Difference between revisions of "DBP2:UNC:Regional Cortical Thickness Pipeline"

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=== Usage (Command Line) ===
 
=== Usage (Command Line) ===
  
−
Input T1_weighted image:
+
Input T1_weighted image:  
−
Input T1-weigthed atlas:
+
Input T1-weigthed atlas:  
 
Input regional atlas (parcellation map):  
 
Input regional atlas (parcellation map):  
  
 
:* 1. Tissue segmentation
 
:* 1. Tissue segmentation
−
 
+
:**Input: EMS-param.xml
 +
:**Output: Image_Corrected_EMS.gipl, Label.gipl
 +
  itkEMSCLP EMS-param.xml
 
:* 2. Skull stripping
 
:* 2. Skull stripping
−
 
+
:**Input: Label.gipl,  Image_Corrected_EMS.gipl
 +
:**Output: Image_Corrected_EMS_Stripped.gipl, BinaryMask.gipl (optionnal)
 +
  SegPostProcessCLP Label.gipl  Image_Corrected_EMS_Stripped.gipl --skullstripping  Image_Corrected_EMS_Stripped.gipl (--mask BinaryMask.gipl –dilate)
 
:* 3. Deformable registration of pediatric regional atlas
 
:* 3. Deformable registration of pediatric regional atlas
 
:** 3.1 Deformable registration of T1-weighted pediatric atlas
 
:** 3.1 Deformable registration of T1-weighted pediatric atlas
 +
:***Input: Atlas.gipl, Image_Corrected_EMS_Stripped.gipl
 +
:***Output: Atlas_Registered.gipl, Atlas_Registered_Transform.txt
 +
  RegisterImages Image_Corrected_EMS_Stripped.gipl Atlas.gipl –resampledImage  Atlas_Registered.gipl –saveTransform Atlas_Registered_Transform.txt –registration PipelineBSpline
 
:** 3.2. Applying transformation to the parcellation map
 
:** 3.2. Applying transformation to the parcellation map
 +
:***Input: Parcellation.gipl,  Atlas_Registered_Transform.txt, Image_Corrected_EMS_Stripped.gipl
 +
:***Output:  Parcellation_Registered.gipl
 +
  ResampleVolume2 Parcellation.gipl Parcellation_Registered.gipl -f Parcellation_Registered.gipl -i nn -R Image_Corrected_EMS_Stripped.gipl
 
:* 4. Cortical Thickness
 
:* 4. Cortical Thickness
−
 
+
:**Input: Parcellation_Registered.gipl, Label.gipl
 +
:**Output: CortThick_Result_Dir/
 +
  CortThickCLP CortThick_Result_Dir/ --par  Parcellation_Registered.gipl --inputSeg Label.gipl --Wm --Gm --Vtk --Sdm –BvsI --GMMaps
  
 
=== Analysis on a small pediatric dataset ===
 
=== Analysis on a small pediatric dataset ===

Revision as of 19:39, 12 August 2008

Home < DBP2:UNC:Regional Cortical Thickness Pipeline

Back to UNC Cortical Thickness Roadmap


Objective

We would like to create an end-to-end application within Slicer3 allowing individual and group analysis of regional cortical thickness.

General information

Pipeline description (steps)

Input: T1-weighted image

  • 1. Tissue segmentation
    • Tool: itkEMS (UNC Slicer3 external module)
  • 2. Skull stripping
    • Tool: SegPostProcess (UNC Slicer3 external module)
  • 3. Deformable registration of pediatric regional atlas
    • 3.1 Deformable registration of T1-weighted pediatric atlas
      • Tool: RegisterImages (Slicer3 module)
    • 3.2. Applying transformation to the parcellation map
      • Tool: ResampleVolume2 (Slicer3 module)
  • 4. Cortical Thickness
    • Tool: CortThick (UNC Slicer3 module)

All the tools used in the current pipeline are Slicer3 modules, some of them being UNC external modules. Thus, the user can process a data and compute a cortical thickness regional analysis, either using Slicer3 GUI modules or by command lines tools

Usage (Command Line)

Input T1_weighted image: Input T1-weigthed atlas: Input regional atlas (parcellation map):

  • 1. Tissue segmentation
    • Input: EMS-param.xml
    • Output: Image_Corrected_EMS.gipl, Label.gipl
 itkEMSCLP EMS-param.xml
  • 2. Skull stripping
    • Input: Label.gipl, Image_Corrected_EMS.gipl
    • Output: Image_Corrected_EMS_Stripped.gipl, BinaryMask.gipl (optionnal)
 SegPostProcessCLP Label.gipl  Image_Corrected_EMS_Stripped.gipl --skullstripping  Image_Corrected_EMS_Stripped.gipl (--mask BinaryMask.gipl –dilate)
  • 3. Deformable registration of pediatric regional atlas
    • 3.1 Deformable registration of T1-weighted pediatric atlas
      • Input: Atlas.gipl, Image_Corrected_EMS_Stripped.gipl
      • Output: Atlas_Registered.gipl, Atlas_Registered_Transform.txt
  RegisterImages Image_Corrected_EMS_Stripped.gipl Atlas.gipl –resampledImage  Atlas_Registered.gipl –saveTransform Atlas_Registered_Transform.txt –registration PipelineBSpline
    • 3.2. Applying transformation to the parcellation map
      • Input: Parcellation.gipl, Atlas_Registered_Transform.txt, Image_Corrected_EMS_Stripped.gipl
      • Output: Parcellation_Registered.gipl
  ResampleVolume2 Parcellation.gipl Parcellation_Registered.gipl -f Parcellation_Registered.gipl -i nn -R Image_Corrected_EMS_Stripped.gipl
  • 4. Cortical Thickness
    • Input: Parcellation_Registered.gipl, Label.gipl
    • Output: CortThick_Result_Dir/
  CortThickCLP CortThick_Result_Dir/ --par  Parcellation_Registered.gipl --inputSeg Label.gipl --Wm --Gm --Vtk --Sdm –BvsI --GMMaps

Analysis on a small pediatric dataset

Tests have been computed on a small pediatric dataset, including 2 years old and 4 years old cases

  • 2 Autistic cases
  • 1 developmental delay
  • 1 normal control


In progress

  • Workflow for individual analysis (Slicer3 external module using BatchMake)

Future work

  • UNC Slicer3 external modules available on NITRIC
  • Pediatric atlas (T1-weighted image and parcellation map) available to the community (XNAT?)
  • Workflow for group analysis
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