EigenvaluesToStructureness3d

Computes a structure score image from the eigenvalues of a three-dimensional tensor image.

Access to parameter description

This algorithm allows extracting tubular, blob-like, and plate-like structures from dark or bright background.

The computation is based on eigenvalues

$\lambda_{1}$ ,

$\lambda_{2}$ and

$\lambda_{3}$ where

$\mid \lambda_{1} \mid \geq \mid \lambda_{2} \mid \geq \mid \lambda_{3} \mid$ .

The structure score for bright tubular structures corresponds to:

$score = \begin{cases} 0 & \text{ if } \lambda_1 >0 \text{ or } \lambda_2 >0 \\ (1-\exp(-\frac{\mathcal{R}_a^2}{2\alpha^2}))\exp(-\frac{\mathcal{R}_b^2}{2\beta^2})(1-\exp(-\frac{S^2}{2c^2})) & \end{cases}$

The score for bright blob-like structures is computed as follows:

$score = \begin{cases} 0 & \text{ if } \lambda_1 >0 \text{ or } \lambda_2 >0 \text{ or } \lambda_3 >0\\ (1-\exp(-\frac{\mathcal{R}_a^2}{2\alpha^2}))(1-\exp(-\frac{\mathcal{R}_b^2}{2\beta^2})) (1-\exp(-\frac{S^2}{2c^2})) \end{cases}$

The score for bright plate-like structures is computed as follows:

$score = \begin{cases} 0 & \text{ if } \lambda_1 >0 \\ \exp(-\frac{\mathcal{R}_a^2}{2\alpha^2})\exp(-\frac{\mathcal{R}_b^2}{2\beta^2})(1-\exp(-\frac{S^2}{2c^2})) & \end{cases}$

Where:

$S$ is the Hessian norm $S = \left \| \mathcal{H} \right \| = \sqrt{\sum \lambda_i^2}$
$\alpha$ is a threshold which controls the flatness sensitivity,
$\beta$ is a threshold which controls the blobness sensitivity,
c is a sensitivity threshold which controls the noise influence.

$c = noiseCutoff \cdot S_{max}$

$S_{max}$

For dark objects the conditions on

$\lambda_{1}$ ,

$\lambda_{2}$ and

$\lambda_{3}$ are reversed.

This algorithm outputs a float grayscale image where each pixel intensity represents a structure score between 0 and 1.

The method for tubular structures is referenced by Alejandro Frangi publication:
A.F.Frangi, W.J.Niessen, K.L.Vincken, M.A.Viergever. "Multiscale vessel enhancement filtering". Lecture Notes in Computer Science(MICCAI), vol. 1496, pp. 130-137, 1998.

See also

Function Syntax

This function returns outputImage.

// Function prototype
std::shared_ptr< iolink::ImageView >
eigenvaluesToStructureness3d( std::shared_ptr< iolink::ImageView > inputEigenvaluesImage,
                              EigenvaluesToStructureness3d::Lightness lightness,
                              EigenvaluesToStructureness3d::StructureType structureType,
                              double alpha,
                              double beta,
                              double noiseCutoff,
                              std::shared_ptr< iolink::ImageView > outputImage = NULL );

This function returns outputImage.

// Function prototype.
eigenvalues_to_structureness_3d( input_eigenvalues_image,
                                 lightness = EigenvaluesToStructureness3d.Lightness.BRIGHT,
                                 structure_type = EigenvaluesToStructureness3d.StructureType.ROD,
                                 alpha = 0.75,
                                 beta = 0.75,
                                 noise_cutoff = 0.5,
                                 output_image = None )

This function returns outputImage.

// Function prototype.
public static IOLink.ImageView
EigenvaluesToStructureness3d( IOLink.ImageView inputEigenvaluesImage,
                              EigenvaluesToStructureness3d.Lightness lightness = ImageDev.EigenvaluesToStructureness3d.Lightness.BRIGHT,
                              EigenvaluesToStructureness3d.StructureType structureType = ImageDev.EigenvaluesToStructureness3d.StructureType.ROD,
                              double alpha = 0.75,
                              double beta = 0.75,
                              double noiseCutoff = 0.5,
                              IOLink.ImageView outputImage = null );

Class Syntax

// Command constructor.
EigenvaluesToStructureness3d();

/// Gets the inputEigenvaluesImage parameter.
/// The input image containing the eigenvalues field. Type must be float. Spectral series size is 3 (channel 0 = largest eigenvalue, channel 1 = medium eigen value, channel 2 = smallest eigenvalue).
std::shared_ptr< iolink::ImageView > inputEigenvaluesImage() const;
/// Sets the inputEigenvaluesImage parameter.
/// The input image containing the eigenvalues field. Type must be float. Spectral series size is 3 (channel 0 = largest eigenvalue, channel 1 = medium eigen value, channel 2 = smallest eigenvalue).
void setInputEigenvaluesImage( std::shared_ptr< iolink::ImageView > inputEigenvaluesImage );

/// Gets the lightness parameter.
/// The type of structure lightness to extract.
EigenvaluesToStructureness3d::Lightness lightness() const;
/// Sets the lightness parameter.
/// The type of structure lightness to extract.
void setLightness( const EigenvaluesToStructureness3d::Lightness& lightness );

/// Gets the structureType parameter.
/// The type of structure shapes to extract.
EigenvaluesToStructureness3d::StructureType structureType() const;
/// Sets the structureType parameter.
/// The type of structure shapes to extract.
void setStructureType( const EigenvaluesToStructureness3d::StructureType& structureType );

/// Gets the alpha parameter.
/// The flatness sensitivity threshold. It corresponds to the alpha term of the score equation.
double alpha() const;
/// Sets the alpha parameter.
/// The flatness sensitivity threshold. It corresponds to the alpha term of the score equation.
void setAlpha( const double& alpha );

/// Gets the beta parameter.
/// The blobness sensitivity threshold. It corresponds to the beta term of the score equation.
double beta() const;
/// Sets the beta parameter.
/// The blobness sensitivity threshold. It corresponds to the beta term of the score equation.
void setBeta( const double& beta );

/// Gets the noiseCutoff parameter.
/// The noise scale factor. It is used for computing the c term of the score equation.
double noiseCutoff() const;
/// Sets the noiseCutoff parameter.
/// The noise scale factor. It is used for computing the c term of the score equation.
void setNoiseCutoff( const double& noiseCutoff );

/// Gets the outputImage parameter.
/// The score output image. X, Y, and Z dimensions, calibration and interpretation of the output image are forced to the same values as the input. The spectral dimension is forced to 1. Type is forced to float and all values are between 0 and 1.
std::shared_ptr< iolink::ImageView > outputImage() const;
/// Sets the outputImage parameter.
/// The score output image. X, Y, and Z dimensions, calibration and interpretation of the output image are forced to the same values as the input. The spectral dimension is forced to 1. Type is forced to float and all values are between 0 and 1.
void setOutputImage( std::shared_ptr< iolink::ImageView > outputImage );


// Method to launch the command.
void execute();

# Property of the inputEigenvaluesImage parameter.
EigenvaluesToStructureness3d.input_eigenvalues_image
# Property of the lightness parameter.
EigenvaluesToStructureness3d.lightness
# Property of the structureType parameter.
EigenvaluesToStructureness3d.structure_type
# Property of the alpha parameter.
EigenvaluesToStructureness3d.alpha
# Property of the beta parameter.
EigenvaluesToStructureness3d.beta
# Property of the noiseCutoff parameter.
EigenvaluesToStructureness3d.noise_cutoff
# Property of the outputImage parameter.
EigenvaluesToStructureness3d.output_image

// Method to launch the command.
execute()

// Command constructor.
EigenvaluesToStructureness3d()

// Property of the inputEigenvaluesImage parameter.
EigenvaluesToStructureness3d.inputEigenvaluesImage
// Property of the lightness parameter.
EigenvaluesToStructureness3d.lightness
// Property of the structureType parameter.
EigenvaluesToStructureness3d.structureType
// Property of the alpha parameter.
EigenvaluesToStructureness3d.alpha
// Property of the beta parameter.
EigenvaluesToStructureness3d.beta
// Property of the noiseCutoff parameter.
EigenvaluesToStructureness3d.noiseCutoff
// Property of the outputImage parameter.
EigenvaluesToStructureness3d.outputImage

// Method to launch the command.
Execute()

Parameters

Parameter Name

Description

Type

Supported Values

Default Value

inputEigenvaluesImage

The input image containing the eigenvalues field. Type must be float. Spectral series size is 3 (channel 0 = largest eigenvalue, channel 1 = medium eigen value, channel 2 = smallest eigenvalue).

Image

Multispectral

nullptr

lightness

The type of structure lightness to extract.

BRIGHT	Extracts bright structures from dark background.
DARK	Extracts dark structures from bright background.

Enumeration

BRIGHT

structureType

The type of structure shapes to extract.

ROD	Extracts rod-like (tubular) structures.
BALL	Extracts blob-like (spherical) structures.
PLANE	Extracts plate-like (planar) structures.

Enumeration

ROD

alpha

The flatness sensitivity threshold. It corresponds to the alpha term of the score equation.

Float64

0.75

beta

The blobness sensitivity threshold. It corresponds to the beta term of the score equation.

Float64

0.75

noiseCutoff

The noise scale factor. It is used for computing the c term of the score equation.

Float64

0.5

outputImage

The score output image. X, Y, and Z dimensions, calibration and interpretation of the output image are forced to the same values as the input. The spectral dimension is forced to 1. Type is forced to float and all values are between 0 and 1.

Image

nullptr

Object Examples

auto neuron_eigenvalues = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "neuron_eigenvalues.vip" );

EigenvaluesToStructureness3d eigenvaluesToStructureness3dAlgo;
eigenvaluesToStructureness3dAlgo.setInputEigenvaluesImage( neuron_eigenvalues );
eigenvaluesToStructureness3dAlgo.setLightness( EigenvaluesToStructureness3d::Lightness::BRIGHT );
eigenvaluesToStructureness3dAlgo.setStructureType( EigenvaluesToStructureness3d::StructureType::ROD );
eigenvaluesToStructureness3dAlgo.setAlpha( 0.75 );
eigenvaluesToStructureness3dAlgo.setBeta( 0.75 );
eigenvaluesToStructureness3dAlgo.setNoiseCutoff( 0.5 );
eigenvaluesToStructureness3dAlgo.execute();

std::cout << "outputImage:" << eigenvaluesToStructureness3dAlgo.outputImage()->toString();

neuron_eigenvalues = imagedev.read_vip_image(imagedev_data.get_image_path("neuron_eigenvalues.vip"))

eigenvalues_to_structureness_3d_algo = imagedev.EigenvaluesToStructureness3d()
eigenvalues_to_structureness_3d_algo.input_eigenvalues_image = neuron_eigenvalues
eigenvalues_to_structureness_3d_algo.lightness = imagedev.EigenvaluesToStructureness3d.BRIGHT
eigenvalues_to_structureness_3d_algo.structure_type = imagedev.EigenvaluesToStructureness3d.ROD
eigenvalues_to_structureness_3d_algo.alpha = 0.75
eigenvalues_to_structureness_3d_algo.beta = 0.75
eigenvalues_to_structureness_3d_algo.noise_cutoff = 0.5
eigenvalues_to_structureness_3d_algo.execute()

print( "output_image:", str( eigenvalues_to_structureness_3d_algo.output_image ) )

ImageView neuron_eigenvalues = Data.ReadVipImage( @"Data/images/neuron_eigenvalues.vip" );

EigenvaluesToStructureness3d eigenvaluesToStructureness3dAlgo = new EigenvaluesToStructureness3d
{
    inputEigenvaluesImage = neuron_eigenvalues,
    lightness = EigenvaluesToStructureness3d.Lightness.BRIGHT,
    structureType = EigenvaluesToStructureness3d.StructureType.ROD,
    alpha = 0.75,
    beta = 0.75,
    noiseCutoff = 0.5
};
eigenvaluesToStructureness3dAlgo.Execute();

Console.WriteLine( "outputImage:" + eigenvaluesToStructureness3dAlgo.outputImage.ToString() );

Function Examples

auto neuron_eigenvalues = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "neuron_eigenvalues.vip" );

auto result = eigenvaluesToStructureness3d( neuron_eigenvalues, EigenvaluesToStructureness3d::Lightness::BRIGHT, EigenvaluesToStructureness3d::StructureType::ROD, 0.75, 0.75, 0.5 );

std::cout << "outputImage:" << result->toString();

neuron_eigenvalues = imagedev.read_vip_image(imagedev_data.get_image_path("neuron_eigenvalues.vip"))

result = imagedev.eigenvalues_to_structureness_3d( neuron_eigenvalues, imagedev.EigenvaluesToStructureness3d.BRIGHT, imagedev.EigenvaluesToStructureness3d.ROD, 0.75, 0.75, 0.5 )

print( "output_image:", str( result ) )

ImageView neuron_eigenvalues = Data.ReadVipImage( @"Data/images/neuron_eigenvalues.vip" );

IOLink.ImageView result = Processing.EigenvaluesToStructureness3d( neuron_eigenvalues, EigenvaluesToStructureness3d.Lightness.BRIGHT, EigenvaluesToStructureness3d.StructureType.ROD, 0.75, 0.75, 0.5 );

Console.WriteLine( "outputImage:" + result.ToString() );

EigenvaluesToStructureness3d

- Function Syntax

+ Class Syntax

Parameters

Object Examples

Function Examples

Function Syntax

Class Syntax