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t1-spm-full-prep – SPM-based pre-processing of T1-weighted MRI images

This pipeline first performs tissue segmentation, bias correction and spatial normalization to MNI space of a T1-weighted MRI image. It wraps the Segmentation procedure from SPM that performs all these processes simultaneously, a procedure also known as “Unified segmentation” [Ashburner and Friston, 2005].

The pipeline then computes a group template by applying the DARTEL diffeomorphic method to the T1-weighted MRI image of each subject considered. With this procedure, each subject T1-weighted MRI image can be registered to the space of the calculated DARTEL template and then to MNI space. This is achieved by wrapping the Run Dartel and Normalise to MNI Space procedures from SPM [Ashburner, 2007].

Finally, a parcellation into a set of anatomical regions according to different atlases is obtained and average values in each region are computed.


  • If you only installed the core of Clinica, this pipeline needs the installation of SPM. You can find how to install this software on the installation page.

Running the pipeline

The pipeline can be run with the following command line:

clinica run t1-spm-full-prep bids_directory caps_directory group_id

  • bids_directory is the input folder containing the dataset in a BIDS hierarchy.
  • caps_directory is the output folder containing the results in a CAPS hierarchy.
  • group_id is the user defined identifier for the provided group of subjects. For more information check Interacting with clinica.


Results are stored in the following folder of the CAPS hierarchy: subjects/sub-<participant_label>/ses-<session_label>/t1/spm.

The full list of output files from FSL pipeline can be found in the The ClinicA Processed Structure (CAPS) Specification.

Describing this pipeline in your paper

Example of paragraph:

Theses results have been obtained using the t1-spm-full-prep pipeline of Clinica. More precisely, this pipeline is a wrapper of the Segmentation [Ashburner and Friston, 2005], Run Dartel [Ashburner, 2007] and Normalise to MNI Space routines implemented in SPM.