multi-scale hessian-based measure 參數設定

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 Multi-Scale Hessian-Based Measure 參數設定. Wei –Lu Lin. Outline. MultiScaleHessianBasedMeasureImageFilter H essianToObjectnessMeasureImageFilter Example( Vessels case :IM065.dcm). I tk :: MultiScaleHessianBasedMeasureImageFilter. - PowerPoint PPT Presentation

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 Multi-Scale Hessian-Based Measure參數設定

Wei –Lu Lin

Outline

•MultiScaleHessianBasedMeasureImageFilter

• HessianToObjectnessMeasureImageFilter

• Example( Vessels case :IM065.dcm)

Itk:: MultiScaleHessianBasedMeasureImag

eFilter• A filter to enhance structures using Hessian

eigensystem-based measures in a multiscale framework

• SetSigmaMinimum

• Set/Get macros for SigmaMin

• SetSigmaMaximum

• Set/Get macros for SigmaMax

• SetNumberOfSigmaSteps

• Set/Get macros for Number of Scales

Itk::HessianToObjectnessMeasureImageFilter

• A filter to enhance M-dimensional objects in N-dimensional images

• SetAlpha

• SetBeta

• SetGamma

• SetAlpha

• Set/Get Alpha, the weight corresponding to R_A (the ratio of the smallest eigenvalue that has to be large to the larger ones). Smaller values lead to increased sensitivity to the object dimensionality

Itk::HessianToObjectnessMeasureImageFilter

• SetBeta

• Set/Get Beta, the weight corresponding to R_B (the ratio of the largest eigenvalue that has to be small to the larger ones). Smaller values lead to increased sensitivity to the object dimensionality

Itk::HessianToObjectnessMeasureImageFilter

• SetGamma

• Set/Get Gamma, the weight corresponding to S (the Frobenius norm of the Hessian matrix, or second-order structureness)

Itk::HessianToObjectnessMeasureImageFilter

Example

• sigmaMinimum = 2.0

• sigmaMaximum = 3.0

• numberOfSigmaSteps = 1

• Alpha = 0.5

• Beta = 0.5

• Gamma = 5.0Vessel case :IM065.dcm

Example

• Tune the sigmaMinimum and sigmaMaximum

sigmaMinimum = 2.0 sigmaMaximum = 3.0

sigmaMinimum = 10.0 sigmaMaximum = 11.0

Example

• Tune the numberOfSigmaSteps

numberOfSigmaSteps = 1

numberOfSigmaSteps = 10

Example• Tune the Alpha

Alpha = 0.5 Alpha = 10.0

Example• Tune the Beta

Beta = 0.5 Beta = 10.0

Example

• Tune the Gamma

Gamma = 5.0 Gamma = 2.0

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