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/*
//
// 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 <Base/cmtkValueSequence.h>
#include <Registration/cmtkTypedArraySimilarity.h>
#include <IO/cmtkVolumeIO.h>
#include <vector>
#include <string>
int
doMain
( const int argc, const char *argv[] )
{
std::vector<std::string> imagePaths;
int sliceAxis = cmtk::AXIS_Z;
cmtk::TypedArraySimilarity::ID metric = cmtk::TypedArraySimilarity::CC;
cmtk::Types::DataItem standardDeviationsThreshold = 3.0;
size_t badSlicesThresh = 0;
try
{
cmtk::CommandLine cl;
cl.SetProgramInfo( cmtk::CommandLine::PRG_TITLE, "Find bad slices in a time series of interleaved images (e.g., a resting-state fMRI series)." );
cl.SetProgramInfo( cmtk::CommandLine::PRG_DESCR, "This tool reads a time series of 3D images and detects outliers." );
cl.AddParameterVector( &imagePaths, "ImagePaths", "List of file system paths for all images in the time series.");
typedef cmtk::CommandLine::Key Key;
cl.BeginGroup( "Input", "Input Options" );
cmtk::CommandLine::EnumGroup<int>::SmartPtr sliceGroup = cl.AddEnum( "slice-orientation", &sliceAxis, "Define slice orientation of the diffusion images." );
sliceGroup->AddSwitch( Key( "axial" ), (int)cmtk::AXIS_Z, "Axial slices" );
sliceGroup->AddSwitch( Key( "sagittal" ),(int)cmtk::AXIS_X, "Sagittal slices" );
sliceGroup->AddSwitch( Key( "coronal" ), (int)cmtk::AXIS_Y, "Coronal slices" );
sliceGroup->AddSwitch( Key( "slice-x" ), (int)cmtk::AXIS_X, "X coordinate axis is slice direction" );
sliceGroup->AddSwitch( Key( "slice-y" ), (int)cmtk::AXIS_Y, "Y coordinate axis is slice direction" );
sliceGroup->AddSwitch( Key( "slice-z" ), (int)cmtk::AXIS_Z, "Z coordinate axis is slice direction" );
cl.EndGroup();
cl.BeginGroup( "detection", "Bad Slice Detection" );
cmtk::CommandLine::EnumGroup<cmtk::TypedArraySimilarity::ID>::SmartPtr metricGroup = cl.AddEnum( "metric", &metric, "Image-to-image similarity metric to compare neighbouring slices." );
metricGroup->AddSwitch( Key( "ncc" ), cmtk::TypedArraySimilarity::CC, "Normalized cross correlation." );
metricGroup->AddSwitch( Key( "rms" ), cmtk::TypedArraySimilarity::MSD, "Root of mean squared differences." );
cl.AddOption( Key( "stdev-thresh" ), &standardDeviationsThreshold, "Threshold for bad slice identification in units of intensity standard deviations over all corresponding slices from the remaining diffusion images." );
cl.EndGroup();
cl.BeginGroup( "output", "Output Options" );
cl.AddOption( Key( "bad-slices-thresh" ), &badSlicesThresh, "Minimum number of detected bad slices before reporting a volume (only number of detected bad slices is reported in this case, rather than each slice separately)." );
cl.EndGroup();
cl.Parse( argc, argv );
}
catch ( const cmtk::CommandLine::Exception& e )
{
cmtk::StdErr << e << "\n";
throw cmtk::ExitException( 1 );
}
// read all diffusion images and make sure their grids match
std::vector<cmtk::UniformVolume::SmartConstPtr> images( imagePaths.size() );
for ( size_t i = 0; i < imagePaths.size(); ++i )
{
images[i] = cmtk::UniformVolume::SmartConstPtr( cmtk::VolumeIO::Read( imagePaths[i] ) );
if ( i && ! images[0]->GridMatches( *images[i] ) )
{
cmtk::StdErr << "ERROR: geometry of image '" << imagePaths[i] << "' does not match that of image '" << imagePaths[0] << "'\n";
throw cmtk::ExitException( 1 );
}
}
// Build slice pair difference tables and statistics
std::vector< cmtk::ValueSequence<double> > slicePairStatistics( images[0]->m_Dims[sliceAxis]-1 );
std::vector< std::vector< double> > slicePairSamples( images[0]->m_Dims[sliceAxis]-1 );
for ( int slice = 0; slice < images[0]->m_Dims[sliceAxis]-1; ++slice )
{
slicePairSamples[slice].resize( images.size() );
for ( size_t i = 0; i < images.size(); ++i )
{
double difference = 0;
switch ( metric )
{
case cmtk::TypedArraySimilarity::CC:
difference = cmtk::TypedArraySimilarity::GetCrossCorrelation( images[i]->ExtractSlice( sliceAxis, slice )->GetData(), images[i]->ExtractSlice( sliceAxis, slice+1 )->GetData() );
break;
case cmtk::TypedArraySimilarity::MSD:
difference = sqrt( fabs( cmtk::TypedArraySimilarity::GetMinusMeanSquaredDifference( images[i]->ExtractSlice( sliceAxis, slice )->GetData(), images[i]->ExtractSlice( sliceAxis, slice+1 )->GetData() ) ) );
break;
default:
break;
}
slicePairSamples[slice][i] = difference;
slicePairStatistics[slice].Proceed( difference );
}
}
// Search for outliers
std::vector<double> means( images[0]->m_Dims[sliceAxis]-1 );
std::vector<double> sdevs( images[0]->m_Dims[sliceAxis]-1 );
for ( int slice = 0; slice < images[0]->m_Dims[sliceAxis]-1; ++slice )
{
means[slice] = slicePairStatistics[slice].GetAverage();
sdevs[slice] = sqrt( slicePairStatistics[slice].GetVariance() );
}
for ( size_t i = 0; i < images.size(); ++i )
{
if ( badSlicesThresh )
{
size_t badSlices = 0;
for ( int slice = 0; slice < images[0]->m_Dims[sliceAxis]-1; ++slice )
{
if ( fabs( slicePairSamples[slice][i]-means[slice] ) / sdevs[slice] > standardDeviationsThreshold )
++badSlices;
}
if ( badSlices >= badSlicesThresh )
{
cmtk::StdOut << imagePaths[i] << "\t" << badSlices << "\n";
}
}
else
{
for ( int slice = 0; slice < images[0]->m_Dims[sliceAxis]-1; ++slice )
{
if ( fabs( slicePairSamples[slice][i]-means[slice] ) / sdevs[slice] > standardDeviationsThreshold )
cmtk::StdOut << imagePaths[i] << "\t" << slice << "\n";
}
}
}
return 0;
}
#include "cmtkSafeMain"
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