recon-all-clinical

This functionality is now available in the developer version of FreeSurfer.

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]nmr.mgh.harvard.edu rather than directly contacting the author.

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

• Cortical analysis of heterogeneous clinical brain MRI scans for large-scale neuroimaging studies. K Gopiath, DN Greeve, S Das, S Arnold, C Magdamo, JE Iglesias

• Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast. JE Iglesias, B Billot, Y Balbastre, A Tabari, J Conklin, RG Gonzalez, DC Alexander, P Golland, BL Edlow, B Fischl, for the ADNI. Neuroimage, 118206 (2021).

• SynthSR: a public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry. JE Iglesias, B Billot, Y Balbastre, C Magdamo, S Arnold, S Das, B Edlow, D Alexander, P Golland, B Fischl. Science Advances, 9(5), eadd3607 (2023).

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:

• SynthSeg: to obtain an aseg.auto_noCCseg.mgz and to compute a Talairach transform

• SynthSR: to have a higher resolution 1mm MPRAGE for visualization

• SynthSurfaces: to fit surfaces by predicting the distance maps and reconstructing topologically accurate cortical surfaces

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.

Usage:

OnceFreeSurfer has been sourced, you can simply run recon-all-clinical on your own data with

recon-all-clinical.sh INPUT_SCAN SUBJECT_ID THREADS [SUBJECT_DIR]

where:

- 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