applywarp函数简介

applywarp --in=core_mask_struct --out=core_mask_MNI --ref=MNI152_T1_2mm_brain --interp=nn --warp=my_nonlinear_transf

--in: filename of input image (to be warped)   core_mask_struct

--out: filename for output (warped) image      core_mask_MNI

--ref: filename for reference image                 MNI152_T1_2mm_brain

--interp: interpolation method {nn,trilinear,sinc,spline}     nn

--warp: filename for warp/coefficient (volume)     my_nonlinear_transf

Usage:

applywarp -i invol -o outvol -r refvol -w warpvol

applywarp -i invol -o outvol -r refvol -w coefvol

Compulsory arguments (You MUST set one or more of):

-i,--in filename of input image (to be warped)

-r,--ref filename for reference image

-o,--out filename for output (warped) image

Optional arguments (You may optionally specify one or more of):

-w,--warp filename for warp/coefficient (volume)

--abs treat warp field as absolute: x' = w(x)

--rel treat warp field as relative: x' = x + w(x)

-d,--datatype Force output data type [char short int float double].

-s,--super intermediary supersampling of output, default is off

--superlevel level of intermediary supersampling, a for 'automatic' or integer level. Default = 2

--premat filename for pre-transform (affine matrix)

--postmat filename for post-transform (affine matrix)

-m,--mask filename for mask image (in reference space)

--interp interpolation method {nn,trilinear,sinc,spline}

--paddingsize Extrapolates outside original volume by n voxels

-v,--verbose switch on diagnostic messages

-h,--help display this message