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/*
* Copyright (c) 2008-2018 the MRtrix3 contributors.
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, you can obtain one at http://mozilla.org/MPL/2.0/
*
* MRtrix3 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.
*
* For more details, see http://www.mrtrix.org/
*/
#include <map>
#include "command.h"
#include "image.h"
#include "image_helpers.h"
#include "memory.h"
#include "progressbar.h"
#include "types.h"
#include "algo/loop.h"
#include "filter/optimal_threshold.h"
using namespace MR;
using namespace App;
void usage ()
{
AUTHOR = "J-Donald Tournier (jdtournier@gmail.com)";
SYNOPSIS = "Create bitwise image by thresholding image intensity";
DESCRIPTION
+ "By default, an optimal threshold is determined using a parameter-free method. "
"Alternatively the threshold can be defined manually by the user.";
REFERENCES
+ "* If not using any manual thresholding option:\n"
"Ridgway, G. R.; Omar, R.; Ourselin, S.; Hill, D. L.; Warren, J. D. & Fox, N. C. "
"Issues with threshold masking in voxel-based morphometry of atrophied brains. "
"NeuroImage, 2009, 44, 99-111";
ARGUMENTS
+ Argument ("input", "the input image to be thresholded.").type_image_in ()
+ Argument ("output", "the output binary image mask.").type_image_out ();
OPTIONS
+ Option ("abs", "specify threshold value as absolute intensity.")
+ Argument ("value").type_float()
+ Option ("percentile", "threshold the image at the ith percentile.")
+ Argument ("value").type_float (0.0, 100.0)
+ Option ("top", "provide a mask of the N top-valued voxels")
+ Argument ("N").type_integer (0)
+ Option ("bottom", "provide a mask of the N bottom-valued voxels")
+ Argument ("N").type_integer (0)
+ Option ("invert", "invert output binary mask.")
+ Option ("toppercent", "provide a mask of the N%% top-valued voxels")
+ Argument ("N").type_float (0.0, 100.0)
+ Option ("bottompercent", "provide a mask of the N%% bottom-valued voxels")
+ Argument ("N").type_float (0.0, 100.0)
+ Option ("nan", "use NaN as the output zero value.")
+ Option ("ignorezero", "ignore zero-valued input voxels.")
+ Option ("mask", "compute the optimal threshold based on voxels within a mask.")
+ Argument ("image").type_image_in ();
}
void run ()
{
default_type threshold_value (NaN), percentile (NaN), bottomNpercent (NaN), topNpercent (NaN);
size_t topN (0), bottomN (0), nopt (0);
auto opt = get_options ("abs");
if (opt.size()) {
threshold_value = opt[0][0];
++nopt;
}
opt = get_options ("percentile");
if (opt.size()) {
percentile = opt[0][0];
++nopt;
}
opt = get_options ("top");
if (opt.size()) {
topN = opt[0][0];
++nopt;
}
opt = get_options ("bottom");
if (opt.size()) {
bottomN = opt[0][0];
++nopt;
}
opt = get_options ("toppercent");
if (opt.size()) {
topNpercent = opt[0][0];
++nopt;
}
opt = get_options ("bottompercent");
if (opt.size()) {
bottomNpercent = opt[0][0];
++nopt;
}
if (nopt > 1)
throw Exception ("too many conflicting options");
bool invert = get_options ("invert").size();
const bool use_NaN = get_options ("nan").size();
const bool ignore_zeroes = get_options ("ignorezero").size();
auto header = Header::open (argument[0]);
if (header.datatype().is_complex())
throw Exception ("Cannot perform thresholding on complex images");
auto in = header.get_image<float>();
if (voxel_count (in) < topN || voxel_count (in) < bottomN)
throw Exception ("number of voxels at which to threshold exceeds number of voxels in image");
if (std::isfinite (percentile)) {
percentile /= 100.0;
if (percentile < 0.5) {
bottomN = std::round (voxel_count (in) * percentile);
invert = !invert;
}
else topN = std::round (voxel_count (in) * (1.0 - percentile));
}
header.datatype() = use_NaN ? DataType::Float32 : DataType::Bit;
auto out = Image<float>::create (argument[1], header);
float zero = use_NaN ? NaN : 0.0;
float one = 1.0;
if (invert) std::swap (zero, one);
if (std::isfinite (topNpercent) || std::isfinite (bottomNpercent)) {
size_t count = 0;
for (auto l = Loop("computing voxel count", in) (in); l; ++l) {
if (ignore_zeroes && in.value() == 0.0) continue;
++count;
}
if (std::isfinite (topNpercent))
topN = std::round (0.01 * topNpercent * count);
else
bottomN = std::round (0.01 * bottomNpercent * count);
}
if (topN || bottomN) {
std::multimap<float,vector<ssize_t> > list;
{
const std::string msg = "thresholding \"" + shorten (in.name()) + "\" at " + (
std::isnan (percentile) ?
(str (topN ? topN : bottomN) + "th " + (topN ? "top" : "bottom") + " voxel") :
(str (percentile*100.0) + "\% percentile"));
if (topN) {
for (auto l = Loop(in) (in); l; ++l) {
const float val = in.value();
if (!std::isfinite (val)) continue;
if (ignore_zeroes && val == 0.0) continue;
if (list.size() == topN) {
if (val < list.begin()->first) continue;
list.erase (list.begin());
}
vector<ssize_t> pos (in.ndim());
for (size_t n = 0; n < in.ndim(); ++n)
pos[n] = in.index(n);
list.insert (std::pair<float,vector<ssize_t> > (val, pos));
}
}
else {
for (auto l = Loop(in) (in); l; ++l) {
const float val = in.value();
if (!std::isfinite (val)) continue;
if (ignore_zeroes && val == 0.0) continue;
if (list.size() == bottomN) {
std::multimap<float,vector<ssize_t> >::iterator i = list.end();
--i;
if (val > i->first) continue;
list.erase (i);
}
vector<ssize_t> pos (in.ndim());
for (size_t n = 0; n < in.ndim(); ++n)
pos[n] = in.index(n);
list.insert (std::pair<float,vector<ssize_t> > (val, pos));
}
}
}
for (auto l = Loop(out) (out); l; ++l)
out.value() = zero;
for (std::multimap<float,vector<ssize_t> >::const_iterator i = list.begin(); i != list.end(); ++i) {
for (size_t n = 0; n < out.ndim(); ++n)
out.index(n) = i->second[n];
out.value() = one;
}
}
else {
Image<bool> mask;
opt = get_options ("mask");
if (opt.size())
mask = Image<bool>::open (opt[0][0]);
if (std::isnan (threshold_value))
threshold_value = Filter::estimate_optimal_threshold (in, mask);
const std::string msg = "thresholding \"" + shorten (in.name()) + "\" at intensity " + str (threshold_value);
for (auto l = Loop(msg, in) (in, out); l; ++l) {
const float val = in.value();
out.value() = ( !std::isfinite (val) || val < threshold_value ) ? zero : one;
}
}
}
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