We planned for this from the start. Most of our tools (including Auto_EACSF) can be run as a command line command. Thus, with a bit of scripting experience, it should be straightforward to batch process them.

You can run Auto_EACSF from the terminal using the "--help" tag and you will see a brief usage information:

USAGE:

Auto_EACSF [--returnparameterfile ]
[--processinformationaddress ] [--xml] [--echo]
[-t ] [--output_dir ] [--cerebmask
] [--subjectVentricleMask ]
[--segmentation ] [--brainmask ]
[--t2 ] [--t1 ] [--noGUI] [-p
] [--] [--version] [-h]
Where:
--returnparameterfile
Filename in which to write simple return parameters (int, float,
int-vector, etc.) as opposed to bulk return parameters (image,
geometry, transform, measurement, table).
--processinformationaddress
Address of a structure to store process information (progress, abort,
etc.). (value: 0)
--xml
Produce xml description of command line arguments (value: 0)
--echo
Echo the command line arguments (value: 0)
-t , --
--output_dir
Output directory
--cerebmask
Input cerebellum mask
--subjectVentricleMask
Input subject ventricle mask
--segmentation
Input brain segmentation
--brainmask
Input brainmask
--t2
Input T2 image
--t1
Input T1 image
--noGUI
Use AutoEACSF without the GUI (value: 0)
-p , --param
Input parameters in a json file
--, --ignore_rest
Ignores the rest of the labeled arguments following this flag.
--version
Displays version information and exits.
-h, --help
Displays usage information and exits.
Description: Automatically extract external CSF from T1 or T1 and T2
images.

What you need:
- save the json for the parameters and executable information
- have a way to edit the json file for all datasets (e.g. via json reading/writing in python using the json python library)
- run Auto_EACSF --noGUI --param yourParam.xml for each case with its edited json file

Martin
Originally posted by cccoleman: