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/* -*- mia-c++ -*-
*
* This file is part of MIA - a toolbox for medical image analysis
* Copyright (c) Leipzig, Madrid 1999-2016 Gert Wollny
*
* MIA 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.
*
* This program 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 MIA; if not, see <http://www.gnu.org/licenses/>.
*
*/
#include <iostream>
#include <iomanip>
#include <string>
#include <limits>
#include <sstream>
#include <stdexcept>
//#include <boost/algorithm/minmax_element.hpp>
#include <mia/2d/filter.hh>
#include <mia/2d/imageio.hh>
#include <mia/2d/segsetwithimages.hh>
#include <mia/core.hh>
using namespace std;
using namespace mia;
const SProgramDescription g_description = {
{pdi_group, "Tools for Myocardial Perfusion Analysis"},
{pdi_short, "Evaluate the time-intensity gradient variation in a series of images."},
{pdi_description, "Given a set of images of temporal sucession, this program evaluates the "
"gradient variation of the pixel-wise time-intensity curves of this series. "
"If the input image set provides a segmentation, then this segmentation can "
"be used to create a bounding box and restrict evaluation to this box. "},
{pdi_example_descr, "Evaluate the gradient-variation image of the bounding box surrounding the segmentation "
"from a series 'segment.set'. The bounding box will be enlarged by 3 pixels in all directions. "
"Store the image in OpenEXR format."},
{pdi_example_code, " -i segment.set -o gradvar.exr -c -e 3"}
};
struct C2DVarAccumulator : public TFilter<bool> {
C2DVarAccumulator():
m_min(numeric_limits<float>::max()),
m_max(-numeric_limits<float>::max()),
m_n(0)
{
}
template <typename T>
bool operator ()(const T2DImage<T>& image)
{
if (m_n) {
if (image.get_size() != m_old.get_size())
throw invalid_argument("Input image and mask differ in size");
transform(image.begin(), image.end(), m_old.begin(), m_delta.begin(),
[](float x, float y){return fabs(x - y);});
transform(m_delta.begin(), m_delta.end(), m_sum.begin(), m_sum.begin(),
[](float x, float y){return x + y;});
transform(m_delta.begin(), m_delta.end(), m_sum2.begin(), m_sum2.begin(),
[](float x, float y){return x * x + y;});
auto src_minmax = minmax_element(image.begin(), image.end());
if (m_min > *src_minmax.first)
m_min = *src_minmax.first;
if (m_max < *src_minmax.second)
m_max = *src_minmax.second;
}else{
m_old = C2DFImage(image.get_size());
m_delta = C2DFImage(image.get_size());
m_sum = C2DFImage(image.get_size());
m_sum2 = C2DFImage(image.get_size());
}
copy(image.begin(), image.end(), m_old.begin());
++m_n;
return true;
}
P2DImage result() const {
float range = 255.0 / (m_max - m_min);
cvdebug() << "all over range = " << range << ": (" << m_min << ", " << m_max << ")\n";
C2DFImage *variation = new C2DFImage(m_sum2.get_size());
float n = m_n - 1;
transform(m_sum2.begin(), m_sum2.end(), m_sum.begin(), variation->begin(),
[n](float sum2, float sum){ return (sum2 - sum * sum / n )/ (n - 1);});
transform(variation->begin(), variation->end(), variation->begin(),
[range](float x) {return range * sqrt(x);});
return P2DImage(variation);
}
private:
float m_min;
float m_max;
C2DFImage m_old;
C2DFImage m_delta;
C2DFImage m_sum;
C2DFImage m_sum2;
size_t m_n;
};
int do_main( int argc, char *argv[] )
{
string in_filename;
string out_filename;
string out_type;
bool crop;
size_t skip = 0;
size_t enlarge_boundary = 5;
const auto& imageio = C2DImageIOPluginHandler::instance();
CCmdOptionList options(g_description);
options.add(make_opt( in_filename, "in-file", 'i', "input segmentation set", CCmdOptionFlags::required_input));
options.add(make_opt( out_filename, "out-file", 'o', "output file name", CCmdOptionFlags::required_output, &imageio));
options.add(make_opt( skip, "skip", 'k', "Skip files at the beginning"));
options.add(make_opt( enlarge_boundary, "enlarge-boundary", 'e', "Enlarge cropbox by number of pixels"));
options.add(make_opt( crop, "crop", 'c', "crop image before running statistics"));
if (options.parse(argc, argv) != CCmdOptionList::hr_no)
return EXIT_SUCCESS;
cvdebug() << "IO supported types: " << imageio.get_plugin_names() << "\n";
if ( in_filename.empty() )
throw runtime_error("'--in-file' ('i') option required");
if ( out_filename.empty() )
throw runtime_error("'--out-base' ('o') option required");
CSegSetWithImages segset(in_filename, true);
P2DFilter crop_filter;
if (crop) {
C2DBoundingBox box = segset.get_boundingbox();
box.enlarge(enlarge_boundary);
stringstream crop_descr;
crop_descr << "crop:"
<< "start=[" << box.get_grid_begin()
<< "],end=[" << box.get_grid_end() << "]";
cvdebug() << "Crop with " << crop_descr.str() << "\r";
crop_filter = C2DFilterPluginHandler::instance().
produce(crop_descr.str().c_str());
}
if (skip >= segset.get_images().size())
throw invalid_argument("Skip is equal or larger then image series");
C2DImageSeries::const_iterator iimages = segset.get_images().begin();
C2DImageSeries::const_iterator eimages = segset.get_images().end();
advance(iimages, skip);
C2DVarAccumulator acc;
for (; iimages != eimages; ++iimages) {
P2DImage in_image = *iimages;
if (crop)
in_image = crop_filter->filter(*in_image);
mia::accumulate(acc, *in_image);
}
if (save_image(out_filename, acc.result()))
return EXIT_SUCCESS;
return EXIT_FAILURE;
}
#include <mia/internal/main.hh>
MIA_MAIN(do_main);
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