Documentation/Nightly/Modules/BrainStructuresSegmenter

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Introduction and Acknowledgements

Extension: BrainTissuesExtension Webpage: http://dcm.ffclrp.usp.br/csim/ Author: Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics) Contact: Antonio Carlos da S. Senra Filho, <email>acsenrafilho@usp.br</email>

CSIM Laboratory   University of Sao Paulo   CAPES Brazil

Module Description

This module offer a ...

Use Cases

• Use Case 1: a
  • b

• 

  Raw T1 weighted MRI Image

• 

  T1 weighted MRI Image with AAD filter (q=1.2)

Panels and their use

User Interface

IO:

• Input Volume
  • Select the input image
• Output Volume
  • Set the output image file which the filters should place the final result

Diffusion Parameters:

• Conductance
  • The conductance regulates the diffusion intensity in the neighbourhood area. Choose a higher conductance if the input image has strong noise seem in the whole image space.
• Number of Iteractions
  • The number of iterations regulates the numerical simulation of the anomalous process over the image. This parameters is also related with the de-noising intensity, however it is more sensible to the noise intensity. Choose the higher number of iterations if the image presents high intensity noise which is not well treated by the conductance parameter.
• Time Step
  • The time step is a normalization parameters for the numerical simulation. The maximum value, given as default, is set to 3D images. Lower time step restrict the numerical simulation of the anomalous process.
• Anomalous parameter
  • The anomalous parameter (or q value) is the generalization parameters responsible to give the anomalous process approach on the diffusion equation. See the reference paper to choose the appropriate q value (at moment, only tested in MRI T1 and T2 weighted images).

Similar Modules

• IAD Image Filter
• Gradient Anisotropic Image Filter

References

• paper