Welcome to ANTx2

You can download ANTx2 from GitHub.

Tutorials

main ANTx gui

Aim

Shows the main ANTx Gui

Steps

 

  → Tutorial: "ANTx_mainGUI.pdf"


Registration to Standard-Space/Atlas-Registration

Aim

The tutorial shows how to setup the toolbox and register a t2w-image to Standard-Space

Steps

(1) Setup ANT-TBX,
(2) Organize the study folder
(3) Start ANT-TBX
(4) Create a new project and load a project file
(5) Import Bruker raw-data
(6) Inspect the imported raw data
(7) Rename files, delete files, define the input image ("t2.nii") for atlas registration
(8) Perform atlas registration (registratiomn to standard space)
(9) Extract a 3d volume from a 4D volume and transform the 3d volume to Allen Space

  → Tutorial: "tutorial_atlasRegistration.pdf"


Bruker Raw-Data Import

Aim

This tutorial shows how to import Bruker raw-data

Steps

- Setup ANT-TBX,
- Organize the study folder
- Start ANT-TBX
- Create a new project and load a project file
- Import Bruker raw-data

  → Tutorial: "tutorial_brukerImport.pdf"


Orientation, Registration & Manual Registration

Aim

The tutorial covers the following topics:
- Determine the orientation of the animal brain
- Template registration
- Manual coregistration

Steps

Prerequisites
Data example
1) Renaming files
2) Examine Image Orientation (Panel selection)
3) Examine Image Orientation via 3-Point-Selection
4) Registration to Template - PART-1: Initialization + Auto Coregistration
5) Examine Automatic (rigid) Coregistration
6) Adding an Animal with a Different Orientation
7) Registration to Template - PART-2: Manual Coregistration
8) Registration to Template - PART-3: Segmentation and Nonlinear Registration
9) Check Template Registration

  → Tutorial: "tutorial_orientation_and_manucoreg.pdf"


Obtain orientation via 3-point-selection

Aim

The tutorial briefly shows how to determine the orientation-type via 3-point-selection

  → Tutorial: "getOrientation_via_3pointSelection.pdf"


Voxelwise statistic, two independent groups

Aim

This tutorial shows how to perform Voxelwise statistic for two independent groups

CONTENTS
1) Create a group-assignment (Excel-file)
2) Perform the voxelwise-T-test (independent group)
3) Examine Results
3.1) EXPORT RESULTS-TABLE AS EXCELFILE
3.2) DISPLAY RESULT TABLE IN COMMAND WINDOW
3.3) EXPORT RESULTS-TABLE AS TXT-FILE
3.4) SAVE THREHOLDED IMAGE AS NIFTI-FILE
3.5) EXTRACT PEAK DATA
3.6) CREATE SUMMARY OF CURRENT CONTRAST
3.7) Change to Cluster-based approach
4) Check the other contrast
5) CREATE BIG-SUMMARY
6) Define new Contrast
7) Work from Command line
7.1) run voxelwise statistic from command line
7.2) Create full report

  → Tutorial: "tutorial_voxwiseStatistic_independentTest.pdf"


Prepare DTI-pipeline

Aim

This tutorial shows how to prepare the data for the DTI-MRtrix-pipeline

CONTENTS
PART-1: BASICS+REGISTRATION
 1) Prepare Study
  GO TO STUDY-FOLDER
  UPDATE ANT-TOOLBOX
  CREATE A PROJECT-FILE:
  Open ANT-gui & CREATE AN ANTx-PROJECT-FILE:
 2) IMPORT BRUKER-DATA
 3) VISUALIZE FILES AND FOLDERS
 4) SELECTION OF ANIMALS
 5) RENAME FILES
 6) Determine Orientation-Type
 7) REGISTER "t2.nii" TO TEMPLATE SPACE (STANDARD-SPACE)
 8) Examine the Processing Report
PART-2: DTI-preprocessing/prepare data for DTI-MRtrix-pipeline
 9) A special DTI-atlas is needed
10) DTI-preprocessing
10.1) IMPORT B-tables [get b-table(s)]
10.2) Specify DTI/DWI-files [get DTIfile(s)]
10.3) specify the DTI-atlas [getDTItemplate]
10.4) Check file-assignment and order of b-tables and DTI-files
10.5) Run the DTIprep-tasks
11) CHECK registration with 1st DWI-file

  → Tutorial: "tutorial_prepareDTIpipeline.pdf"


Tutorial: no graphic-support/processing without GUIs

Aim

The tutorial covers the following topic:
- How to handle processing without graphics/GUI-support
- working only from the command line

CONTENTS

1) OPTIONAL: How to set the paths of ELASTIX in UNIX/LINUX-system:
2) OPTIONAL: Open interactive session on HPC-cluster and start Matlab
3) BASICS
  ADD ANTx-PATHS
  GO TO STUDY-FOLDER
  UPDATE ANT-TOOLBOX
  CREATE A PROJECT-FILE:
  LOAD A PROJECT-FILE "proj.m"
  CHECK WHETHER THE PROJECT-FILE IS LOADED
4) IMPORT BRUKER-DATA
5) VISUALIZE FILES AND FOLDERS
6) SELECTION OF ANIMALS
7) RENAME FILES
8) REGISTER "t2.nii" TO TEMPLATE (STANDARD SPACE, SS)
9) Extract the first 3d-volume from the 4D-vlume "dti_b100.nii"
10) COREGISTER "dti_b100_1stIMG.nii" to "t2.nii"
11) TRANSFORM ANOTHER IMAGE TO STANDARD-SPACE
12) TRANSFORM ANOTHER IMAGE TO NATIVE-SPACE
13) CHECK REGISTRATION in STANDARD-SPACE - CREATE HTML-FILE
14) CHECK REGISTRATION in NATIVE-SPACE - CREATE HTML-FILE
15) REGIONWISE PARAMETER-EXTRACTION
16) DTI-preprocessing: Import DTI/DWI-files from Bruker rawdata
17) DTI-preprocessing: rename DWI-files
18) DTI-preprocessing: A special DTI-atlas is needed
19) DTI-preprocessing: Perform DTI-preprocessing

  → Tutorial: "tutorial_noGraphic_support.pdf"


Multi-Tube Segmentation

Scenario

- several ex-vivo skullstripped mouse brains within one MR-volume
- mouse brains are differently positioned in the MR bore

Goals

- Isolate mouse brains
- obtain orientation type for each animal
- register brains to Allen mouse brain atlas (ABA)

  → Tutorial: newer version "tutorial_tubeSegmentation_registration_feb2022.pdf"


  → Tutorial: another approach, a bit older "tutorial_tubeSegmentation_manualSegment.pdf"


Registration of CT-data

Aims

 - warp CT-data to Allen space and inversion (atlas to native space)

Goals & Issues

- CT does not have enough image contrast for brain registration/segmentation.
  Solution: use t2w-image of the same animal & skull extraction from CT to create an inner mask of the
  skull which roughly refers to the "brain"-volume. This volume is then registered to the Allen-brain
  mask. The Allen-brain mask is created after registering the t2w-image to the Allen brain template
  and after back-transform of the Allen-brain mask. Thus, registration parameters from t2w-registration
  can be applied to the CT-image or other images.
- mouse is differently positioned (differently oriented) compared to berlin procedure.
  Thus the header of the t2w-image has to be changed.
- t2w-image is different regarding the position/origin of the CT-image
- CT-image is different regarding the position/origin of the t2w-image
- SPECT-image is different regarding the position/origin of the CT-image

  → Tutorial: "tutorial_CTdata_registration.pdf"


Extract Regionwise Parameter

Aims

 This tutorial shows how to obtain a regionwise parameter (regionwise volume) from native space (animal space)

Important

- Iit is assumed that the animal is already registered to standard space.

  → Tutorial: "tutorial_getanatomicalLabel_NativeSpace.pdf"


Extract Parameter using a Mask

Aims

 This tutorial shows how to extract parameter from a readout image using a specific mask.
 The mask can contain one or more ROIs.
 Parameters such a volume, mean, median etc will be extracted for each ROI.
 The output is an Excel-file containing the parameters.
 Here, read-out images and masks are bot in native space and located in the respective
 animal folders.

Steps

  1) Prerequisite
  2) Steps to perform the parameter extraction
  2.1) Readout-file selection
  2.2) Mask-file selection
  2.3) Select a filename-prefix for resulting excel-file
  3) The output: Excel-file
  4) Batch

  → Tutorial: "tutorial_extractParamter_via_Mask.pdf"


Batch & Programmatically Perform A Task

Aims

 This short tutorial shows how to obtain some batch line, modify the batch and rerun on same/other animals

Covered in this tutorial:

- select mouse folders
- renamimg
- distribute files
- image calculation
- coregistration
- slicewise rigid/affine/nonlinear registration
- normalize: transform t2.nii from animal space to standard space
- transform other images to standard space or animal space
- extract region-based parameters from an image

  → Tutorial: "tutorial_batch.pdf"


Other Tutorials

  → convert Dicoms-images to Nifti: "tutorial_convertDICOMs.pdf"


  → prepare data for FSL: "tutorial_prepareforFSL.pdf"


  → mask approach: "infos.pdf"