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reslice.h
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reslice.h
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/* Copyright (c) 2008-2022 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/.
*
* Covered Software is provided under this License on an "as is"
* basis, without warranty of any kind, either expressed, implied, or
* statutory, including, without limitation, warranties that the
* Covered Software is free of defects, merchantable, fit for a
* particular purpose or non-infringing.
* See the Mozilla Public License v. 2.0 for more details.
*
* For more details, see http://www.mrtrix.org/.
*/
#ifndef __adapter_reslice_h__
#define __adapter_reslice_h__
#include <type_traits>
#include "image.h"
#include "transform.h"
#include "types.h"
#include "interp/base.h"
#include "interp/nearest.h"
namespace MR
{
namespace Adapter
{
namespace
{
// Partial specialisation for boolean value_type in order to avoid compiler
// warning regarding use of multiplication when assigning to a boolean
template <typename value_type>
typename std::enable_if<std::is_same<value_type, bool>::value, value_type>::type
inline normalise (const default_type sum, const default_type norm)
{
return ((sum*norm) >= 0.5) ? true : false;
}
// Partial specialisation to invoke round-to-nearest when taking an average of integers
template <typename value_type>
typename std::enable_if<!std::is_same<value_type, bool>::value && std::is_integral<value_type>::value, value_type>::type
inline normalise (const default_type sum, const default_type norm)
{
return value_type(std::round (sum*norm));
}
template <typename value_type>
typename std::enable_if<std::is_floating_point<value_type>::value, value_type>::type
inline normalise (const default_type sum, const default_type norm)
{
return (sum * norm);
}
}
extern const transform_type NoTransform;
extern const vector<uint32_t> AutoOverSample;
//! \addtogroup interp
// @{
//! an Image providing interpolated values from another Image
/*! the Reslice class provides an Image interface to data
* interpolated using the specified Interpolator class from the
* Image \a original. The Reslice object will have the same
* dimensions, voxel sizes and transform as the \a reference HeaderType.
* Any of the interpolator classes (currently Interp::Nearest,
* Interp::Linear, Interp::Cubic and Interp::Sinc) can be used.
*
* For example:
* \code
* // reference header:
* auto reference = Header::open (argument[0]);
* // input data to be resliced:
* auto input = Image<float>::open (argument[1]);
*
* Adapter::Reslice<Interp::Cubic, Image<float> > reslicer (input, reference);
* auto output = Image::create<float> (argument[2], reslicer);
*
* // copy data from regridder to output
* copy (reslicer, output);
* \endcode
*
* It is also possible to supply an additional transform to be applied to
* the data, using the \a transform parameter. The transform will be
* applied in the scanner coordinate system, and should map scanner-space
* coordinates in the original image to scanner-space coordinates in the
* reference image.
*
* To deal with possible aliasing due to sparse sampling of a
* high-resolution image, the Reslice object may perform over-sampling,
* whereby multiple samples are taken at regular sub-voxel intervals and
* averaged. By default, oversampling will be performed along those axes
* where it is deemed necessary. This can be over-ridden using the \a
* oversampling parameter, which should contain one (integer)
* over-sampling factor for each of the 3 imaging axes. Specifying the
* vector [ 1 1 1 ] will therefore disable over-sampling.
*
* \sa Interp::reslice()
*/
template <template <class ImageType> class Interpolator, class ImageType>
class Reslice :
public ImageBase<Reslice<Interpolator,ImageType>,typename ImageType::value_type>
{ MEMALIGN (Reslice<Interpolator, ImageType>)
public:
using value_type = typename ImageType::value_type;
template <class HeaderType>
Reslice (const ImageType& original,
const HeaderType& reference,
const transform_type& transform = NoTransform,
const vector<uint32_t>& oversample = AutoOverSample,
const value_type value_when_out_of_bounds = Interp::Base<ImageType>::default_out_of_bounds_value()) :
interp (original, value_when_out_of_bounds),
x { 0, 0, 0 },
dim { reference.size(0), reference.size(1), reference.size(2) },
vox { reference.spacing(0), reference.spacing(1), reference.spacing(2) },
transform_ (reference.transform()),
direct_transform (Transform(original).scanner2voxel * transform * Transform(reference).voxel2scanner) {
using namespace Eigen;
assert (ndim() >= 3);
const bool is_nearest = std::is_same<typename Interp::Nearest<ImageType>, decltype(interp)>::value;
if (oversample.size()) { // oversample explicitly set
assert (oversample.size() == 3);
if (oversample[0] < 1 || oversample[1] < 1 || oversample[2] < 1)
throw Exception ("oversample factors must be greater than zero");
if (is_nearest && (oversample[0] != 1 || oversample[1] != 1 || oversample[2] != 1)) {
WARN("oversampling factors ignored for nearest neighbour interpolation");
OS[0] = OS[1] = OS[2] = 1;
}
else {
OS[0] = oversample[0]; OS[1] = oversample[1]; OS[2] = oversample[2];
}
}
else { // oversample is default
if (is_nearest) {
OS[0] = OS[1] = OS[2] = 1;
}
else {
Vector3d y = direct_transform * Vector3d (0.0, 0.0, 0.0);
Vector3d x0 = direct_transform * Vector3d (1.0, 0.0, 0.0);
OS[0] = std::ceil ((1.0-std::numeric_limits<default_type>::epsilon()) * (y-x0).norm());
x0 = direct_transform * Vector3d (0.0, 1.0, 0.0);
OS[1] = std::ceil ((1.0-std::numeric_limits<default_type>::epsilon()) * (y-x0).norm());
x0 = direct_transform * Vector3d (0.0, 0.0, 1.0);
OS[2] = std::ceil ((1.0-std::numeric_limits<default_type>::epsilon()) * (y-x0).norm());
}
}
if (OS[0] * OS[1] * OS[2] > 1) {
INFO ("using oversampling factors [ " + str (OS[0]) + " " + str (OS[1]) + " " + str (OS[2]) + " ]");
oversampling = true;
norm = 1.0;
for (size_t i = 0; i < 3; ++i) {
inc[i] = 1.0/default_type (OS[i]);
from[i] = 0.5* (inc[i]-1.0);
norm *= OS[i];
}
norm = 1.0 / norm;
}
else oversampling = false;
}
size_t ndim () const { return interp.ndim(); }
bool valid () const { return interp.valid(); }
int size (size_t axis) const { return axis < 3 ? dim[axis]: interp.size (axis); }
default_type spacing (size_t axis) const { return axis < 3 ? vox[axis] : interp.spacing (axis); }
const transform_type& transform () const { return transform_; }
const std::string& name () const { return interp.name(); }
ssize_t stride (size_t axis) const {
return interp.stride (axis);
}
void reset () {
x[0] = x[1] = x[2] = 0;
for (size_t n = 3; n < interp.ndim(); ++n)
interp.index(n) = 0;
}
value_type value () {
using namespace Eigen;
if (oversampling) {
Vector3d d (x[0]+from[0], x[1]+from[1], x[2]+from[2]);
default_type sum (0.0);
Vector3d s;
for (uint32_t z = 0; z < OS[2]; ++z) {
s[2] = d[2] + z*inc[2];
for (uint32_t y = 0; y < OS[1]; ++y) {
s[1] = d[1] + y*inc[1];
for (uint32_t x = 0; x < OS[0]; ++x) {
s[0] = d[0] + x*inc[0];
if (interp.voxel (direct_transform * s))
sum += interp.value();
}
}
}
return normalise<value_type> (sum, norm);
}
interp.voxel (direct_transform * Vector3d (x[0], x[1], x[2]));
return interp.value();
}
ssize_t get_index (size_t axis) const { return axis < 3 ? x[axis] : interp.index(axis); }
void move_index (size_t axis, ssize_t increment) {
if (axis < 3) x[axis] += increment;
else interp.index(axis) += increment;
}
private:
Interpolator<ImageType> interp;
ssize_t x[3];
const ssize_t dim[3];
const default_type vox[3];
bool oversampling;
uint32_t OS[3];
default_type from[3], inc[3];
default_type norm;
const transform_type transform_, direct_transform;
};
//! @}
}
}
#endif