighborNodeTransferBufferLayers[InOrOut][
BufferLayerNumber][ThreadId],
List);
}
if ( m_Boundary[ThreadId] != m_ZSize - 1 )
{
CopyInsertList(ThreadId,
m_Data[this->GetThreadNumber (m_Boundary[ThreadId]
+ 1)].m_InterNeighborNodeTransferBufferLayers[InOrOut][
BufferLayerNumber][ThreadId],
List);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ClearInterNeighborNodeTransferBufferLayers(
ThreadIdType ThreadId, unsigned int InOrOut,
unsigned int BufferLayerNumber)
{
for ( unsigned int i = 0; i < m_NumOfThreads; i++ )
{
ClearList(ThreadId, m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[InOrOut][BufferLayerNumber][i]);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedProcessFirstLayerStatusLists(
unsigned int InputLayerNumber, unsigned int OutputLayerNumber,
const StatusType& SearchForStatus, unsigned int InOrOut,
unsigned int BufferLayerNumber, ThreadIdType ThreadId)
{
LayerNodeType *nodePtr;
StatusType from, neighbor_status;
ValueType value, value_temp, delta;
bool found_neighbor_flag;
IndexType center_index, n_index;
unsigned int neighbor_Size = m_NeighborList.GetSize();
LayerPointerType InputList, OutputList;
//InOrOut == 1, inside, more negative, uplist
//InOrOut == 0, outside
if ( InOrOut == 1 )
{
delta = -m_ConstantGradientValue;
from = 2;
InputList = m_Data[ThreadId].UpList[InputLayerNumber];
OutputList = m_Data[ThreadId].UpList[OutputLayerNumber];
}
else
{
delta = m_ConstantGradientValue;
from = 1;
InputList = m_Data[ThreadId].DownList[InputLayerNumber];
OutputList = m_Data[ThreadId].DownList[OutputLayerNumber];
}
// 1. nothing to clear
// 2. make a copy of the node on the
// m_InterNeighborNodeTransferBufferLayers[InOrOut][BufferLayerNumber -
// 1][i]
// for all neighbors i ... and insert it in one's own InputList
CopyInsertInterNeighborNodeTransferBufferLayers(ThreadId, InputList, InOrOut,
BufferLayerNumber - 1);
typename LayerType::Iterator layerIt = InputList->Begin();
typename LayerType::Iterator layerEnd = InputList->End();
while ( layerIt != layerEnd )
{
nodePtr = layerIt.GetPointer();
++layerIt;
center_index = nodePtr->m_Index;
// remove node from InputList
InputList->Unlink(nodePtr);
// check if this is not a duplicate pixel in the InputList
// In the case when the thread boundaries differ by just 1 pixel some
// nodes may get added twice in the InputLists Even if the boundaries are
// more than 1 pixel wide the *_shape_* of the layer may allow this to
// happen. Solution: If a pixel comes multiple times than we would find
// that the Status image would already be reflecting the new status after
// the pixel was encountered the first time
if ( m_StatusImage->GetPixel(center_index) == 0 )
{
// duplicate node => return it to the node pool
m_Data[ThreadId].m_LayerNodeStore->Return (nodePtr);
continue;
}
// set status to zero
m_StatusImage->SetPixel(center_index, 0);
// add node to the layer-0
m_Data[ThreadId].m_Layers[0]->PushFront(nodePtr);
m_Data[ThreadId].m_ZHistogram[nodePtr->m_Index[m_SplitAxis]] =
m_Data[ThreadId].m_ZHistogram[nodePtr->m_Index[m_SplitAxis]] + 1;
value = m_OutputImage->GetPixel(center_index);
found_neighbor_flag = false;
for ( unsigned int i = 0; i < neighbor_Size; ++i )
{
n_index = center_index + m_NeighborList.GetNeighborhoodOffset(i);
neighbor_status = m_StatusImage->GetPixel(n_index);
// Have we bumped up against the boundary? If so, turn on bounds
// checking.
if ( neighbor_status == m_StatusBoundaryPixel )
{
m_BoundsCheckingActive = true;
}
if ( neighbor_status == from )
{
value_temp = m_OutputImage->GetPixel(n_index);
if ( found_neighbor_flag == false )
{
value = value_temp;
}
else
{
if ( itk::Math::abs(value_temp + delta) < itk::Math::abs(value + delta) )
{
// take the value closest to zero
value = value_temp;
}
}
found_neighbor_flag = true;
}
if ( neighbor_status == SearchForStatus )
{
// mark this pixel so we MAY NOT add it twice
// This STILL DOES NOT GUARANTEE RACE CONDITIONS BETWEEN THREADS. This
// is handled at the next stage
m_StatusImage->SetPixel(n_index, m_StatusChanging);
unsigned int tmpId = this->GetThreadNumber(n_index[m_SplitAxis]);
nodePtr = m_Data[ThreadId].m_LayerNodeStore->Borrow();
nodePtr->m_Index = n_index;
if ( tmpId != ThreadId )
{
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[InOrOut][BufferLayerNumber][tmpId]->PushFront(
nodePtr);
}
else
{
OutputList->PushFront(nodePtr);
}
}
}
m_OutputImage->SetPixel(center_index, value + delta);
// This function can be overridden in the derived classes to process pixels
// entering the active layer.
this->ThreadedProcessPixelEnteringActiveLayer (center_index, value + delta, ThreadId);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedProcessPixelEnteringActiveLayer( const IndexType& itkNotUsed(index),
const ValueType& itkNotUsed(value),
ThreadIdType itkNotUsed(ThreadId) )
{
// This function can be overridden in the derived classes to process pixels
// entering the active layer.
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedProcessStatusList(
unsigned int InputLayerNumber, unsigned int OutputLayerNumber,
const StatusType& ChangeToStatus, const StatusType& SearchForStatus,
unsigned int InOrOut, unsigned int BufferLayerNumber,
ThreadIdType ThreadId)
{
unsigned int i;
LayerNodeType *nodePtr;
StatusType neighbor_status;
IndexType center_index, n_index;
LayerPointerType InputList, OutputList;
// Push each index in the input list into its appropriate status layer
// (ChangeToStatus) and update the status image value at that index.
// Also examine the neighbors of the index to determine which need to go onto
// the output list (search for SearchForStatus).
if ( InOrOut == 1 )
{
InputList = m_Data[ThreadId].UpList[InputLayerNumber];
OutputList = m_Data[ThreadId].UpList[OutputLayerNumber];
}
else
{
InputList = m_Data[ThreadId].DownList[InputLayerNumber];
OutputList = m_Data[ThreadId].DownList[OutputLayerNumber];
}
// 1. clear one's own
// m_InterNeighborNodeTransferBufferLayers[InOrOut][BufferLayerNumber - 2][i]
// for all threads i.
if ( BufferLayerNumber >= 2 )
{
ClearInterNeighborNodeTransferBufferLayers(ThreadId, InOrOut,
BufferLayerNumber - 2);
}
// SPECIAL CASE: clear one's own
// m_InterNeighborNodeTransferBufferLayers[InOrOut][m_NumberOfLayers][i] for
// all threads i
if ( BufferLayerNumber == 0 )
{
ClearInterNeighborNodeTransferBufferLayers(ThreadId, InOrOut, m_NumberOfLayers);
}
// obtain the pixels (from last iteration) that were given to you from other
// (neighboring) threads 2. make a copy of the node on the
// m_InterNeighborNodeTransferBufferLayers[InOrOut][LastLayer - 1][i] for all
// thread neighbors i ... ... and insert it in one's own InputList
if ( BufferLayerNumber > 0 )
{
CopyInsertInterNeighborNodeTransferBufferLayers(ThreadId, InputList,
InOrOut, BufferLayerNumber - 1);
}
unsigned int neighbor_size = m_NeighborList.GetSize();
while ( !InputList->Empty() )
{
nodePtr = InputList->Front();
center_index = nodePtr->m_Index;
InputList->PopFront();
// Check if this is not a duplicate pixel in the InputList.
// Solution: If a pixel comes multiple times than we would find that the
// Status image would already be reflecting
// the new status after the pixel was encountered the first time
if ( ( BufferLayerNumber != 0 )
&& ( m_StatusImage->GetPixel(center_index) == ChangeToStatus ) )
{
// duplicate node => return it to the node pool
m_Data[ThreadId].m_LayerNodeStore->Return (nodePtr);
continue;
}
// add to layer
m_Data[ThreadId].m_Layers[ChangeToStatus]->PushFront (nodePtr);
// change the status
m_StatusImage->SetPixel(center_index, ChangeToStatus);
for ( i = 0; i < neighbor_size; ++i )
{
n_index = center_index + m_NeighborList.GetNeighborhoodOffset(i);
neighbor_status = m_StatusImage->GetPixel(n_index);
// Have we bumped up against the boundary? If so, turn on bounds
// checking.
if ( neighbor_status == m_StatusBoundaryPixel )
{
m_BoundsCheckingActive = true;
}
if ( neighbor_status == SearchForStatus )
{
// mark this pixel so we MAY NOT add it twice
// This STILL DOES NOT AVOID RACE CONDITIONS BETWEEN THREADS (This is
// handled at the next stage)
m_StatusImage->SetPixel(n_index, m_StatusChanging);
unsigned int tmpId = this->GetThreadNumber (n_index[m_SplitAxis]);
nodePtr = m_Data[ThreadId].m_LayerNodeStore->Borrow();
nodePtr->m_Index = n_index;
if ( tmpId != ThreadId )
{
m_Data[ThreadId].m_InterNeighborNodeTransferBufferLayers[InOrOut][BufferLayerNumber][tmpId]->PushFront(
nodePtr);
}
else
{
OutputList->PushFront(nodePtr);
}
}
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedProcessOutsideList(
unsigned int InputLayerNumber, const StatusType& ChangeToStatus,
unsigned int InOrOut, unsigned int BufferLayerNumber,
ThreadIdType ThreadId)
{
LayerPointerType OutsideList;
if ( InOrOut == 1 )
{
OutsideList = m_Data[ThreadId].UpList[InputLayerNumber];
}
else
{
OutsideList = m_Data[ThreadId].DownList[InputLayerNumber];
}
// obtain the pixels (from last iteration of ThreadedProcessStatusList() )
// that were given to you from other (neighboring) threads
// 1. clear one's own
// m_InterNeighborNodeTransferBufferLayers[InOrOut][BufferLayerNumber -
// 2][i]
// for all threads i.
ClearInterNeighborNodeTransferBufferLayers(ThreadId, InOrOut, BufferLayerNumber - 2);
// 2. make a copy of the node on the
// m_InterNeighborNodeTransferBufferLayers[InOrOut][LastLayer - 1][i] for
// all thread neighbors i ... ... and insert it in one's own InoutList
CopyInsertInterNeighborNodeTransferBufferLayers(ThreadId, OutsideList, InOrOut,
BufferLayerNumber - 1);
// Push each index in the input list into its appropriate status layer
// (ChangeToStatus) and ... ... update the status image value at that index
LayerNodeType *nodePtr;
while ( !OutsideList->Empty() )
{
nodePtr = OutsideList->Front();
OutsideList->PopFront();
m_StatusImage->SetPixel(nodePtr->m_Index, ChangeToStatus);
m_Data[ThreadId].m_Layers[ChangeToStatus]->PushFront (nodePtr);
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedPropagateLayerValues(
const StatusType& from, const StatusType& to,
const StatusType& promote, unsigned int InOrOut,
ThreadIdType ThreadId)
{
ValueType value, value_temp, delta;
bool found_neighbor_flag;
typename LayerType::Iterator toIt;
typename LayerType::Iterator toEnd;
LayerNodeType *nodePtr;
StatusType past_end = static_cast< StatusType >( m_Layers.size() ) - 1;
// Are we propagating values inward (more negative) or outward (more
// positive)?
if ( InOrOut == 1 )
{
delta = -m_ConstantGradientValue;
}
else
{
delta = m_ConstantGradientValue;
}
unsigned int Neighbor_Size = m_NeighborList.GetSize();
toIt = m_Data[ThreadId].m_Layers[to]->Begin();
toEnd = m_Data[ThreadId].m_Layers[to]->End();
IndexType centerIndex, nIndex;
StatusType centerStatus, nStatus;
while ( toIt != toEnd )
{
centerIndex = toIt->m_Index;
centerStatus = m_StatusImage->GetPixel(centerIndex);
if ( centerStatus != to )
{
// delete nodes NOT deleted earlier
nodePtr = toIt.GetPointer();
++toIt;
// remove the node from the layer
m_Data[ThreadId].m_Layers[to]->Unlink(nodePtr);
m_Data[ThreadId].m_LayerNodeStore->Return(nodePtr);
continue;
}
value = m_ValueZero;
found_neighbor_flag = false;
for ( unsigned int i = 0; i < Neighbor_Size; ++i )
{
nIndex = centerIndex + m_NeighborList.GetNeighborhoodOffset(i);
nStatus = m_StatusImage->GetPixel(nIndex);
// If this neighbor is in the "from" list, compare its absolute value
// to any previous values found in the "from" list. Keep only the
// value with the smallest magnitude.
if ( nStatus == from )
{
value_temp = m_OutputImage->GetPixel(nIndex);
if ( found_neighbor_flag == false )
{
value = value_temp;
}
else
{
if ( itk::Math::abs(value_temp + delta) < itk::Math::abs(value + delta) )
{
// take the value closest to zero
value = value_temp;
}
}
found_neighbor_flag = true;
}
}
if ( found_neighbor_flag == true )
{
// Set the new value using the smallest magnitude found in our "from"
// neighbors
m_OutputImage->SetPixel (centerIndex, value + delta);
++toIt;
}
else
{
// Did not find any neighbors on the "from" list, then promote this
// node. A "promote" value past the end of my sparse field size
// means delete the node instead. Change the status value in the
// status image accordingly.
nodePtr = toIt.GetPointer();
++toIt;
m_Data[ThreadId].m_Layers[to]->Unlink(nodePtr);
if ( promote > past_end )
{
m_Data[ThreadId].m_LayerNodeStore->Return(nodePtr);
m_StatusImage->SetPixel(centerIndex, m_StatusNull);
}
else
{
m_Data[ThreadId].m_Layers[promote]->PushFront(nodePtr);
m_StatusImage->SetPixel(centerIndex, promote);
}
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::CheckLoadBalance()
{
unsigned int i, j;
// This parameter defines a degree of unbalancedness of the load among
// threads.
const float MAX_PIXEL_DIFFERENCE_PERCENT = 0.025;
m_BoundaryChanged = false;
// work load division based on the nodes on the active layer (layer-0)
typedef IndexValueType NodeCounterType;
NodeCounterType min = NumericTraits< NodeCounterType >::max();
NodeCounterType max = 0;
NodeCounterType total = 0; // the total nodes in the active layer of the surface
for ( i = 0; i < m_NumOfThreads; i++ )
{
NodeCounterType count = m_Data[i].m_Layers[0]->Size();
total += count;
if ( min > count ) { min = count; }
if ( max < count ) { max = count; }
}
if ( max - min < MAX_PIXEL_DIFFERENCE_PERCENT * total / m_NumOfThreads )
{
// if the difference between max and min is NOT even x% of the average
// nodes in the thread layers then no need to change the boundaries next
return;
}
// Change the boundaries --------------------------
// compute the global histogram from the individual histograms
for ( i = 0; i < m_NumOfThreads; i++ )
{
for ( j = ( i == 0 ? 0 : m_Boundary[i - 1] + 1 ); j <= m_Boundary[i]; j++ )
{
m_GlobalZHistogram[j] = m_Data[i].m_ZHistogram[j];
}
}
// compute the cumulative frequency distribution using the histogram
m_ZCumulativeFrequency[0] = m_GlobalZHistogram[0];
for ( i = 1; i < m_ZSize; i++ )
{
m_ZCumulativeFrequency[i] = m_ZCumulativeFrequency[i - 1] + m_GlobalZHistogram[i];
}
// now define the boundaries
m_Boundary[m_NumOfThreads - 1] = m_ZSize - 1; // special case: the last bound
for ( i = 0; i < m_NumOfThreads - 1; i++ )
{
// compute m_Boundary[i]
float cutOff = 1.0f * ( i + 1 ) * m_ZCumulativeFrequency[m_ZSize - 1] / m_NumOfThreads;
// find the position in the cumulative freq dist where this cutoff is met
for ( j = ( i == 0 ? 0 : m_Boundary[i - 1] ); j < m_ZSize; j++ )
{
if ( cutOff > m_ZCumulativeFrequency[j] )
{
continue;
}
else
{
// do some optimization !
// go further FORWARD and find the first index (k) in the cumulative
// freq distribution s.t. m_ZCumulativeFrequency[k] !=
// m_ZCumulativeFrequency[j]. This is to be done because if we have a
// flat patch in the cum freq dist then ... . we can choose a bound
// midway in that flat patch
unsigned int k;
for ( k = 1; j + k < m_ZSize; k++ )
{
if ( m_ZCumulativeFrequency[j + k] != m_ZCumulativeFrequency[j] )
{
break;
}
}
// if ALL new boundaries same as the original then NO NEED TO DO
// ThreadedLoadBalance() next !!!
unsigned int newBoundary = static_cast< unsigned int >( ( j + ( j + k ) ) / 2 );
if ( newBoundary != m_Boundary[i] )
{
//
m_BoundaryChanged = true;
m_Boundary[i] = newBoundary;
}
break;
}
}
}
if ( m_BoundaryChanged == false )
{
return;
}
// Reset the individual histograms to reflect the new distrbution
// Also reset the mapping from the Z value --> the thread number i.e.
// m_MapZToThreadNumber[]
for ( i = 0; i < m_NumOfThreads; i++ )
{
if ( i != 0 )
{
for ( j = 0; j <= m_Boundary[i - 1]; j++ )
{
m_Data[i].m_ZHistogram[j] = 0;
}
}
for ( j = ( i == 0 ? 0 : m_Boundary[i - 1] + 1 ); j <= m_Boundary[i]; j++ )
{
// this Z histogram value should be given to thread-i
m_Data[i].m_ZHistogram[j] = m_GlobalZHistogram[j];
// this Z belongs to the region associated with thread-i
m_MapZToThreadNumber[j] = i;
}
for ( j = m_Boundary[i] + 1; j < m_ZSize; j++ )
{
m_Data[i].m_ZHistogram[j] = 0;
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedLoadBalance(ThreadIdType ThreadId)
{
// the situation at this point in time::
// the OPTIMAL boundaries (that divide work equally) have changed but ...
// the thread data lags behind the boundaries (it is still following the old
// boundaries) the m_ZHistogram[], however, reflects the latest optimal
// boundaries
// The task:
// 1. Every thread checks for pixels with itself that should NOT be with
// itself anymore (because of the changed boundaries).
// These pixels are now put in extra "buckets" for other threads to grab
// 2. WaitForAll ().
// 3. Every thread grabs those pixels, from every other thread, that come
// within its boundaries (from the extra buckets).
////////////////////////////////////////////////////
// 1.
unsigned int i;
// cleanup the layers first
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
for ( ThreadIdType tid = 0; tid < m_NumOfThreads; tid++ )
{
if ( tid == ThreadId )
{
// a thread does NOT pass nodes to istelf
continue;
}
ClearList(ThreadId, m_Data[ThreadId].m_LoadTransferBufferLayers[i][tid]);
}
}
LayerNodeType *nodePtr;
// for all layers
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
typename LayerType::Iterator layerIt = m_Data[ThreadId].m_Layers[i]->Begin();
typename LayerType::Iterator layerEnd = m_Data[ThreadId].m_Layers[i]->End();
while ( layerIt != layerEnd )
{
nodePtr = layerIt.GetPointer();
++layerIt;
// use the latest (just updated in CheckLoadBalance) boundaries to
// determine to which thread region does the pixel now belong
ThreadIdType tmpId = this->GetThreadNumber(nodePtr->m_Index[m_SplitAxis]);
if ( tmpId != ThreadId ) // this pixel no longer belongs to this thread
{
// remove from the layer
m_Data[ThreadId].m_Layers[i]->Unlink(nodePtr);
// insert temporarily into the special-layers TO BE LATER taken by the
// other thread
// NOTE: What is pushed is a node belonging to the LayerNodeStore of
// ThreadId. This is deleted later (during the start of the next
// SpecialIteration). What is taken by the other thread is NOT this
// node BUT a copy of it.
m_Data[ThreadId].m_LoadTransferBufferLayers[i][tmpId]->PushFront(nodePtr);
}
}
}
////////////////////////////////////////////////////
// 2.
this->WaitForAll();
////////////////////////////////////////////////////
// 3.
for ( i = 0; i < 2 * static_cast< unsigned int >( m_NumberOfLayers ) + 1; i++ )
{
// check all other threads
for ( ThreadIdType tid = 0; tid < m_NumOfThreads; tid++ )
{
if ( tid == ThreadId )
{
continue; // exclude oneself
}
CopyInsertList(ThreadId, m_Data[tid].m_LoadTransferBufferLayers[i][ThreadId],
m_Data[ThreadId].m_Layers[i]);
}
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::GetThreadRegionSplitByBoundary(ThreadIdType ThreadId, ThreadRegionType & ThreadRegion)
{
// Initialize the ThreadRegion to the output's requested region
ThreadRegion = m_OutputImage->GetRequestedRegion();
// compute lower bound on the index
typename TOutputImage::IndexType threadRegionIndex = ThreadRegion.GetIndex();
if ( ThreadId != 0 )
{
if ( m_Boundary[ThreadId - 1] < m_Boundary[m_NumOfThreads - 1] )
{
threadRegionIndex[m_SplitAxis] += m_Boundary[ThreadId - 1] + 1;
}
else
{
threadRegionIndex[m_SplitAxis] += m_Boundary[ThreadId - 1];
}
}
ThreadRegion.SetIndex (threadRegionIndex);
// compute the size of the region
typename TOutputImage::SizeType threadRegionSize = ThreadRegion.GetSize();
threadRegionSize[m_SplitAxis] = ( ThreadId == 0
? ( m_Boundary[0] + 1 )
: m_Boundary[ThreadId] - m_Boundary[ThreadId - 1] );
ThreadRegion.SetSize(threadRegionSize);
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::GetThreadRegionSplitUniformly(
ThreadIdType ThreadId, ThreadRegionType & ThreadRegion)
{
// Initialize the ThreadRegion to the output's requested region
ThreadRegion = m_OutputImage->GetRequestedRegion();
typename TOutputImage::IndexType threadRegionIndex = ThreadRegion.GetIndex();
threadRegionIndex[m_SplitAxis] +=
static_cast< unsigned int >( 1.0 * ThreadId * m_ZSize / m_NumOfThreads );
ThreadRegion.SetIndex(threadRegionIndex);
typename TOutputImage::SizeType threadRegionSize = ThreadRegion.GetSize();
// compute lower bound on the index and the size of the region
if ( ThreadId < m_NumOfThreads - 1 ) // this is NOT the last thread
{
threadRegionSize[m_SplitAxis] = static_cast< unsigned int >( 1.0 * ( ThreadId + 1 ) * m_ZSize / m_NumOfThreads )
- static_cast< unsigned int >( 1.0 * ThreadId * m_ZSize / m_NumOfThreads );
}
else
{
threadRegionSize[m_SplitAxis] = m_ZSize
- static_cast< unsigned int >( 1.0 * ThreadId * m_ZSize / m_NumOfThreads );
}
ThreadRegion.SetSize(threadRegionSize);
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::ThreadedPostProcessOutput(const ThreadRegionType & regionToProcess)
{
// Assign background pixels INSIDE the sparse field layers to a new level set
// with value less than the innermost layer. Assign background pixels
// OUTSIDE the sparse field layers to a new level set with value greater than
// the outermost layer.
const ValueType max_layer = static_cast< ValueType >( m_NumberOfLayers );
const ValueType outside_value = ( max_layer + 1 ) * m_ConstantGradientValue;
const ValueType inside_value = -( max_layer + 1 ) * m_ConstantGradientValue;
ImageRegionConstIterator< StatusImageType > statusIt(m_StatusImage, regionToProcess);
ImageRegionIterator< OutputImageType > outputIt(m_OutputImage, regionToProcess);
for ( outputIt.GoToBegin(), statusIt.GoToBegin();
!outputIt.IsAtEnd(); ++outputIt, ++statusIt )
{
if ( statusIt.Get() == m_StatusNull || statusIt.Get() == m_StatusBoundaryPixel )
{
if ( outputIt.Get() > m_ValueZero )
{
outputIt.Set (outside_value);
}
else
{
outputIt.Set (inside_value);
}
}
}
}
template< typename TInputImage, typename TOutputImage >
unsigned int
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::GetThreadNumber(unsigned int splitAxisValue)
{
return ( m_MapZToThreadNumber[splitAxisValue] );
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::SignalNeighborsAndWait(ThreadIdType ThreadId)
{
// This is the case when a thread has no pixels to process
// This case is analogous to NOT using that thread at all
// Hence this thread does not need to signal / wait for any other neighbor
// thread during the iteration
if ( ThreadId != 0 )
{
if ( m_Boundary[ThreadId - 1] == m_Boundary[ThreadId] )
{
m_Data[ThreadId].m_SemaphoreArrayNumber = 1
- m_Data[ThreadId].m_SemaphoreArrayNumber;
return;
}
}
ThreadIdType lastThreadId = m_NumOfThreads - 1;
if ( lastThreadId == 0 )
{
return; // only 1 thread => no need to wait
}
// signal neighbors that work is done
if ( ThreadId != 0 ) // not the first thread
{
this->SignalNeighbor( m_Data[ThreadId].m_SemaphoreArrayNumber,
this->GetThreadNumber (m_Boundary[ThreadId - 1]) );
}
if ( m_Boundary[ThreadId] != m_ZSize - 1 ) // not the last thread
{
this->SignalNeighbor ( m_Data[ThreadId].m_SemaphoreArrayNumber,
this->GetThreadNumber (m_Boundary[ThreadId] + 1) );
}
// wait for signal from neighbors signifying that their work is done
if ( ( ThreadId == 0 ) || ( m_Boundary[ThreadId] == m_ZSize - 1 ) )
{
// do it just once for the first and the last threads because they share
// just 1 boundary (just 1 neighbor)
this->WaitForNeighbor (m_Data[ThreadId].m_SemaphoreArrayNumber, ThreadId);
m_Data[ThreadId].m_SemaphoreArrayNumber = 1 - m_Data[ThreadId].m_SemaphoreArrayNumber;
}
else
{
// do twice because share 2 boundaries with neighbors
this->WaitForNeighbor (m_Data[ThreadId].m_SemaphoreArrayNumber, ThreadId);
this->WaitForNeighbor (m_Data[ThreadId].m_SemaphoreArrayNumber, ThreadId);
m_Data[ThreadId].m_SemaphoreArrayNumber = 1 - m_Data[ThreadId].m_SemaphoreArrayNumber;
}
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::SignalNeighbor(
unsigned int SemaphoreArrayNumber,
ThreadIdType ThreadId)
{
ThreadData &td = m_Data[ThreadId];
td.m_Lock[SemaphoreArrayNumber].Lock();
++td.m_Semaphore[SemaphoreArrayNumber];
td.m_Condition[SemaphoreArrayNumber]->Signal();
td.m_Lock[SemaphoreArrayNumber].Unlock();
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::WaitForNeighbor(unsigned int SemaphoreArrayNumber, ThreadIdType ThreadId)
{
ThreadData &td = m_Data[ThreadId];
td.m_Lock[SemaphoreArrayNumber].Lock();
if ( td.m_Semaphore[SemaphoreArrayNumber] == 0 )
{
td.m_Condition[SemaphoreArrayNumber]->Wait( & td.m_Lock[SemaphoreArrayNumber]);
}
--td.m_Semaphore[SemaphoreArrayNumber];
td.m_Lock[SemaphoreArrayNumber].Unlock();
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::WaitForAll()
{
m_Barrier->Wait();
}
template< typename TInputImage, typename TOutputImage >
void
ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
unsigned int i;
os << indent << "m_NumberOfLayers: " << NumericTraits< StatusType >::PrintType( this->GetNumberOfLayers() )
<< std::endl;
os << indent << "m_IsoSurfaceValue: " << this->GetIsoSurfaceValue() << std::endl;
os << indent << "m_LayerNodeStore: " << m_LayerNodeStore;
ThreadIdType ThreadId;
for ( ThreadId = 0; ThreadId < m_NumOfThreads; ThreadId++ )
{
os << indent << "ThreadId: " << ThreadId << std::endl;
if ( m_Data != ITK_NULLPTR )
{
for ( i = 0; i < m_Data[ThreadId].m_Layers.size(); i++ )
{
os << indent << "m_Layers[" << i << "]: size="
<< m_Data[ThreadId].m_Layers[i]->Size() << std::endl;
os << indent << m_Data[ThreadId].m_Layers[i];
}
}
}
}
} // end namespace itk
#endif
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