MIRACL in a nutshell
MIRACL (Multi-modal Image Registration And Connectivity anaLysis) is a general-purpose, open-source pipeline for automated:
Registration of cleared and imaging data (ex. LSFM and MRI) to atlases (ex. Allen Reference Atlas)
3D Segmentation and feature extraction of cleared data
Tract-specific or network-level connectivity analysis
Statistical analysis of cleared and imaging data
Comparison of dMRI/tractography, virus tracing, and connectivity atlases
Atlas generation and Label manipulation
Program structure
MIRACL is structured into Modules and Workflows.
Modules
The pipeline is comprised of different Modules
depending on their
respective functionality. Functions for each module are grouped together:
Module |
Functionality |
---|---|
connect |
Connectivity |
Conversion (Input/Output) |
|
Registration |
|
seg |
Segmentation |
lbls |
Labels |
Utilities |
|
sta |
Structure Tensor Analysis |
stats |
Statistics |
An example of using a module would be to run the clar_allen
function which
performs a CLARITY whole-brain registration to Allen Atlas on a nifti
image (down-sampled by a factor of five):
$ miracl reg clar_allen -i niftis/SHIELD_05x_down_autoflor_chan.nii.gz -o ARI -m combined -b 1
The above command uses the -i
flag to select the nifti file, -o
to
specify the orientation of the image, -m
to register to both hemispheres
and -b
to include the olfactory bulb.
Workflows
The workflow (flow) module combines multiple functions from the above modules for ease of use to perform a desired task.
For example, a standard reg/seg analysis could look like this:
First perform registration of whole-brain CLARITY data to ARA:
$ miracl flow reg_clar -h
Then perform segmentation and feature extraction of full resolution CLARITY data:
$ miracl flow seg -h
Or structure tensor analysis:
$ miracl flow sta -h