1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303
|
/*
//
// Copyright 1997-2009 Torsten Rohlfing
//
// Copyright 2004-2012 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 <cmtkconfig.h>
#include <System/cmtkCommandLine.h>
#include <System/cmtkExitException.h>
#include <System/cmtkConsole.h>
#include <System/cmtkDebugOutput.h>
#include <System/cmtkProgressConsole.h>
#include <Base/cmtkUniformVolume.h>
#include <Base/cmtkTypedArray.h>
#include <Base/cmtkHistogram.h>
#include <Base/cmtkMathUtil.h>
#include <Base/cmtkMathFunctionWrappers.h>
#include <IO/cmtkVolumeIO.h>
#include <math.h>
#include <list>
#include <algorithm>
#include <limits>
const char* OutputFileName = "average.nii";
bool ApplyLog = false;
bool ApplyAbs = false;
bool Normalize = false;
bool Padding = false;
cmtk::Types::DataItem PaddingValue = 0;
size_t NumberHistogramBins = 64;
typedef enum
{
MODE_AVG,
MODE_STDEV,
MODE_VAR,
MODE_ZSCORE,
MODE_ENTROPY
} ModeEnum;
ModeEnum Mode = MODE_AVG;
cmtk::ScalarDataType DataType = cmtk::TYPE_FLOAT;
std::list<const char*> imagePathList;
void
GetNormalizationCoefficients
( const cmtk::TypedArray* floatingData, const cmtk::Types::DataItem refMean, const cmtk::Types::DataItem refVariance, cmtk::Types::DataItem& scale, cmtk::Types::DataItem& offset )
{
cmtk::Types::DataItem fltMean, fltVariance;
floatingData->GetStatistics( fltMean, fltVariance );
scale = sqrt( refVariance ) / sqrt( fltVariance );
offset = refMean - scale * fltMean;
cmtk::DebugOutput( 1 ).GetStream().printf( "Converted grey values: %f +- %f -> %f +- %f\n", fltMean, sqrt( fltVariance ), refMean, sqrt( refVariance ) );
}
int
doMain( const int argc, const char* argv[] )
{
try
{
cmtk::CommandLine cl;
cl.SetProgramInfo( cmtk::CommandLine::PRG_TITLE, "Average images" );
cl.SetProgramInfo( cmtk::CommandLine::PRG_DESCR, "This tool computes pixelwiase average, variance, standard deviation, z-score, or entropy images from a list of user-provided intensity images." );
cl.SetProgramInfo( cmtk::CommandLine::PRG_SYNTX, "average_images [options] image0 ..." );
typedef cmtk::CommandLine::Key Key;
cmtk::CommandLine::EnumGroup<ModeEnum>::SmartPtr modeGroup = cl.AddEnum( "mode", &Mode, "Mode of averaging operation" );
modeGroup->AddSwitch( Key( "avg" ), MODE_AVG, "Compute average (i.e., mean) image" );
modeGroup->AddSwitch( Key( "var" ), MODE_VAR, "Compute variance image" );
modeGroup->AddSwitch( Key( "stdev" ), MODE_STDEV, "Compute standard deviation image" );
modeGroup->AddSwitch( Key( "zscore" ), MODE_ZSCORE, "Compute z-score image" );
modeGroup->AddSwitch( Key( "entropy" ), MODE_ENTROPY, "Compute pixel-by-pixel population entropy image" );
cl.BeginGroup( "Preprocessing", "Data Preprocessing" );
cl.AddSwitch( Key( 'l', "log" ), &ApplyLog, true, "Apply log to input data" );
cl.AddSwitch( Key( 'a', "abs" ), &ApplyAbs, true, "Use absolute input values" );
cl.AddSwitch( Key( 'n', "normalize-mean-stdev" ), &Normalize, true, "Normalize image intensities using means and standard deviations" );
cl.AddOption( Key( "set-padding-value" ), &PaddingValue, "Define padding value in input images", &Padding );
cl.EndGroup();
cl.BeginGroup( "Output", "Output Options" );
cl.AddOption( Key( 'o', "outfile-name" ), &OutputFileName, "Output file name" );
cmtk::CommandLine::EnumGroup<cmtk::ScalarDataType>::SmartPtr typeGroup = cl.AddEnum( "type", &DataType, "Scalar data type of output image." );
typeGroup->AddSwitch( Key( "float" ), cmtk::TYPE_FLOAT, "Single-precision float." );
typeGroup->AddSwitch( Key( "double" ), cmtk::TYPE_DOUBLE, "Double-precision float." );
cl.EndGroup();
cl.Parse( argc, argv );
const char* next = cl.GetNext();
while ( next )
{
imagePathList.push_back( next );
next = cl.GetNextOptional();
}
}
catch ( const cmtk::CommandLine::Exception& e )
{
cmtk::StdErr << e << "\n";
throw cmtk::ExitException(1);
}
cmtk::UniformVolume::SmartPtr volume( NULL );
cmtk::TypedArray::SmartPtr outputData( NULL );
bool firstImage = true;
cmtk::Types::DataItem refMean, refVariance;
cmtk::Types::DataItemRange imagesValueRange( 0, 0 );
std::list<cmtk::TypedArray::SmartPtr> dataList;
std::list<const char*>::const_iterator it;
for ( it = imagePathList.begin(); it != imagePathList.end(); ++it )
{
cmtk::UniformVolume::SmartPtr nextVolume( cmtk::VolumeIO::ReadOriented( *it) );
if ( ! nextVolume )
{
cmtk::StdErr << "ERROR: Could not open image " << *it << "\n";
throw cmtk::ExitException( 1 );
}
if ( ! volume )
{
volume = nextVolume;
}
cmtk::TypedArray::SmartPtr data = nextVolume->GetData();
data->Convert( DataType );
if ( Padding )
{
data->SetPaddingValue( PaddingValue );
}
if ( ApplyLog )
{
data->ApplyFunctionDouble( cmtk::Wrappers::Log );
}
if ( ApplyAbs )
{
data->ApplyFunctionDouble( cmtk::Wrappers::Abs );
}
if ( Normalize )
{
if ( firstImage )
{
firstImage = false;
data->GetStatistics( refMean, refVariance );
}
else
{
cmtk::Types::DataItem normFactor, normOffset;
GetNormalizationCoefficients( data, refMean, refVariance, normFactor, normOffset );
data->Rescale( normFactor, normOffset );
}
}
const cmtk::Types::DataItemRange dataRange = data->GetRange();
if ( firstImage )
{
imagesValueRange = dataRange;
}
else
{
imagesValueRange.m_LowerBound = std::min( imagesValueRange.m_LowerBound, dataRange.m_LowerBound );
imagesValueRange.m_UpperBound = std::min( imagesValueRange.m_UpperBound, dataRange.m_UpperBound );
}
dataList.push_back( data );
}
// this is only used in "Entropy" mode, but we'll instantiate it anyway to save time
cmtk::Histogram<float> histogram( NumberHistogramBins );
histogram.SetRange( imagesValueRange );
if ( ! outputData )
{
outputData = cmtk::TypedArray::SmartPtr( cmtk::TypedArray::Create( DataType, volume->GetNumberOfPixels() ) );
outputData->SetPaddingValue( std::numeric_limits<float>::signaling_NaN() );
}
cmtk::ProgressConsole progressIndicator;
const int pixelsPerPercent = volume->GetNumberOfPixels() / 100;
cmtk::Progress::Begin( 0, 100, 1, "Image averaging" );
std::vector<cmtk::Types::DataItem> pixelData( dataList.size() );
for ( size_t i = 0; i < volume->GetNumberOfPixels(); ++i )
{
if ( !(i % pixelsPerPercent) )
cmtk::Progress::SetProgress( i / pixelsPerPercent );
pixelData.resize( dataList.size() );
size_t actualSize = 0;
std::list<cmtk::TypedArray::SmartPtr>::const_iterator dit;
for ( dit = dataList.begin(); dit != dataList.end(); ++dit )
{
cmtk::Types::DataItem v;
if ( (*dit)->Get( v, i ) )
{
pixelData[actualSize++] = v;
}
}
if ( actualSize )
{
pixelData.resize( actualSize );
switch ( Mode )
{
case MODE_AVG:
{
const cmtk::Types::DataItem avg = cmtk::MathUtil::Mean<cmtk::Types::DataItem>( pixelData );
outputData->Set( avg, i );
break;
}
case MODE_VAR:
{
const cmtk::Types::DataItem avg = cmtk::MathUtil::Mean<cmtk::Types::DataItem>( pixelData );
const cmtk::Types::DataItem var = cmtk::MathUtil::Variance<cmtk::Types::DataItem>( pixelData, avg );
outputData->Set( var, i );
break;
}
case MODE_STDEV:
{
const cmtk::Types::DataItem avg = cmtk::MathUtil::Mean<cmtk::Types::DataItem>( pixelData );
const cmtk::Types::DataItem var = cmtk::MathUtil::Variance<cmtk::Types::DataItem>( pixelData, avg );
outputData->Set( sqrt(var), i );
break;
}
case MODE_ENTROPY:
{
histogram.Reset();
for ( size_t idx = 0; idx < actualSize; ++idx )
histogram.IncrementFractional( histogram.ValueToBinFractional( pixelData[idx] ) );
outputData->Set( histogram.GetEntropy(), i );
break;
}
case MODE_ZSCORE:
{
const cmtk::Types::DataItem avg = cmtk::MathUtil::Mean<cmtk::Types::DataItem>( pixelData );
const cmtk::Types::DataItem var = cmtk::MathUtil::Variance<cmtk::Types::DataItem>( pixelData, avg );
outputData->Set( avg / sqrt(var), i );
break;
}
}
}
else
{
outputData->SetPaddingAt( i );
}
}
cmtk::Progress::Done();
volume->SetData( outputData );
cmtk::VolumeIO::Write( *volume, OutputFileName );
return 0;
}
#include "cmtkSafeMain"
|