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Structural processing
Chris Klink edited this page May 26, 2020
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Here we provide an overview of the main steps involved, and the tools available in PRIME-RE or in existing neuroimaging software packages, for the processing of NHP structural images with the goal of achieving an extracted brain mask and the segmentation masks (WM,GM and CSF). We also provide a list of existing pipelines for macaque anatomical processing for reference.
Processing Step | Available Tools |
---|---|
1. Data Preparation | |
Reorientation | FSL: fslreorient2std , fslswapdim + fslreorient Freesurfer: mri_convert -sphinx , mri_convert --in_orientation Jip analysis toolkit Web-based Reorient Tool |
Deoblique | AFNI: 3drefit -deoblique (for changing header information) |
Cropping | FSL: fslroi , FSLeyesAFNI: @clip_volume FreeSurfer: mri_convert --slice-crop
|
Denoising | Adaptive non-local means filter denoising in ANTs (ImageDenoise ), SPM or Matlab package
|
Averaging multiple images | Linear Registration tools: FSL-FLIRT, AFNI-3dVolReg, 3dAllineate , SPM Register, etc.Image averaging: fslmaths , SPM Imcalc, etc. |
2. Bias-Correction | |
T1xT2 bias field correction (HCP Method) | Can be implemented using standard image calculation software such as fslmaths based on procedures described in Rilling et al. (2011)A module for this bias-correction is also available in Macapype ( correct_bias.py ). |
N3, N4BiasFieldCorrection
|
Available in ANTs, MINC, Freesurfer packages. One could also consider N3biascorrection which works better in some cases. |
FSL-Fast | FSL |
CMTK-mrbias | Find it here |
3. Brain Extraction | |
Template-based | AntsBrainExtraction (ANTs), Atlasbrex |
Non Template-based | FSL-BET (can also be used with a template), bet_macaque.sh |
Deep Learning Model | U-NET |
Manual corrections | ITK-SNAP, Slicer, BrainBox |
4. Brain Segmentation | |
Template-based | AntsAtroposN4 script, Atropos (ANTs), SPM Segment |
Non Template-based | FSL-Fast (can be used with templates) |
Manual segmentations/corrections | ITK-SNAP, BrainBox |
5. Templates and Atlases | See PRIME-RE |
6. Ready-to-use Pipelines | |
Civet-Macaque | Find it here |
NHP-Freesurfer | Find it here |
PREEMACS | Find it here |
Macapype | Find it here |
Precon_all | Find it here |
HCP-style NHP Pipeline | Find it here |
A. Why the interest in NHP neuroimaging?
B. What makes NHP MRI challenging?
C. Typical data analysis challenges
D. Structural data processing steps and PRIME-RE tools
E. Functional data processing steps and PRIME-RE tools
F. Diffusion data processing steps and PRIME-RE tools
G. Cross-species comparisons and PRIME-RE tools