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Samseg (cross-sectional, longitudinal, MS lesions)

This functionality is available in FreeSurfer 7, with gradual improvements appearing in the development version.

Author: Koen Van Leemput

E-mail: koen [at] nmr.mgh.harvard.edu

Rather than directly contacting the author, please post your questions on this module to the FreeSurfer mailing list at freesurfer [at] nmr.mgh.harvard.edu

If you use these tools in your analysis, please cite:

See also: ThalamicNuclei, HippocampalSubfieldsAndNucleiOfAmygdala, BrainstemSubstructures


1. General Description

Sequence Adaptive Multimodal SEGmentation (SAMSEG) is a tool to robustly segment dozens of brain structures from head MRI scans without preprocessing. The characteristic property of SAMSEG is that it accepts multi-contrast MRI data without prior assumptions on the specific type of scanner or pulse sequences used. Dedicated versions to handle longitudinal data, or to segment white matter lesions in multiple sclerosis (MS) patients are also available.

The figure below illustrates a typical SAMSEG segmentation result on a T1w-FLAIR scan of a MS patient:
3D_small.png

2. Basic SAMSEG (cross-sectional processing)

In its most basic form SAMSEG takes one or more co-registered MRI volumes as input, and produces an output segmentation in around 10 min on a good desktop computer (with multi-threading enabled). Preprocessing of the scan(s) with FreeSurfer is neither required nor recommended (e.g., no reformatting to 1mm isotropic resolution, no bias field correction and no skull stripping is needed nor recommended). The command line is:

run_samseg --input <file> [<file> ...] --output <dir> [--threads <threads>] [--pallidum-separate] 

where:

* <file>: is the path to the input volume(s) in NIFTI or MGZ file format. If you have more than one contrast (e.g., both T1w and T2w) you can simply list all the input contrasts you want to use -- the only requirement is that all input volumes are co-registered with each other, and have the same image grid size and voxel dimensions.


3. Usage