[WARNING: the script in FreeSurfer 7.4 has a small bug when computing the surface label files at the end of the script. Please replace $FREESURFER_HOME/bin/ with the latest version HERE. Development versions newer than June 15th 2023 do not have this problem.]

This functionality is available since FreeSurfer 7.4.

Author: Karthik Gopinath

E-mail: kgopinath[at]mgh[dot]harvard[dot]edu

Please post your questions on this module to the FreeSurfer mailing list at freesurfer[at] rather than directly contacting the author.

If you use this package in your analysis, please cite:

General description:

This tool performs recon-all-clinical, the first out-of-the-box cortical surface reconstruction and analysis of brain MRI scans of any modality, contrast and resolution without retraining and fine-tuning.

This "Recon-all-like" stream for clinical scans of arbitrary orientation/resolution/contrast is essentially a combination of:

Out of the box cortical surface reconstruction and analysis of heterogenous scans. (a)Sagittal T1 scan with .4×.4×6mm resolution. (b)Axial FLAIR scan with 1.7×1.7×6mm resolution. (c)Axial T2-weighted scan with .9×.9×6mm resolution. The WM surface with cortical parcellation overlaid and pial surfaces are also shown.


OnceFreeSurfer has been sourced, you can simply run recon-all-clinical on your own data with INPUT_SCAN SUBJECT_ID THREADS [SUBJECT_DIR]


- INPUT_SCAN: path to an image that will be processed.

- SUBJECT_ID: specifies the name or ID of the subject you would like to use. A directory with that name will be created for all the subject's FreeSurfer output.

- THREADS (optional): number of CPU threads to use. The default is just 1, so crank it up for faster processing if you have multiple cores!

- SUBJECT_DIR: only necessary if the environment variable SUBJECTS_DIR has not been set when sourcing FreeSurfer or if you want to override it.

This stream runs a bit faster than the original recon-all, since the volumetric segmentation is much faster than the iterative Bayesian method in the standard stream


This stream will create a directory structure that is almost the same as recon-all, but with some minor changes in the SUBJECT_DIR/mri:

Post completion of the cortical surface stream, some of the results from the cortical stream are used to refine the results in the directory SUBJECT_DIR/mri:

Cortical thickness and future work

The current recon-all-clinical stream is accurate for parcellation at nearly any resolution / slice spacing (see paper). However, the quality of cortical thickness estimation does degrade relatively quickly with increasing slice spacing; we plan to improve this in future versions of the tool.

recon-all-clinical (last edited 2023-06-13 10:42:55 by JuanIglesias)