void run ()
{
Image::Header H_in (argument[0]);
DWI::Tractography::ACT::verify_5TT_image (H_in);
Image::Buffer<float> in (H_in);
Image::Header H_out (in);
H_out.set_ndim (3);
H_out.datatype() = DataType::Float32;
Options
opt = get_options ("bg"); const float bg_multiplier = opt.size() ? opt[0][0] : VALUE_DEFAULT_BG;
opt = get_options ("cgm"); const float cgm_multiplier = opt.size() ? opt[0][0] : VALUE_DEFAULT_CGM;
opt = get_options ("sgm"); const float sgm_multiplier = opt.size() ? opt[0][0] : VALUE_DEFAULT_SGM;
opt = get_options ("wm"); const float wm_multiplier = opt.size() ? opt[0][0] : VALUE_DEFAULT_WM;
opt = get_options ("csf"); const float csf_multiplier = opt.size() ? opt[0][0] : VALUE_DEFAULT_CSF;
opt = get_options ("path"); const float path_multiplier = opt.size() ? opt[0][0] : VALUE_DEFAULT_PATH;
Image::Buffer<float> out (argument[1], H_out);
auto v_in = in.voxel();
auto v_out = out.voxel();
auto f = [&] (decltype(v_in)& in, decltype(v_out)& out) {
const DWI::Tractography::ACT::Tissues t (in);
const float bg = 1.0 - (t.get_cgm() + t.get_sgm() + t.get_wm() + t.get_csf() + t.get_path());
out.value() = (bg_multiplier * bg) + (cgm_multiplier * t.get_cgm()) + (sgm_multiplier * t.get_sgm())
+ (wm_multiplier * t.get_wm()) + (csf_multiplier * t.get_csf()) + (path_multiplier * t.get_path());
};
Image::ThreadedLoop (v_out, 0, 3).run (f, v_in, v_out);
}
Dynamic::Dynamic (const std::string& in, Image::Buffer<float>& fod_data, const Math::RNG& rng, const DWI::Directions::FastLookupSet& dirs) :
Base (in, rng, "dynamic", MAX_TRACKING_SEED_ATTEMPTS_DYNAMIC),
SIFT::ModelBase<Fixel_TD_seed> (fod_data, dirs),
total_samples (0),
total_seeds (0),
transform (SIFT::ModelBase<Fixel_TD_seed>::info())
#ifdef DYNAMIC_SEED_DEBUGGING
, seed_output ("seeds.tck", Tractography::Properties())
#endif
{
App::Options opt = App::get_options ("act");
if (opt.size())
act = new Dynamic_ACT_additions (opt[0][0]);
perform_FOD_segmentation (fod_data);
// Have to set a volume so that Seeding::List works correctly
for (std::vector<Fixel>::const_iterator i = fixels.begin(); i != fixels.end(); ++i)
volume += i->get_weight();
volume *= (fod_data.vox(0) * fod_data.vox(1) * fod_data.vox(2));
// Prevent divide-by-zero at commencement
SIFT::ModelBase<Fixel_TD_seed>::TD_sum = DYNAMIC_SEED_INITIAL_TD_SUM;
}
void run ()
{
Image::Header H (argument[0]);
Image::Info info (H);
info.set_ndim (3);
Image::BufferScratch<bool> mask (info);
auto v_mask = mask.voxel();
std::string mask_path;
Options opt = get_options ("mask");
if (opt.size()) {
mask_path = std::string(opt[0][0]);
Image::Buffer<bool> in (mask_path);
if (!Image::dimensions_match (H, in, 0, 3))
throw Exception ("Input mask image does not match DWI");
if (!(in.ndim() == 3 || (in.ndim() == 4 && in.dim(3) == 1)))
throw Exception ("Input mask image must be a 3D image");
auto v_in = in.voxel();
Image::copy (v_in, v_mask, 0, 3);
} else {
for (auto l = Image::LoopInOrder (v_mask) (v_mask); l; ++l)
v_mask.value() = true;
}
DWI::CSDeconv<float>::Shared shared (H);
const size_t lmax = DWI::lmax_for_directions (shared.DW_dirs);
if (lmax < 4)
throw Exception ("Cannot run dwi2response with lmax less than 4");
shared.lmax = lmax;
Image::BufferPreload<float> dwi (H, Image::Stride::contiguous_along_axis (3));
DWI::Directions::Set directions (1281);
Math::Vector<float> response (lmax/2+1);
response.zero();
{
// Initialise response function
// Use lmax = 2, get the DWI intensity mean and standard deviation within the mask and
// use these as the first two coefficients
auto v_dwi = dwi.voxel();
double sum = 0.0, sq_sum = 0.0;
size_t count = 0;
Image::LoopInOrder loop (dwi, "initialising response function... ", 0, 3);
for (auto l = loop (v_dwi, v_mask); l; ++l) {
if (v_mask.value()) {
for (size_t volume_index = 0; volume_index != shared.dwis.size(); ++volume_index) {
v_dwi[3] = shared.dwis[volume_index];
const float value = v_dwi.value();
sum += value;
sq_sum += Math::pow2 (value);
++count;
}
}
}
response[0] = sum / double (count);
response[1] = - 0.5 * std::sqrt ((sq_sum / double(count)) - Math::pow2 (response[0]));
// Account for scaling in SH basis
response *= std::sqrt (4.0 * Math::pi);
}
INFO ("Initial response function is [" + str(response, 2) + "]");
// Algorithm termination options
opt = get_options ("max_iters");
const size_t max_iters = opt.size() ? int(opt[0][0]) : DWI2RESPONSE_DEFAULT_MAX_ITERS;
opt = get_options ("max_change");
const float max_change = 0.01 * (opt.size() ? float(opt[0][0]) : DWI2RESPONSE_DEFAULT_MAX_CHANGE);
// Should all voxels (potentially within a user-specified mask) be tested at every iteration?
opt = get_options ("test_all");
const bool reset_mask = opt.size();
// Single-fibre voxel selection options
opt = get_options ("volume_ratio");
const float volume_ratio = opt.size() ? float(opt[0][0]) : DWI2RESPONSE_DEFAULT_VOLUME_RATIO;
opt = get_options ("dispersion_multiplier");
const float dispersion_multiplier = opt.size() ? float(opt[0][0]) : DWI2RESPONSE_DEFAULT_DISPERSION_MULTIPLIER;
opt = get_options ("integral_multiplier");
const float integral_multiplier = opt.size() ? float(opt[0][0]) : DWI2RESPONSE_DEFAULT_INTEGRAL_STDEV_MULTIPLIER;
SFThresholds thresholds (volume_ratio); // Only threshold the lobe volume ratio for now; other two are not yet used
size_t total_iter = 0;
bool first_pass = true;
size_t prev_sf_count = 0;
{
bool iterate = true;
size_t iter = 0;
ProgressBar progress ("optimising response function... ");
do {
++iter;
{
MR::LogLevelLatch latch (0);
shared.set_response (response);
shared.init();
}
++progress;
if (reset_mask) {
if (mask_path.size()) {
Image::Buffer<bool> in (mask_path);
auto v_in = in.voxel();
Image::copy (v_in, v_mask, 0, 3);
} else {
for (auto l = Image::LoopInOrder(v_mask) (v_mask); l; ++l)
v_mask.value() = true;
}
++progress;
}
std::vector<FODSegResult> seg_results;
{
FODCalcAndSeg processor (dwi, mask, shared, directions, lmax, seg_results);
Image::ThreadedLoop loop (mask, 0, 3);
loop.run (processor);
}
++progress;
if (!first_pass)
thresholds.update (seg_results, dispersion_multiplier, integral_multiplier, iter);
++progress;
Response output (lmax);
mask.zero();
{
SFSelector selector (seg_results, thresholds, mask);
ResponseEstimator estimator (dwi, shared, lmax, output);
Thread::run_queue (selector, FODSegResult(), Thread::multi (estimator));
}
if (!output.get_count())
throw Exception ("Cannot estimate response function; all voxels have been excluded from selection");
const Math::Vector<float> new_response = output.result();
const size_t sf_count = output.get_count();
++progress;
if (App::log_level >= 2)
std::cerr << "\n";
INFO ("Iteration " + str(iter) + ", " + str(sf_count) + " SF voxels, new response function: [" + str(new_response, 2) + "]");
if (sf_count == prev_sf_count) {
INFO ("terminating due to convergence of single-fibre voxel selection");
iterate = false;
}
if (iter == max_iters) {
INFO ("terminating due to completing maximum number of iterations");
iterate = false;
}
bool rf_changed = false;
for (size_t i = 0; i != response.size(); ++i) {
if (std::abs ((new_response[i] - response[i]) / new_response[i]) > max_change)
rf_changed = true;
}
if (!rf_changed) {
INFO ("terminating due to negligible changes in the response function coefficients");
iterate = false;
}
if (!iterate && first_pass) {
iterate = true;
first_pass = false;
INFO ("commencing second-pass of response function estimation");
total_iter = iter;
iter = 0;
}
response = new_response;
prev_sf_count = sf_count;
//v_mask.save ("mask_pass_" + str(first_pass?1:2) + "_iter_" + str(iter) + ".mif");
} while (iterate);
total_iter += iter;
}
CONSOLE ("final response function: [" + str(response, 2) + "] (reached after " + str(total_iter) + " iterations using " + str(prev_sf_count) + " voxels)");
response.save (argument[1]);
opt = get_options ("sf");
if (opt.size())
v_mask.save (std::string (opt[0][0]));
}