ITK  5.3.0
Insight Toolkit
Examples/DataRepresentation/Image/Image4.cxx
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
// Software Guide : BeginLatex
//
// Even though \href{https://www.itk.org}{ITK} can be used to perform
// general image processing tasks, the primary purpose of the toolkit is the
// processing of medical image data. In that respect, additional
// information about the images is considered mandatory. In particular the
// information associated with the physical spacing between pixels and the
// position of the image in space with respect to some world coordinate
// system are extremely important.
//
// Image origin, voxel directions (i.e. orientation), and spacing are
// fundamental to many applications. Registration, for example, is performed
// in physical coordinates. Improperly defined spacing, direction, and origins
// will result in inconsistent results in such processes. Medical images with
// no spatial information should not be used for medical diagnosis, image
// analysis, feature extraction, assisted radiation therapy or image guided
// surgery. In other words, medical images lacking spatial information are not
// only useless but also hazardous.
//
// \begin{figure} \center
// \includegraphics[width=\textwidth]{ImageOriginAndSpacing}
// \itkcaption[ITK Image Geometrical Concepts]{Geometrical concepts associated
// with the ITK image.}
// \label{fig:ImageOriginAndSpacing}
// \end{figure}
//
// Figure \ref{fig:ImageOriginAndSpacing} illustrates the main geometrical
// concepts associated with the \doxygen{Image}.
// In this figure, circles are
// used to represent the center of pixels. The value of the pixel is assumed
// to exist as a Dirac delta function located at the pixel center. Pixel
// spacing is measured between the pixel centers and can be different along
// each dimension. The image origin is associated with the coordinates of the
// first pixel in the image.
// For this simplified example, the voxel lattice is perfectly aligned with
// physical space orientation, and the image direction is therefore an
// identity mapping. If the voxel lattice samples were rotated with respect to
// physical space, then the image direction would contain a rotation matrix.
//
// A \emph{pixel} is considered to be the
// rectangular region surrounding the pixel center holding the data
// value.
//
// Software Guide : EndLatex
#include "itkImage.h"
// Function to simulate getting mouse click from an image
GetIndexFromMouseClick()
{
LeftEyeIndex[0] = 60;
LeftEyeIndex[1] = 127;
LeftEyeIndex[2] = 93;
return LeftEyeIndex;
}
int
main(int, char *[])
{
constexpr unsigned int Dimension = 3;
ImageType::Pointer image = ImageType::New();
const ImageType::SizeType size = {
{ 200, 200, 200 }
}; // Size along {X,Y,Z}
const ImageType::IndexType start = {
{ 0, 0, 0 }
}; // First index on {X,Y,Z}
region.SetSize(size);
region.SetIndex(start);
image->SetRegions(region);
image->Allocate(true); // initialize buffer to zero
// Software Guide : BeginLatex
//
// Image spacing is represented in a \code{FixedArray}
// whose size matches the dimension of the image. In order to manually set
// the spacing of the image, an array of the corresponding type must be
// created. The elements of the array should then be initialized with the
// spacing between the centers of adjacent pixels. The following code
// illustrates the methods available in the \doxygen{Image} class for
// dealing with spacing and origin.
//
// \index{itk::Image!Spacing}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
ImageType::SpacingType spacing;
// Units (e.g., mm, inches, etc.) are defined by the application.
spacing[0] = 0.33; // spacing along X
spacing[1] = 0.33; // spacing along Y
spacing[2] = 1.20; // spacing along Z
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The array can be assigned to the image using
// the \code{SetSpacing()} method.
//
// \index{itk::Image!SetSpacing()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
image->SetSpacing(spacing);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The spacing information can be retrieved from an image by using the
// \code{GetSpacing()} method. This method returns a reference to a
// \code{FixedArray}. The returned object can then be used to read the
// contents of the array. Note the use of the \code{const} keyword to
// indicate that the array will not be modified.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const ImageType::SpacingType & sp = image->GetSpacing();
std::cout << "Spacing = ";
std::cout << sp[0] << ", " << sp[1] << ", " << sp[2] << std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The image origin is managed in a similar way to the spacing. A
// \code{Point} of the appropriate dimension must first be
// allocated. The coordinates of the origin can then be assigned to
// every component. These coordinates correspond to the position of
// the first pixel of the image with respect to an arbitrary
// reference system in physical space. It is the user's
// responsibility to make sure that multiple images used in the same
// application are using a consistent reference system. This is
// extremely important in image registration applications.
//
// The following code illustrates the creation and assignment of a variable
// suitable for initializing the image origin.
//
// \index{itk::Image!origin}
// \index{itk::Image!SetOrigin()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// coordinates of the center of the first pixel in N-D
newOrigin.Fill(0.0);
image->SetOrigin(newOrigin);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The origin can also be retrieved from an image by using the
// \code{GetOrigin()} method. This will return a reference to a
// \code{Point}. The reference can be used to read the contents of
// the array. Note again the use of the \code{const} keyword to indicate
// that the array contents will not be modified.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const ImageType::PointType & origin = image->GetOrigin();
std::cout << "Origin = ";
std::cout << origin[0] << ", " << origin[1] << ", " << origin[2]
<< std::endl;
// Software Guide : EndCodeSnippet
// TODO: This example should really be written for a more complicated
// direction cosine. i.e. As the first index element increases, the 1st
// physical space decreases.
// Software Guide : BeginLatex
//
// The image direction matrix represents the orientation relationships
// between the image samples and physical space coordinate systems. The
// image direction matrix is an orthonormal matrix that describes the
// possible permutation of image index values and the rotational aspects
// that are needed to properly reconcile image index organization with
// physical space axis. The image directions is a $N x N$ matrix where $N$
// is the dimension of the image. An identity image direction indicates that
// increasing values of the 1st, 2nd, 3rd index element corresponds to
// increasing values of the 1st, 2nd and 3rd physical space axis
// respectively, and that the voxel samples are perfectly aligned with the
// physical space axis.
//
// The following code illustrates the creation and assignment of a variable
// suitable for initializing the image direction with an identity.
//
// \index{itk::Image!direction}
// \index{itk::Image!SetDirection()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// coordinates of the center of the first pixel in N-D
direction.SetIdentity();
image->SetDirection(direction);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The direction can also be retrieved from an image by using the
// \code{GetDirection()} method. This will return a reference to a
// \code{Matrix}. The reference can be used to read the contents of
// the array. Note again the use of the \code{const} keyword to indicate
// that the matrix contents can not be modified.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const ImageType::DirectionType & direct = image->GetDirection();
std::cout << "Direction = " << std::endl;
std::cout << direct << std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Once the spacing, origin, and direction of the image samples have been
// initialized, the image will correctly map pixel indices to and from
// physical space coordinates. The following code illustrates how a point in
// physical space can be mapped into an image index for the purpose of
// reading the content of the closest pixel.
//
// First, a \doxygen{Point} type must be declared. The point type is
// templated over the type used to represent coordinates and over the
// dimension of the space. In this particular case, the dimension of the
// point must match the dimension of the image.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The \doxygen{Point} class, like an \doxygen{Index}, is a relatively
// small and simple object. This means that no \doxygen{SmartPointer}
// is used here and the objects are simply declared as instances,
// like any other C++ class. Once the point is declared, its
// components can be accessed using traditional array notation. In
// particular, the \code{[]} operator is available. For efficiency reasons,
// no bounds checking is performed on the index used to access a particular
// point component. It is the user's responsibility to make sure that the
// index is in the range $\{0,Dimension-1\}$.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
PointType point;
point[0] = 1.45; // x coordinate
point[1] = 7.21; // y coordinate
point[2] = 9.28; // z coordinate
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The image will map the point to an index using the values of the
// current spacing and origin. An index object must be provided to
// receive the results of the mapping. The index object can be
// instantiated by using the \code{IndexType} defined in the image
// type.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The \code{TransformPhysicalPointToIndex()} method of the image class
// will compute the pixel index closest to the point provided. The method
// checks for this index to be contained inside the current buffered pixel
// data. The method returns a boolean indicating whether the resulting
// index falls inside the buffered region or not. The output index should
// not be used when the returned value of the method is \code{false}.
//
// The following lines illustrate the point to index mapping and the
// subsequent use of the pixel index for accessing pixel data from the
// image.
//
// \index{itk::Image!TransformPhysicalPointToIndex()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const bool isInside =
image->TransformPhysicalPointToIndex(point, pixelIndex);
if (isInside)
{
ImageType::PixelType pixelValue = image->GetPixel(pixelIndex);
pixelValue += 5;
image->SetPixel(pixelIndex, pixelValue);
}
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Remember that \code{GetPixel()} and \code{SetPixel()} are very
// inefficient methods for accessing pixel data. Image iterators should be
// used when massive access to pixel data is required.
//
// Software Guide : EndLatex
//
// Software Guide : BeginLatex
//
// The following example illustrates the mathematical relationships between
// image index locations and its corresponding physical point
// representation for a given Image.
//
// \index{itk::Image!PhysicalPoint}
// \index{itk::Image!Index}
//
// Let us imagine that a graphical user interface exists
// where the end user manually selects the voxel index location
// of the left eye in a volume with a mouse interface. We need to
// convert that index location to a physical location so that
// laser guided surgery can be accurately performed. The
// \code{TransformIndexToPhysicalPoint} method can be used for this.
//
// SoftwareGuide : EndLatex
// Software Guide : BeginCodeSnippet
const ImageType::IndexType LeftEyeIndex = GetIndexFromMouseClick();
ImageType::PointType LeftEyePoint;
image->TransformIndexToPhysicalPoint(LeftEyeIndex, LeftEyePoint);
// Software Guide : EndCodeSnippet
std::cout << "===========================================" << std::endl;
std::cout << "The Left Eye Location is " << LeftEyePoint << std::endl;
// create new global def \NL in latex to avoid \\ multi-line warning
// Software Guide : BeginLatex
//
// \gdef\NL{\\}
//
// For a given index $\vec{I}$ in 3D, the physical location $\vec{P}$ is
// calculated as following:
//
// \begin{equation}
// \begin{pmatrix}
// P_1\NL
// P_2\NL
// P_3
// \end{pmatrix}
// =
// \begin{pmatrix}
// O_1\NL
// O_2\NL
// O_3
// \end{pmatrix}
// +
// \begin{pmatrix}
// D_{1,1} & D_{1,2} & D_{1,3}\NL
// D_{2,1} & D_{2,2} & D_{2,3}\NL
// D_{3,1} & D_{3,2} & D_{3,3}
// \end{pmatrix}
// *
// \begin{pmatrix}
// S_1 & 0 & 0 \NL
// 0 & S_2 & 0 \NL
// 0 & 0 & S_3\NL
// \end{pmatrix}
// *
// \begin{pmatrix}
// I_1\NL
// I_2\NL
// I_3
// \end{pmatrix}
// \end{equation}
// Where:\newline
// $\vec{I}$: image space index.\newline
// $\vec{P}$: resulting physical space position of the image index
// $\vec{I}$.\newline
// $\vec{O}$: physical space origin of the first image index.\newline
// $\mathcal{D}$: direction cosines matrix (orthonormal). It represents the
// orientation relationship between the image and the physical space
// coordinate system.\newline
// $\vec{S}$: physical spacing between pixels of the same axis.
// \newline
//
// \noindent The operation can be thought as a particular case of the linear
// transform: \begin{equation} \vec{P} = \vec{O} + \mathcal{A} \cdot \vec{I}
// \end{equation}
// \noindent where $\mathcal{A}$:
// \begin{equation}
// \mathcal{A}
// =
// \begin{pmatrix}
// D_{1,1}\cdot S_1 & D_{1,2}\cdot S_2 & D_{1,3}\cdot S_3\NL
// D_{2,1}\cdot S_1 & D_{2,2}\cdot S_2 & D_{2,3}\cdot S_3\NL
// D_{3,1}\cdot S_1 & D_{3,2}\cdot S_2 & D_{3,3}\cdot S_3
// \end{pmatrix}
// \end{equation}
//
// In matlab syntax the conversions are:
//
// \begin{verbatim}
// % Non-identity Spacing and Direction
// spacing=diag( [0.9375, 0.9375, 1.5] );
// direction=[0.998189, 0.0569345, -0.0194113;
// 0.0194429, -7.38061e-08, 0.999811;
// 0.0569237, -0.998378, -0.00110704];
// point = origin + direction * spacing * LeftEyeIndex
// \end{verbatim}
//
// A corresponding mathematical expansion of the C/C++ code is:
// SoftwareGuide : EndLatex
// Software Guide : BeginCodeSnippet
MatrixType SpacingMatrix;
SpacingMatrix.Fill(0.0F);
const ImageType::SpacingType & ImageSpacing = image->GetSpacing();
SpacingMatrix(0, 0) = ImageSpacing[0];
SpacingMatrix(1, 1) = ImageSpacing[1];
SpacingMatrix(2, 2) = ImageSpacing[2];
const ImageType::DirectionType & ImageDirectionCosines =
image->GetDirection();
const ImageType::PointType & ImageOrigin = image->GetOrigin();
VectorType LeftEyeIndexVector;
LeftEyeIndexVector[0] = LeftEyeIndex[0];
LeftEyeIndexVector[1] = LeftEyeIndex[1];
LeftEyeIndexVector[2] = LeftEyeIndex[2];
ImageType::PointType LeftEyePointByHand =
ImageOrigin + ImageDirectionCosines * SpacingMatrix * LeftEyeIndexVector;
// Software Guide : EndCodeSnippet
std::cout << "===========================================" << std::endl;
std::cout << "Spacing:: " << std::endl << SpacingMatrix << std::endl;
std::cout << "===========================================" << std::endl;
std::cout << "DirectionCosines:: " << std::endl
<< ImageDirectionCosines << std::endl;
std::cout << "===========================================" << std::endl;
std::cout << "Origin:: " << std::endl << ImageOrigin << std::endl;
std::cout << "===========================================" << std::endl;
std::cout << "The Left Eye Location is " << LeftEyePointByHand << std::endl;
//
// Check if two results are identical
//
if ((LeftEyePointByHand - LeftEyePoint).GetNorm() < 0.01F)
{
std::cout << "===========================================" << std::endl;
std::cout << "Two results are identical as expected!" << std::endl;
std::cout << "The Left Eye from TransformIndexToPhysicalPoint is "
<< LeftEyePoint << std::endl;
std::cout << "The Left Eye from Math is " << LeftEyePointByHand
<< std::endl;
}
return EXIT_SUCCESS;
}
itk::Matrix::SetIdentity
void SetIdentity()
Definition: itkMatrix.h:192
itk::Index< VImageDimension >
itk::GTest::TypedefsAndConstructors::Dimension2::DirectionType
ImageBaseType::DirectionType DirectionType
Definition: itkGTestTypedefsAndConstructors.h:52
itk::Matrix::Fill
void Fill(const T &value)
Definition: itkMatrix.h:209
itk::GTest::TypedefsAndConstructors::Dimension2::VectorType
ImageBaseType::SpacingType VectorType
Definition: itkGTestTypedefsAndConstructors.h:53
itk::GTest::TypedefsAndConstructors::Dimension2::PointType
ImageBaseType::PointType PointType
Definition: itkGTestTypedefsAndConstructors.h:51
itk::Vector
A templated class holding a n-Dimensional vector.
Definition: itkVector.h:62
itk::GTest::TypedefsAndConstructors::Dimension2::SizeType
ImageBaseType::SizeType SizeType
Definition: itkGTestTypedefsAndConstructors.h:49
itkImage.h
itk::GTest::TypedefsAndConstructors::Dimension2::IndexType
ImageBaseType::IndexType IndexType
Definition: itkGTestTypedefsAndConstructors.h:50
itk::GTest::TypedefsAndConstructors::Dimension2::RegionType
ImageBaseType::RegionType RegionType
Definition: itkGTestTypedefsAndConstructors.h:54
itk::Matrix
A templated class holding a M x N size Matrix.
Definition: itkMatrix.h:51
itk::Point
A templated class holding a geometric point in n-Dimensional space.
Definition: itkPoint.h:53
itk::Image
Templated n-dimensional image class.
Definition: itkImage.h:88
itk::ImageRegion::SetSize
void SetSize(const SizeType &size)
Definition: itkImageRegion.h:174
itk::GTest::TypedefsAndConstructors::Dimension2::Dimension
constexpr unsigned int Dimension
Definition: itkGTestTypedefsAndConstructors.h:44
itk::VariableLengthVectorExpression::GetNorm
std::enable_if_t< mpl::IsArray< TExpr >::Value, typename TExpr::RealValueType > GetNorm(TExpr const &v)
Definition: itkVariableLengthVector.h:1377
itk::FixedArray::Fill
void Fill(const ValueType &)