DegreeOfAnisotropy
Computes an anisotropy indicator of a binary image with a mean intercept length method.
Access to parameter description
For an introduction:
Mean intercept length proceeds by sending a set of oriented rays through the binary input image. A set of discreet angles are processed with a pitch angle fixed at 10 degrees. For each orientation, a regularly spaced grid of rays is shot. The length of the intersection of each ray with the objects encountered is measured, and averaged over the grid of rays. The spacing of this grid is controlled by the interceptDistance parameter, which represents the distance between two intercept lines.
The distribution of the mean intercept length, as a function of the angle, is analyzed using an eigenvalue decomposition. This analysis allows one to extract $\lambda_1$ and $\lambda_2$, respectively, the maximum and minimum eigenvalues. The closer these values are, the less the structural anisotropy is. Indeed, $\lambda_1=\lambda_2$ means that there is no privileged structural direction. $$ DA = \left( 1-\left|\frac{\lambda_2}{\lambda_1}\right| \right) $$ Degree of anisotropy is 0 for total isotropy, and 1 for total anisotropy.
Reference:
A.Odgaard. "Three-Dimensional Methods for Quantification of Cancellous Bone Architecture". Bone, vol. 20, no. 4, pp. 315-328, 1997.
See also
Access to parameter description
For an introduction:
- section Image Analysis
- section Moment And Orientation
Mean intercept length proceeds by sending a set of oriented rays through the binary input image. A set of discreet angles are processed with a pitch angle fixed at 10 degrees. For each orientation, a regularly spaced grid of rays is shot. The length of the intersection of each ray with the objects encountered is measured, and averaged over the grid of rays. The spacing of this grid is controlled by the interceptDistance parameter, which represents the distance between two intercept lines.
The distribution of the mean intercept length, as a function of the angle, is analyzed using an eigenvalue decomposition. This analysis allows one to extract $\lambda_1$ and $\lambda_2$, respectively, the maximum and minimum eigenvalues. The closer these values are, the less the structural anisotropy is. Indeed, $\lambda_1=\lambda_2$ means that there is no privileged structural direction. $$ DA = \left( 1-\left|\frac{\lambda_2}{\lambda_1}\right| \right) $$ Degree of anisotropy is 0 for total isotropy, and 1 for total anisotropy.
Reference:
A.Odgaard. "Three-Dimensional Methods for Quantification of Cancellous Bone Architecture". Bone, vol. 20, no. 4, pp. 315-328, 1997.
See also
Function Syntax
This function returns outputMeasurement.
// Function prototype
AnisotropyDegreeMsr::Ptr degreeOfAnisotropy( std::shared_ptr< iolink::ImageView > inputBinaryImage, int32_t interceptDistance, AnisotropyDegreeMsr::Ptr outputMeasurement = NULL );
This function returns outputMeasurement.
// Function prototype. degree_of_anisotropy( input_binary_image, intercept_distance = 3, output_measurement = None )
This function returns outputMeasurement.
// Function prototype. public static AnisotropyDegreeMsr DegreeOfAnisotropy( IOLink.ImageView inputBinaryImage, Int32 interceptDistance = 3, AnisotropyDegreeMsr outputMeasurement = null );
Class Syntax
Parameters
Class Name | DegreeOfAnisotropy |
---|
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
inputBinaryImage |
The input binary image. | Image | Binary | nullptr | |
interceptDistance |
The distance in pixels between two intercept lines. | Int32 | >=1 | 3 | |
outputMeasurement |
The output measurement result. | AnisotropyDegreeMsr | nullptr |
Object Examples
auto polystyrene_sep = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene_sep.vip" ); DegreeOfAnisotropy degreeOfAnisotropyAlgo; degreeOfAnisotropyAlgo.setInputBinaryImage( polystyrene_sep ); degreeOfAnisotropyAlgo.setInterceptDistance( 3 ); degreeOfAnisotropyAlgo.execute(); std::cout << "anisotropy: " << degreeOfAnisotropyAlgo.outputMeasurement()->anisotropy( 0 ) ;
polystyrene_sep = imagedev.read_vip_image(imagedev_data.get_image_path("polystyrene_sep.vip")) degree_of_anisotropy_algo = imagedev.DegreeOfAnisotropy() degree_of_anisotropy_algo.input_binary_image = polystyrene_sep degree_of_anisotropy_algo.intercept_distance = 3 degree_of_anisotropy_algo.execute() print( "anisotropy: ", str( degree_of_anisotropy_algo.output_measurement.anisotropy( 0 ) ) )
ImageView polystyrene_sep = Data.ReadVipImage( @"Data/images/polystyrene_sep.vip" ); DegreeOfAnisotropy degreeOfAnisotropyAlgo = new DegreeOfAnisotropy { inputBinaryImage = polystyrene_sep, interceptDistance = 3 }; degreeOfAnisotropyAlgo.Execute(); Console.WriteLine( "anisotropy: " + degreeOfAnisotropyAlgo.outputMeasurement.anisotropy( 0 ) );
Function Examples
auto polystyrene_sep = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene_sep.vip" ); auto result = degreeOfAnisotropy( polystyrene_sep, 3 ); std::cout << "anisotropy: " << result->anisotropy( 0 ) ;
polystyrene_sep = imagedev.read_vip_image(imagedev_data.get_image_path("polystyrene_sep.vip")) result = imagedev.degree_of_anisotropy( polystyrene_sep, 3 ) print( "anisotropy: ", str( result.anisotropy( 0 ) ) )
ImageView polystyrene_sep = Data.ReadVipImage( @"Data/images/polystyrene_sep.vip" ); AnisotropyDegreeMsr result = Processing.DegreeOfAnisotropy( polystyrene_sep, 3 ); Console.WriteLine( "anisotropy: " + result.anisotropy( 0 ) );