If you have used the previous implementation of the generalised image registration and motion-modelling framework called Nifty-Reg-Resp then you will need to adapt the command line parameters according to the table below. SuPReMo has extended functionality over reg-resp.

Parameters:

reg_resp	runSupremo	Pattern	Description
-static	-refState	[fName]	Reference state/static image
-dynamic	-dynamic	[int] [fName]	File containing list of dynamic images and the total number of dynamic images
-surr	-surr	[int] [fName]	File containting the surrogate signal and the number of signals used
-dType	-dType	[int]	Dynamic image data type [0] = full res images, [1] = low res images
-defSpace	-defSpace	[fName]	File name of image that defines the space of the deformed iamges
-mcrType	-mcrType	[int]	Motion compensation [0] none, [1] average weighting, [2] SR, restart, [3] SR update
-maxMCRIt	-maxMCRIt	[int]	Number of iterations used for iterative MCR method
-rcm	-outRCM	[fName]	Path to save the respratory correspondence model (RCM) to
-saveDyn	-outSimDyn	[fName]	Path to save the simulated dynamic images to
-saveMCR	-outMCR	[fName]	Path to save the motion-compensated reconstruction images to
-saveInterMCRs	-outInterMCR	[fName]	Path to save the motion-compensated reconstruction images to
	-outInterGrad	[fName]	Path to save the intermediate gradient to (experimental)
-sx	-sx	[float]	Final grid spacing along x axis (in mm if positive, in voxels if negative)
-sy	-sy	[float]	Final grid spacing along y axis (in mm if positive, in voxels if negative)
-sz	-sz	[float]	Final grid spacing along z axis (in mm if positive, in voxels if negative)
-be	-be	[float]	Bending energy constraint weight
	-le	[float]	Linear energy constraint weight (experimental)
-maxSwitchIt	-maxSwitchIt	[int]	Maximum number of switches between fitting and reconstruction
-ln	-ln	[int]	Number of pypramid levels generated
-lp	-lp	[int]	Number of pypramid levels used
-maxFitIt	-maxFitIt	[int]	Number of iterations to fit the motion model