Difference between revisions of "Full brain parcellation using Geodesic Information Flow"
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This pipeline uses Geodesic Information Flow (GIF) in order to propagate an atlas parcellation towards a target subject geometry. It only takes an input T1 image as input and a reference database xml file in a specific format. Simplest usage is the following: | This pipeline uses Geodesic Information Flow (GIF) in order to propagate an atlas parcellation towards a target subject geometry. It only takes an input T1 image as input and a reference database xml file in a specific format. Simplest usage is the following: | ||
| + | <pre> | ||
| + | perform_gif_propagation_expanded.py -d <database.xml> -i <T1.nii.gz> -o <output_dir> | ||
| + | </pre> | ||
| + | |||
| + | The following is a description of the other parameters available from the pipeline: | ||
<pre> | <pre> | ||
usage: perform_gif_propagation_expanded.py [-h] -i input_file [input_file ...] | usage: perform_gif_propagation_expanded.py [-h] -i input_file [input_file ...] | ||
| Line 23: | Line 28: | ||
-g, --graph Print a graph describing the node connections | -g, --graph Print a graph describing the node connections | ||
</pre> | </pre> | ||
| + | |||
| + | The database is the key argument of the pipeline. It will determine what atlas is to be propagated and the subjects present in the database will influence the propagation. | ||
| + | |||
| + | When in the cmic cluster, the database is located here: <code>~ntoussai/scratch/data/template-database/db.xml</code>, so you can use the following line: | ||
| + | <pre> | ||
| + | perform_gif_propagation_expanded.py -d <~ntoussai/scratch/data/template-database/db.xml> -i <T1.nii.gz> -o <output_dir> | ||
| + | </pre> | ||
| + | |||
| + | When in the DRC network, the database is located here: <code>~toussaint/scratch/data/template-database/db.xml</code>, so you can use the following line: | ||
| + | <pre> | ||
| + | perform_gif_propagation_expanded.py -d <~toussaint/scratch/data/template-database/db.xml> -i <T1.nii.gz> -o <output_dir> | ||
| + | </pre> | ||
| + | |||
External links: | External links: | ||
* [conference paper about the algorithm]<http://doi.org/10.1007/978-3-642-33418-4_33> | * [conference paper about the algorithm]<http://doi.org/10.1007/978-3-642-33418-4_33> | ||
Revision as of 11:49, 1 September 2015
This pipeline uses Geodesic Information Flow (GIF) in order to propagate an atlas parcellation towards a target subject geometry. It only takes an input T1 image as input and a reference database xml file in a specific format. Simplest usage is the following:
perform_gif_propagation_expanded.py -d <database.xml> -i <T1.nii.gz> -o <output_dir>
The following is a description of the other parameters available from the pipeline:
usage: perform_gif_propagation_expanded.py [-h] -i input_file [input_file ...]
-d database -o output [-n n_procs]
[-u username] [-g]
GIF Propagation
optional arguments:
-h, --help show this help message and exit
-i input_file [input_file ...], --input_file input_file [input_file ...]
Input image file to propagate labels in
-d database, --database database
gif-based database xml file describing the inputs
-o output, --output output
output directory to which the gif outputs are stored
-n n_procs, --n_procs n_procs
maximum number of CPUs to be used when using the
MultiProc plugin
-u username, --username username
Username to use to submit jobs on the cluster
-g, --graph Print a graph describing the node connections
The database is the key argument of the pipeline. It will determine what atlas is to be propagated and the subjects present in the database will influence the propagation.
When in the cmic cluster, the database is located here: ~ntoussai/scratch/data/template-database/db.xml, so you can use the following line:
perform_gif_propagation_expanded.py -d <~ntoussai/scratch/data/template-database/db.xml> -i <T1.nii.gz> -o <output_dir>
When in the DRC network, the database is located here: ~toussaint/scratch/data/template-database/db.xml, so you can use the following line:
perform_gif_propagation_expanded.py -d <~toussaint/scratch/data/template-database/db.xml> -i <T1.nii.gz> -o <output_dir>
External links:
- [conference paper about the algorithm]<http://doi.org/10.1007/978-3-642-33418-4_33>
