Name

mri_robust_template - construct an unbiased robust template for longitudinal volumes

Synopsis

mri_robust_template --mov <tp1.mgz> <tp2.mgz> ... --template <template.mgz> --satit [options]

Please Cite This

Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis
M. Reuter, N.J. Schmansky, H.D. Rosas, B. Fischl.
NeuroImage 61(4):1402-1418, 2012.

http://dx.doi.org/10.1016/j.neuroimage.2012.02.084 http://reuter.mit.edu/papers/reuter-long12.pdf

Description

This program constructs an unbiased robust template for longitudinal volumes (within modality, 6-7 DOF). It uses an iterative method to construct a mean/median volume and the robust rigid registration of all input images to the current mean/median.

It is used for the Motion Correction step in recon-all and for creating a within-subject template in the longitudinal stream (-base) in FreeSurfer.

Important Note: For best performance the input images should all have the same intensity level! Good images are, for example, the T1.mgz and norm.mgz from the FreeSurfer stream.

Arguments

Required Flagged Arguments

-- mov <tp1.mgz> <tp2.mgz> ...	input movable volumes to be aligned to common mean/median template
-- template <template.mgz>	output template volume (final mean/median image)

One of the following is required for sensitivity:

-- sat <real>	set outlier sensitivity manually (e.g. '--sat 4.685' ). Higher values mean less sensitivity.
-- satit	auto-detect good sensitivity (recommended for head or full brain scans)

Optional Flagged Arguments

-- lta <tp1.lta> <tp2.lta> ...	output xforms to template (for each input)
-- mapmov <aligned1.mgz> ...	output images: map and resample each input to template
-- weights <weights1.mgz> ...	output weights (outliers) in target space
-- average <#>	construct template from: 0 Mean, 1 Median (default)
-- inittp <#>	use TP# for spacial init (default random), 0: no init
-- fixtp	map everthing to init TP# (init TP is not resampled)
-- iscale	allow also intensity scaling (default off)
-- iscalein <is1.txt> <is2.txt> ...	use initial intensity scales
-- iscaleout <is1.txt> <is2.txt> ...	output final intensity scales (will activate --iscale)
-- ixforms <t1.lta> <t2.lta> ...	use initial transforms (lta) on source ('id'=identity)
-- vox2vox	output VOX2VOX lta file (default is RAS2RAS)
-- affine	compute 12 DOF registration (default is 6 DOF)
-- leastsquares	use least squares instead of robust M-estimator (for testing only)
-- noit	do not iterate, just create first template
-- maxit <#>	iterate max # times (if #tp>2 default 6, else 5 for 2tp reg.)
-- highit <#>	iterate max # times on highest resolution (default 5)
-- epsit <real>	stop iterations when all tp transform updates fall below <real> (if #tp>2 default 0.03, else 0.01 for 2tp reg.)
-- subsample <#>	subsample if dim > # on all axes (default no subs.)
-- floattype	convert images to float internally (default: keep input type)
-- finalnearest	use nearest neighbor in final interpolation when creating average. This is useful, e.g., when -noit and --ixforms are specified and brainmasks are mapped.
-- doubleprec	double precision (instead of float) internally (large memory usage!!!)
-- debug	show debug output (default no debug output)

Examples

Example 1

mri_robust_template --mov tp1.mgz tp2.mgz tp3.mgz --template mean.mgz --lta tp1.lta tp2.lta tp3.lta --mapmov tp1tomean.mgz tp2tomean.mgz tp3tomean.mgz --average 0 --iscale --satit

Constructs a mean (--average 0) template from tp1,tp2 and tp3 and outputs the mean.mgz, the corresponding transforms (tp?.lta) and aligned images (tp?tomean.mgz). Intensity scaling is allowed, the saturation/sensitivity for outliers is automatically computed (only possible for full head or full brain images).

View results:

tkmedit -f mean.mgz -aux tp1tomean.mgz

Example 2

mri_robust_template --mov 001.mgz 002.mgz --average 1 --template rawavg.mgz --satit --inittp 1 --fixtp --noit --iscale --subsample 200

Is used in the recon-all stream for motion correction of several (here two: 001.mgz and 002.mgz) inputs. In this case all follow-ups are registered to the first input (as specified with --inittp 1 --fixtp --noit) and the rawavg.mgz is output as the median image (--average 1).

Bugs

None (of course)

Links

FreeSurfer, FsFast

References

Please cite this:

Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis
M. Reuter, N.J. Schmansky, H.D. Rosas, B. Fischl.
NeuroImage 61(4):1402-1418, 2012.