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

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Back to [[DBP2:UNC:Cortical_Thickness_Roadmap | UNC Cortical Thickness Roadmap]]
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Back to [[DBP2:UNC:Cortical_Thickness_Roadmap | UNC Cortical Thickness Roadmap]]
  
 
[[Image:ArcticLogo.png|thumb|400px|ARCTIC Logo|right]]
 
[[Image:ArcticLogo.png|thumb|400px|ARCTIC Logo|right]]
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:** 2.3. Applying transformation to the parcellation map
 
:** 2.3. Applying transformation to the parcellation map
 
:*** Tool: ResampleVolume2 (Slicer3 module)
 
:*** Tool: ResampleVolume2 (Slicer3 module)
−
:* '''3. Cortical Thickness'''
+
:* '''3. Cortical thickness measurement'''
 
:** Sparse asymmetric local cortical thickness
 
:** Sparse asymmetric local cortical thickness
 
:** Tool: CortThick (UNC Slicer3 external module)
 
:** Tool: CortThick (UNC Slicer3 external module)
 
:* '''4. Statistics'''
 
:* '''4. Statistics'''
−
:** Generate spreesheats with volume informations
+
:** Volume information (WM, GM, CSF, lobes) stored in spreadsheet
 
:** Tools: ImageMath, ImageStat (UNC Slicer3 external modules)
 
:** Tools: ImageMath, ImageStat (UNC Slicer3 external modules)
−
:* '''5. Mesh Creation'''
+
:* '''5. Mesh creation'''
−
:** Generation of white matter and grey matter meshes
+
:** White matter and grey matter meshes creation
 
:** Tool: ModelMaker (Slicer3 module)
 
:** Tool: ModelMaker (Slicer3 module)
−
:* '''6. MRML scene creation'''
+
:* '''6. MRML scene creation for quality control'''
−
:** Creation of a MRML scene describing all the steps of the pipeline
+
:** MRML scene creation allowing quality control for each step of the pipeline
−
 
+
:** Output images and surfaces are automatically displayed
  
 
All the tools used in the current pipeline are Slicer3 modules, some of them being UNC external modules.
 
All the tools used in the current pipeline are Slicer3 modules, some of them being UNC external modules.
 
The user can thus compute an individual regional cortical thickness analysis by running the 'ARCTIC' module, either within Slicer3 or as a command line.
 
The user can thus compute an individual regional cortical thickness analysis by running the 'ARCTIC' module, either within Slicer3 or as a command line.
  
−
== ARCTIC Download ==
+
== Download ==
−
=== Source code available with CVS ===
 
−
 
 
−
====Required softwares====
 
−
 
 
−
* Install required softwares to compile the NeuroLib
 
−
- [http://www.cmake.org/cmake/resources/software.html| CMake]
 
−
 
 
−
- [http://www.batchmake.org/batchmake/resources/software.html| BatchMake] (v 1.0.8 needed, use cvs access)
 
−
 
 
−
- [http://www.fltk.org/software.php| FLTK]
 
−
 
 
−
- [http://www.slicer.org/DownloadSlicer.php/Nightly| Slicer Nighly Build]
 
−
 
 
  
−
====Download and install the NeuroLib====
+
=== ARCTIC download ===
  
−
* Create and go to a NeuroLib/ directory
+
Source code, executables and tutorial are available on [http://www.nitrc.org/projects/arctic NITRC]
−
  mkdir NeuroLib
 
−
  cd NeuroLib
 
−
* Make the following commands :
 
−
  cvs -d :pserver:anonymous@demeter.ia.unc.edu:/cvsroot login (press Enter for password)
 
−
  cvs -d :pserver:anonymous@demeter.ia.unc.edu:/cvsroot co NeuroLib
 
−
* Create and go to a Neurolib-build/ directory
 
−
  mkdir NeuroLib-build
 
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  cd NeuroLib-build
 
−
* Start the compilation while launching 'ccmake'
 
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  ccmake ../NeuroLib
 
−
*Configure the compilation
 
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  Set ARCTIC at "ON"
 
−
  Press 'c' to start the configuration
 
  
−
=== Executables and tutorial dataset ===  
+
=== Complementary downloads ===
−
Available on NITRC : http://www.nitrc.org/projects/arctic/
 
  
−
== Complementary Downloads ==
+
==== Brain atlases ====
 +
Four brain atlases are available on MIDAS:
 +
:* [http://www.insight-journal.org/midas/item/view/2277 Pediatric atlas]
 +
:* [http://www.insight-journal.org/midas/item/view/2328 Adult atlas]
 +
:* [http://www.insight-journal.org/midas/item/view/2330 Elderly atlas]
 +
:* [http://www.insight-journal.org/midas/item/view/2283 Primate atlas]
  
−
=== Pediatric atlas ===  
+
==== Pediatric Brain MRI data ====  
−
Available on MIDAS : http://www.insight-journal.org/midas/item/view/2277
+
[http://insight-journal.org/midas/community/view/24 Data of 2 autistic children and 2 normal controls] (male, female) scanned at 2 years with follow up at 4 years from a 1.5T Siemens scanner. Files include structural data, tissue segmentation label map and subcortical structures segmentation.
  
−
=== Tutorials ===
+
==== Tutorials ====
−
• '''ARCTIC tutorial''' : end-to-end Slicer3 module to perform automatic regional cortical thickness analysis[[Media:ARCTIC-Slicer3-Tutorial.ppt|‏ [ppt]]][[Media:ARCTIC-Slicer3-Tutorial.pdf|‏ [pdf]]]
+
*'''ARCTIC tutorial''' : end-to-end Slicer3 module to perform automatic regional cortical thickness analysis[[Media:ARCTIC-Slicer3-Tutorial.ppt|‏ [ppt]]][[Media:ARCTIC-Slicer3-Tutorial.pdf|‏ [pdf]]]
 +
**1st Prize: NAMIC tutorial contest AHM 2009
 +
**2nd Prize: NAMIC tutorial contest summer project week 2009
 +
*'''UNC Modules tutorial''' : UNC Slicer3 modules to perform regional cortical thickness analysis step by step[[Media:UNC_Modules-Slicer3-Tutorial.ppt| [ppt]‏]][[Media:UNC_Modules-Slicer3-Tutorial.pdf| [pdf]‏]]
  
−
• '''UNC Modules tutorial''' : UNC Slicer3 modules to perform regional cortical thickness analysis step by step[[Media:UNC_Modules-Slicer3-Tutorial.ppt| [ppt]‏]][[Media:UNC_Modules-Slicer3-Tutorial.pdf| [pdf]‏]]
+
*'''[https://www.slicer.org/wiki/Modules:ARCTIC-Documentation-3.6 Online documentation within Slicer 3.6]'''
  
 
<center>
 
<center>
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|}
 
|}
 
</center>
 
</center>
−
 
−
== ARCTIC (Automatic Regional Cortical ThICkness) usage: ==
 
−
 
−
 
−
=== Prerequities ===
 
−
 
−
Add directories to the PATH variable
 
−
  -tcsh usage : setenv PATH ARCTIC-Executables-Directory:Slicer3D-Plugins-Directory:Batchmake-Directory:${PATH}
 
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  -bash usage : export PATH=ARCTIC-Executables-Directory:Slicer3D-Plugins-Directory:Batchmake-Directory:${PATH}
 
−
  Notice : To execute ARCTIC within Slicer3D, it is not necessary to add "Slicer3D-Plugins-Directory" in the PATH.
 
−
 
−
Add libraries to the LD_LIBRARY_PATH variable
 
−
  -tcsh usage : setenv SLICERLIBPATH Slicer-nightly-build/lib
 
−
                setenv LD_LIBRARY_PATH ${LD_LIBRARY_PATH}:${SLICERLIBPATH}/TEEM-1.9:${SLICERLIBPATH}/vtk-5.2:${SLICERLIBPATH}:${SLICERLIBPATH}/InsightToolkit:${SLICERLIBPATH}/ModuleDescriptionParser:${SLICERLIBPATH}/vtkITK:${SLICERLIBPATH}/MRML:${SLICERLIBPATH}/SlicerIO:${SLICERLIBPATH}/Slicer3:${SLICERLIBPATH}/FreeSurfer:${SLICERLIBPATH}/vtkTeem:${SLICERLIBPATH}/Teem-1.10.0:${SLICERLIBPATH}/KWWidgets:${SLICERLIBPATH}/Python/lib:${SLICERLIBPATH}/bmModuleDescriptionParser:${SLICERLIBPATH}/BatchMake
 
−
  -bash usage : export SLICERLIBPATH=Slicer-nightly-build/lib
 
−
                export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${SLICERLIBPATH}/TEEM-1.9:${SLICERLIBPATH}/vtk-5.2:${SLICERLIBPATH}:${SLICERLIBPATH}/InsightToolkit:${SLICERLIBPATH}/ModuleDescriptionParser:${SLICERLIBPATH}/vtkITK:${SLICERLIBPATH}/MRML:${SLICERLIBPATH}/SlicerIO:${SLICERLIBPATH}/Slicer3:${SLICERLIBPATH}/FreeSurfer:${SLICERLIBPATH}/vtkTeem:${SLICERLIBPATH}/Teem-1.10.0:${SLICERLIBPATH}/KWWidgets:${SLICERLIBPATH}/Python/lib:${SLICERLIBPATH}/bmModuleDescriptionParser:${SLICERLIBPATH}/BatchMake
 
−
 
−
Set an environment variable
 
−
  -tcsh usage : setenv BatchmakeWrapper_Dir Batchmake-Wrapper-Directory
 
−
  -bash usage : export BatchmakeWrapper_Dir=Batchmake-Wrapper-Directory
 
−
 
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Set ARCTIC as a Slicer3D module
 
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  Within Slicer3D : View -> Applications Settings -> Module Settings -> Add a preset button and then select the ARCTIC-Executables-Directory/
 
−
 
−
=== Command line execution ===
 
−
 
−
ARCTIC can be use with two different input modes.
 
−
 
−
==== Raw Image Mode ====
 
−
 
−
Inputs: T1-weighted image, T1-weighted atlas, regional atlas (parcellation map)
 
−
 
−
  ARCTIC --T1 Image_T1.gipl --segAtlasDir TissueSegmentationAtlasDirectory/ --atlas Atlas.gipl --atlasParcellation Parcellation.gipl
 
−
 
−
Complementary flags
 
−
  --T2 Image_T2.gipl / --pd Image_PD.gipl : T2 and/or Pd-weighted image(s) can be added to improve tissue segmentation
 
−
  --orientation RAI : if the orientation of your file(s) is different than the default value (RAI), add this flag to set the right orientation
 
−
  --atlasOrientation : if the orientation of your tissue segmentation atlas is different than the default value (RAI), add this flag to set the right orientation
 
−
  --atlasType T1 : if the type of your tissue segmentation atlas is different than T1 (default value)
 
−
  --outputDir output_directory/ : if you want to select the output directory, add this flag and indicate the path an existing folder
 
−
  --SaveWM  WMCorticalThicknessMap.gipl / --SaveGM GMCorticalThicknessMap.gipl : those flags are used to save a volume with information of the average cortical thickness on WM/GM boundary(ies), the fileName needed is a path with the name of the output volume
 
−
 
−
==== Segmented Image Mode ====
 
−
 
−
Inputs: label image, regional atlas (parcellation map)
 
−
 
−
  ARCTIC --label label_image.gipl --rawImage raw_image.gipl --atlas Atlas.gipl --atlasParcellation Parcellation.gipl
 
−
  Notice : the "raw_image.gipl" file is a MRI image of the case. It can be a T1-weighted image as well as a T2 or a PD.
 
−
 
−
Complementary flags
 
−
  --WMLabel 1 / --GMLabel 2 / --CSFLabel 3 : if tour label are different than the default value
 
−
  --outputDir output_directory/ : if you want to select the output directory, add this flag and indicate the path an existing folder
 
−
  --SaveWM  WMCorticalThicknessMap.gipl / --SaveGM GMCorticalThicknessMap.gipl : those flags are used to save a volume with information of the average cortical thickness on WM/GM boundary(ies), the fileName needed is a path with the name of the output volume
 
−
 
−
=== Step by step command line execution ===
 
−
 
−
:* '''1. Tissue segmentation'''
 
−
:**Input: EMSparam.xml
 
−
:**Output: Image_Corrected_EMS.gipl, Label.gipl
 
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  itkEMSCLP --XMLFile EMSparam.xml
 
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:* '''2. Skull stripping'''
 
−
:**Input: Label.gipl,  Image_Corrected_EMS.gipl
 
−
:**Output: Image_Corrected_EMS_Stripped.gipl, BinaryMask.gipl (optional)
 
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  SegPostProcessCLP Label.gipl  Image_Corrected_EMS_Stripped.gipl --skullstripping  Image_Corrected_EMS.gipl
 
−
:* '''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 Atlas_Registered_Transform.txt -i nn -R Image_Corrected_EMS_Stripped.gipl
 
−
:* '''4. Cortical Thickness'''
 
−
:**Input: Parcellation_Registered.gipl, Label.gipl
 
−
:**Output: CortThick_Result_Dir/, WMCorticalThicknessMap, GMCorticalThicknessMap
 
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  CortThickCLP CortThick_Result_Dir/ --par  Parcellation_Registered.gipl --inputSeg Label.gipl --SaveWM  WMCorticalThicknessMap  --SaveGM GMCorticalThicknessMap
 
  
 
== Pipeline validation ==
 
== Pipeline validation ==
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=== Comparison to state of the art ===
 
=== Comparison to state of the art ===
  
−
We would like to compare our pipeline with FreeSurfer. We have thus started to perform a regional statistical analysis using Pearson's correlation coefficient on a pediatric dataset including 90 cases.
+
We would like to compare our pipeline with FreeSurfer. We have thus performed a [[DBP2:UNC:Cortical_Thickness_Comparison | regional statistical analysis]] based on Pearson's correlation on an adult dataset (FreeSurfer's publicly available dataset) including 40 cases. We also performed [[DBP2:UNC:Cortical_Thickness_Comparison#Tests_on_a_longitudinal_pediatric_autism_study | tests on a longitudinal autism study]] of 86 subject aged 2-4 years.
−
 
 
−
Two distinct groups are considered: 2 year-old cases and 4 year-old cases.  
 
−
 
 
  
 
== Planning ==
 
== Planning ==
Line 196: Line 97:
 
:* Workflow for individual analysis (Slicer3 external module using BatchMake)
 
:* Workflow for individual analysis (Slicer3 external module using BatchMake)
 
:* 2 Tutorials with application example on a small dataset : "How to use the UNC modules to compute the regional cortical thickness" and "How to use ARCTIC"
 
:* 2 Tutorials with application example on a small dataset : "How to use the UNC modules to compute the regional cortical thickness" and "How to use ARCTIC"
−
:* Pediatric atlases available to the community through MIDAS
+
:* Pediatric and adult brain atlases available to the community via MIDAS
−
:* ARCTIC available to the community through NITRC: executables (UNC external modules for Slicer3) and Tutorial dataset
+
:* ARCTIC available to the community via NITRC: executables (UNC external modules for Slicer3) and Tutorial dataset
−
:* New version including quality control through MRML scene, and WM, GM models generation  
+
:** New version including quality control through MRML scene, and WM, GM models generation  
 +
:** Mac and windows executables also available on to the community through NITRC
 +
:** Input images orientation automatically managed by ARCTIC
 
:* ARCTIC source code (SVN, CVS) available to the community
 
:* ARCTIC source code (SVN, CVS) available to the community
 +
:* ARCTIC executable can be downloaded directly within Slicer3 using the extension wizard
 +
:* Comparison to FreeSurfer (40 cases dataset): pearson correlation analysis
 +
 +
== References ==
  
−
=== In progress ===
+
*Hazlett HC, Poe MD, Gerig G, Styner M, Chappell C, Smith RG, Vachet, C., & Piven, J., Early brain overgrowth in autism results from an increase in cortical surface area before age 2, Arch Gen Psychiatry. 2011;68(5):1-10
−
:* Comparison to FreeSurfer (180 cases dataset): pearson correlation analysis
+
*H.C. Hazlett, C. Vachet, C. Mathieu, M. Styner, J. Piven, Use of the Slicer3 Toolkit to Produce Regional Cortical Thickness Measurement of Pediatric MRI Data, presented at the 8th Annual International Meeting for Autism Research (IMFAR) Chicago, IL 2009.
−
:* Mac and windows executables available on to the community through NITRC
+
*C. Mathieu, C. Vachet, H.C. Hazlett, G. Geric, J. Piven, and M. Styner, ARCTIC – Automatic Regional Cortical ThICkness Tool, UNC Radiology Research Day 2009 abstract

Latest revision as of 17:46, 10 July 2017

Home < DBP2:UNC:Regional Cortical Thickness Pipeline
Back to  UNC Cortical Thickness Roadmap
ARCTIC Logo


Objective

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

This page describes the related pipeline with its basic components, as well as its validation.


Pipeline overview

A Slicer3 high-level module for individual cortical thickness analysis has been developed: ARCTIC (Automatic Regional Cortical ThICkness)

Input: RAW images (T1-weighted, T2-weighted, PD-weighted images)

  • 1. Tissue segmentation
    • Probabilistic atlas-based automatic tissue segmentation via an Expectation-Maximization scheme
    • Tool: itkEMS (UNC Slicer3 external module)
  • 2. Regional atlas deformable registration
    • 2.1 Skull stripping using previously computed tissue segmentation label image
      • Tool: SegPostProcess (UNC Slicer3 external module)
    • 2.2 T1-weighted atlas deformable registration
      • B-spline pipeline registration
      • Tool: RegisterImages (Slicer3 module)
    • 2.3. Applying transformation to the parcellation map
      • Tool: ResampleVolume2 (Slicer3 module)
  • 3. Cortical thickness measurement
    • Sparse asymmetric local cortical thickness
    • Tool: CortThick (UNC Slicer3 external module)
  • 4. Statistics
    • Volume information (WM, GM, CSF, lobes) stored in spreadsheet
    • Tools: ImageMath, ImageStat (UNC Slicer3 external modules)
  • 5. Mesh creation
    • White matter and grey matter meshes creation
    • Tool: ModelMaker (Slicer3 module)
  • 6. MRML scene creation for quality control
    • MRML scene creation allowing quality control for each step of the pipeline
    • Output images and surfaces are automatically displayed

All the tools used in the current pipeline are Slicer3 modules, some of them being UNC external modules. The user can thus compute an individual regional cortical thickness analysis by running the 'ARCTIC' module, either within Slicer3 or as a command line.

Download

ARCTIC download

Source code, executables and tutorial are available on NITRC

Complementary downloads

Brain atlases

Four brain atlases are available on MIDAS:

Pediatric Brain MRI data

Data of 2 autistic children and 2 normal controls (male, female) scanned at 2 years with follow up at 4 years from a 1.5T Siemens scanner. Files include structural data, tissue segmentation label map and subcortical structures segmentation.

Tutorials

  • ARCTIC tutorial : end-to-end Slicer3 module to perform automatic regional cortical thickness analysis‏ [ppt]‏ [pdf]
    • 1st Prize: NAMIC tutorial contest AHM 2009
    • 2nd Prize: NAMIC tutorial contest summer project week 2009
  • UNC Modules tutorial : UNC Slicer3 modules to perform regional cortical thickness analysis step by step [ppt]‏ [pdf]‏
T1-weighted skull-stripped image
Parcellation image
Cortical thickness on WM surface
Cortical thickness information

Pipeline validation

Analysis on a small pediatric dataset

Tests have been computed on a small pediatric dataset which includes 2 year-old and 4 year-old cases.

  • 16 autistic cases
  • 1 developmental delay
  • 3 normal control

Comparison to state of the art

We would like to compare our pipeline with FreeSurfer. We have thus performed a regional statistical analysis based on Pearson's correlation on an adult dataset (FreeSurfer's publicly available dataset) including 40 cases. We also performed tests on a longitudinal autism study of 86 subject aged 2-4 years.

Planning

Done

  • Workflow for individual analysis (Slicer3 external module using BatchMake)
  • 2 Tutorials with application example on a small dataset : "How to use the UNC modules to compute the regional cortical thickness" and "How to use ARCTIC"
  • Pediatric and adult brain atlases available to the community via MIDAS
  • ARCTIC available to the community via NITRC: executables (UNC external modules for Slicer3) and Tutorial dataset
    • New version including quality control through MRML scene, and WM, GM models generation
    • Mac and windows executables also available on to the community through NITRC
    • Input images orientation automatically managed by ARCTIC
  • ARCTIC source code (SVN, CVS) available to the community
  • ARCTIC executable can be downloaded directly within Slicer3 using the extension wizard
  • Comparison to FreeSurfer (40 cases dataset): pearson correlation analysis

References

  • Hazlett HC, Poe MD, Gerig G, Styner M, Chappell C, Smith RG, Vachet, C., & Piven, J., Early brain overgrowth in autism results from an increase in cortical surface area before age 2, Arch Gen Psychiatry. 2011;68(5):1-10
  • H.C. Hazlett, C. Vachet, C. Mathieu, M. Styner, J. Piven, Use of the Slicer3 Toolkit to Produce Regional Cortical Thickness Measurement of Pediatric MRI Data, presented at the 8th Annual International Meeting for Autism Research (IMFAR) Chicago, IL 2009.
  • C. Mathieu, C. Vachet, H.C. Hazlett, G. Geric, J. Piven, and M. Styner, ARCTIC – Automatic Regional Cortical ThICkness Tool, UNC Radiology Research Day 2009 abstract
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