What is XFSL

XFSL is first a set of many useful automation scripts to facilitate Neuroimaging data analysis process. Originally, it is a tweak of FSL to release the power of cluster computing. With numerous revisions, now it can also simplify the whole data analysis procedures using FSL. It may also give newbie, especially those who are not familiar with Linux/Unix environment, a easier way to get started.

DCM4CHEE: a FREE but powerful crossplatform PACS solution

To retrieve your DICOM data from USC DNI, you may burn CD/DVD disks or use PACS server (Not like some other sites, like UCLA or BNU, that you can download your data from their FTP server). We burned a lot of CD/DVD disks previously. It worked very well until one day they pushed us to setup our own PACS to receive data because we also burned a lot of DVD writers in the same time:(


Simple scripts for interaction with your PACS

You may download these scripts here: http://www.nitrc.org/frs/download.php/7388/xfsl_PACS_Ver0.1.tar.gz

Using PACS(Picture Archiving and Communication System) is a very good way to manage your DICOM raw data. At USC, PACS is recommended way to fetch DICOM data from our MRI machine. I recommend DCM4CHEE to be your PACS server. It is super easy to setup, doesn't need too much administration, and it is FREE!
Here I have five scripts to further ease your usage of PACS.


Useful DICOM tags

When I trying to upgrade my PACS related scripts from dcm4che toolkit Ver 2.0.28 to Ver 3.3.5. I noticed huge changes.
In the past, I could use dcmqr to query & download my PACS to find my data, it was very straight forward and convenient.
But, now I have to use findscu and getscu to do the same job and it is so complicated!


Be more proficient in FSL's VBM analysis

The XFSL VBM scripts can be downloaded at here: http://www.nitrc.org/frs/download.php/7383/xfsl_vbm_Ver0.11.tar.gz

Organize your data

Data structure

Before using XFSL, you need to organize(or maybe re-organize) your data first.

In XFSL philosophy, each project has a unique folder(where the $PROJECTROOT redirects to in the code), under which are folders for each individual subjects, folder for group analysis, and folders for other files, such as behavioral data etc. Detailed in the attached picture.

Under each subject's folder, there should be two folders: data and analysis. Please save all NIFTI raw data into the data folder, such as structural MRI data (MNPRAGE/3D, DTI) and functional data.


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