void run()
{
auto input_image = Image<float>::open (argument[0]);
Eigen::MatrixXd grad = DWI::get_valid_DW_scheme (input_image);
// Want to support non-shell-like data if it's just a straight extraction
// of all dwis or all bzeros i.e. don't initialise the Shells class
std::vector<int> volumes;
bool bzero = get_options ("bzero").size();
auto opt = get_options ("shell");
if (opt.size()) {
DWI::Shells shells (grad);
shells.select_shells (false, false);
for (size_t s = 0; s != shells.count(); ++s) {
DEBUG ("Including data from shell b=" + str(shells[s].get_mean()) + " +- " + str(shells[s].get_stdev()));
for (const auto v : shells[s].get_volumes())
volumes.push_back (v);
}
bzero = (shells.count() == 1 && shells[0].is_bzero());
} else {
const float bzero_threshold = File::Config::get_float ("BValueThreshold", 10.0);
for (ssize_t row = 0; row != grad.rows(); ++row) {
if ((bzero && (grad (row, 3) < bzero_threshold)) || (!bzero && (grad (row, 3) > bzero_threshold)))
volumes.push_back (row);
}
}
if (volumes.empty()) {
auto type = (bzero) ? "b=0" : "dwi";
throw Exception ("No " + str(type) + " volumes present");
}
std::sort (volumes.begin(), volumes.end());
Header header (input_image);
Stride::set_from_command_line (header);
header.size (3) = volumes.size();
Eigen::MatrixXd new_grad (volumes.size(), grad.cols());
for (size_t i = 0; i < volumes.size(); i++)
new_grad.row (i) = grad.row (volumes[i]);
header.set_DW_scheme (new_grad);
auto output_image = Image<float>::create (argument[1], header);
auto input_volumes = Adapter::make<Adapter::Extract1D> (input_image, 3, volumes);
threaded_copy_with_progress_message ("extracting volumes", input_volumes, output_image);
}
void run ()
{
try {
auto directions = DWI::Directions::load_cartesian (argument[0]);
report (argument[0], directions);
}
catch (Exception& E) {
auto directions = load_matrix<double> (argument[0]);
DWI::normalise_grad (directions);
if (directions.cols() < 3)
throw Exception ("unexpected matrix size for DW scheme \"" + str(argument[0]) + "\"");
print (str(argument[0]) + " [ " + str(directions.rows()) + " volumes ]\n");
DWI::Shells shells (directions);
for (size_t n = 0; n < shells.count(); ++n) {
Eigen::MatrixXd subset (shells[n].count(), 3);
for (ssize_t i = 0; i < subset.rows(); ++i)
subset.row(i) = directions.row(shells[n].get_volumes()[i]).head(3);
report ("\nb = " + str(shells[n].get_mean(), precision), subset);
}
}
}
void run ()
{
try {
Math::Matrix<value_type> directions = DWI::Directions::load_cartesian<value_type> (argument[0]);
report (str(argument[0]), directions);
}
catch (Exception& E) {
Math::Matrix<value_type> directions (str(argument[0]));
DWI::normalise_grad (directions);
if (directions.columns() < 3)
throw Exception ("unexpected matrix size for DW scheme \"" + str(argument[0]) + "\"");
print (str(argument[0]) + " [ " + str(directions.rows()) + " volumes ]\n");
DWI::Shells shells (directions);
for (size_t n = 0; n < shells.count(); ++n) {
Math::Matrix<value_type> subset (shells[n].count(), 3);
for (size_t i = 0; i < subset.rows(); ++i)
subset.row(i) = directions.row(shells[n].get_volumes()[i]).sub(0,3);
report ("\nb = " + str(shells[n].get_mean()), subset);
}
}
}
void run ()
{
auto sh_data = Image<value_type>::open(argument[0]);
Math::SH::check (sh_data);
auto amp_header = sh_data.original_header();
Eigen::MatrixXd directions;
if (get_options("gradient").size()) {
Eigen::MatrixXd grad;
grad = load_matrix(argument[1]);
DWI::Shells shells (grad);
directions = DWI::gen_direction_matrix (grad, shells.largest().get_volumes());
} else {
directions = load_matrix(argument[1]);
}
if (!directions.rows())
throw Exception ("no directions found in input directions file");
std::stringstream dir_stream;
for (ssize_t d = 0; d < directions.rows() - 1; ++d)
dir_stream << directions(d,0) << "," << directions(d,1) << "\n";
dir_stream << directions(directions.rows() - 1,0) << "," << directions(directions.rows() - 1,1);
amp_header.keyval().insert(std::pair<std::string, std::string> ("directions", dir_stream.str()));
amp_header.size(3) = directions.rows();
Stride::set_from_command_line (amp_header, Stride::contiguous_along_axis (3));
amp_header.datatype() = DataType::from_command_line (DataType::Float32);
auto amp_data = Image<value_type>::create(argument[2], amp_header);
SH2Amp sh2amp (directions, Math::SH::LforN (sh_data.size(3)), get_options("nonnegative").size());
ThreadedLoop("computing amplitudes", sh_data, 0, 3, 2).run(sh2amp, sh_data, amp_data);
}
void run() {
auto input_image = Image<float>::open (argument[0]).with_direct_io (3);
Eigen::MatrixXd grad = DWI::get_valid_DW_scheme (input_image);
// Want to support non-shell-like data if it's just a straight extraction
// of all dwis or all bzeros i.e. don't initialise the Shells class
std::vector<size_t> volumes;
bool bzero = get_options ("bzero").size();
auto opt = get_options ("shell");
if (opt.size()) {
DWI::Shells shells (grad);
shells.select_shells (false, false);
for (size_t s = 0; s != shells.count(); ++s) {
DEBUG ("Including data from shell b=" + str(shells[s].get_mean()) + " +- " + str(shells[s].get_stdev()));
for (std::vector<size_t>::const_iterator v = shells[s].get_volumes().begin(); v != shells[s].get_volumes().end(); ++v)
volumes.push_back (*v);
}
// Remove DW information from header if b=0 is the only 'shell' selected
bzero = (shells.count() == 1 && shells[0].is_bzero());
} else {
const float bzero_threshold = File::Config::get_float ("BValueThreshold", 10.0);
for (ssize_t row = 0; row != grad.rows(); ++row) {
if ((bzero && (grad (row, 3) < bzero_threshold)) || (!bzero && (grad (row, 3) > bzero_threshold)))
volumes.push_back (row);
}
}
if (volumes.empty()) {
auto type = (bzero) ? "b=0" : "dwi";
throw Exception ("No " + str(type) + " volumes present");
}
std::sort (volumes.begin(), volumes.end());
Header header (input_image);
if (volumes.size() == 1)
header.set_ndim (3);
else
header.size (3) = volumes.size();
Eigen::MatrixXd new_grad (volumes.size(), grad.cols());
for (size_t i = 0; i < volumes.size(); i++)
new_grad.row (i) = grad.row (volumes[i]);
header.set_DW_scheme (new_grad);
auto output_image = Image<float>::create (argument[1], header);
auto outer = Loop ("extracting volumes", input_image, 0, 3);
if (output_image.ndim() == 4) {
for (auto i = outer (output_image, input_image); i; ++i) {
for (size_t i = 0; i < volumes.size(); i++) {
input_image.index(3) = volumes[i];
output_image.index(3) = i;
output_image.value() = input_image.value();
}
}
} else {
const size_t volume = volumes[0];
for (auto i = outer (output_image, input_image); i; ++i) {
input_image.index(3) = volume;
output_image.value() = input_image.value();
}
}
}
void run ()
{
Image::Buffer<value_type> dwi_data (argument[0]);
if (dwi_data.ndim() != 4)
throw Exception ("dwi image should contain 4 dimensions");
Math::Matrix<value_type> grad = DWI::get_valid_DW_scheme<value_type> (dwi_data);
DWI::Shells shells (grad);
// Keep the b=0 shell (may be used for normalisation), but force single non-zero shell
shells.select_shells (true, true);
Math::Matrix<value_type> DW_dirs = DWI::gen_direction_matrix (grad, shells.largest().get_volumes());
Options opt = get_options ("lmax");
lmax = opt.size() ? opt[0][0] : Math::SH::LforN (shells.largest().count());
INFO ("calculating even spherical harmonic components up to order " + str (lmax));
Math::Matrix<value_type> HR_dirs;
Math::Matrix<value_type> HR_SHT;
opt = get_options ("normalise");
if (opt.size()) {
normalise = true;
opt = get_options ("directions");
if (opt.size())
HR_dirs.load (opt[0][0]);
else
DWI::Directions::electrostatic_repulsion_300 (HR_dirs);
Math::SH::init_transform (HR_SHT, HR_dirs, lmax);
}
// set Lmax
int i;
for (i = 0; Math::SH::NforL(i) < shells.largest().count(); i += 2);
i -= 2;
if (lmax > i) {
WARN ("not enough data for SH order " + str(lmax) + ", falling back to " + str(i));
lmax = i;
}
INFO("setting maximum even spherical harmonic order to " + str(lmax));
// Setup response function
int num_RH = (lmax + 2)/2;
Math::Vector<value_type> sigs(num_RH);
std::vector<value_type> AL (lmax+1);
Math::Legendre::Plm_sph<value_type>(&AL[0], lmax, 0, 0);
for (int l = 0; l <= lmax; l += 2) sigs[l/2] = AL[l];
Math::Vector<value_type> response(num_RH);
Math::SH::SH2RH(response, sigs);
opt = get_options ("filter");
Math::Vector<value_type> filter;
if (opt.size()) {
filter.load (opt[0][0]);
if (filter.size() <= response.size())
throw Exception ("not enough filter coefficients supplied for lmax" + str(lmax));
for (int i = 0; i <= lmax/2; i++) response[i] *= filter[i];
INFO ("using initial filter coefficients: " + str (filter));
}
Math::SH::Transform<value_type> FRT_SHT(DW_dirs, lmax);
FRT_SHT.set_filter(response);
Image::Header qbi_header (dwi_data);
qbi_header.dim(3) = Math::SH::NforL (lmax);
qbi_header.datatype() = DataType::Float32;
Image::Stride::set (qbi_header, Image::Stride::contiguous_along_axis (3, dwi_data));
Image::Buffer<value_type> qbi_data (argument[1], qbi_header);
opt = get_options ("mask");
if (opt.size()) {
Image::Buffer<bool> mask_data (opt[0][0]);
Image::ThreadedLoop ("estimating dODFs using Q-ball imaging...", dwi_data, 0, 3)
.run (DWI2QBI (FRT_SHT.mat_A2SH(), HR_SHT, shells), mask_data.voxel(), dwi_data.voxel(), qbi_data.voxel());
}
else
Image::ThreadedLoop ("estimating dODFs using Q-ball imaging...", dwi_data, 0, 3)
.run (DWI2QBI (FRT_SHT.mat_A2SH(), HR_SHT, shells), dwi_data.voxel(), qbi_data.voxel());
}
void run ()
{
auto amp = Image<value_type>::open (argument[0]).with_direct_io (3);
Header header (amp);
std::vector<size_t> bzeros, dwis;
Eigen::MatrixXd dirs;
auto opt = get_options ("directions");
if (opt.size()) {
dirs = load_matrix (opt[0][0]);
}
else {
auto hit = header.keyval().find ("directions");
if (hit != header.keyval().end()) {
std::vector<default_type> dir_vector;
for (auto line : split_lines (hit->second)) {
auto v = parse_floats (line);
dir_vector.insert (dir_vector.end(), v.begin(), v.end());
}
dirs.resize(dir_vector.size() / 2, 2);
for (size_t i = 0; i < dir_vector.size(); i += 2) {
dirs(i/2, 0) = dir_vector[i];
dirs(i/2, 1) = dir_vector[i+1];
}
}
else {
auto grad = DWI::get_valid_DW_scheme (amp);
DWI::Shells shells (grad);
shells.select_shells (true, true);
if (shells.smallest().is_bzero())
bzeros = shells.smallest().get_volumes();
dwis = shells.largest().get_volumes();
dirs = DWI::gen_direction_matrix (grad, dwis);
}
}
auto sh2amp = DWI::compute_SH2amp_mapping (dirs, true, 8);
bool normalise = get_options ("normalise").size();
if (normalise && !bzeros.size())
throw Exception ("the normalise option is only available if the input data contains b=0 images.");
header.size (3) = sh2amp.cols();
Stride::set_from_command_line (header);
auto SH = Image<value_type>::create (argument[1], header);
Amp2SHCommon common (sh2amp, bzeros, dwis, normalise);
opt = get_options ("rician");
if (opt.size()) {
auto noise = Image<value_type>::open (opt[0][0]).with_direct_io();
ThreadedLoop ("mapping amplitudes to SH coefficients", amp, 0, 3)
.run (Amp2SH (common), SH, amp, noise);
}
else {
ThreadedLoop ("mapping amplitudes to SH coefficients", amp, 0, 3)
.run (Amp2SH (common), SH, amp);
}
}
void run() {
Image::BufferPreload<float> data_in (argument[0], Image::Stride::contiguous_along_axis (3));
auto voxel_in = data_in.voxel();
Math::Matrix<value_type> grad (DWI::get_valid_DW_scheme<float> (data_in));
// Want to support non-shell-like data if it's just a straight extraction
// of all dwis or all bzeros i.e. don't initialise the Shells class
std::vector<size_t> volumes;
bool bzero = get_options ("bzero").size();
Options opt = get_options ("shell");
if (opt.size()) {
DWI::Shells shells (grad);
shells.select_shells (false, false);
for (size_t s = 0; s != shells.count(); ++s) {
DEBUG ("Including data from shell b=" + str(shells[s].get_mean()) + " +- " + str(shells[s].get_stdev()));
for (std::vector<size_t>::const_iterator v = shells[s].get_volumes().begin(); v != shells[s].get_volumes().end(); ++v)
volumes.push_back (*v);
}
// Remove DW information from header if b=0 is the only 'shell' selected
bzero = (shells.count() == 1 && shells[0].is_bzero());
} else {
const float bzero_threshold = File::Config::get_float ("BValueThreshold", 10.0);
for (size_t row = 0; row != grad.rows(); ++row) {
if ((bzero && (grad (row, 3) < bzero_threshold)) || (!bzero && (grad (row, 3) > bzero_threshold)))
volumes.push_back (row);
}
}
if (volumes.empty())
throw Exception ("No " + str(bzero ? "b=0" : "dwi") + " volumes present");
std::sort (volumes.begin(), volumes.end());
Image::Header header (data_in);
if (volumes.size() == 1)
header.set_ndim (3);
else
header.dim (3) = volumes.size();
Math::Matrix<value_type> new_grad (volumes.size(), grad.columns());
for (size_t i = 0; i < volumes.size(); i++)
new_grad.row (i) = grad.row (volumes[i]);
header.DW_scheme() = new_grad;
Image::Buffer<value_type> data_out (argument[1], header);
auto voxel_out = data_out.voxel();
Image::Loop outer ("extracting volumes...", 0, 3);
if (voxel_out.ndim() == 4) {
for (auto i = outer (voxel_out, voxel_in); i; ++i) {
for (size_t i = 0; i < volumes.size(); i++) {
voxel_in[3] = volumes[i];
voxel_out[3] = i;
voxel_out.value() = voxel_in.value();
}
}
} else {
const size_t volume = volumes[0];
for (auto i = outer (voxel_out, voxel_in); i; ++i) {
voxel_in[3] = volume;
voxel_out.value() = voxel_in.value();
}
}
}