int main( int argc , char * argv[] )
{
float mrad=0.0f , fwhm=0.0f ;
int nrep=1 ;
char *prefix = "Polyfit" ;
char *resid = NULL ;
char *cfnam = NULL ;
int iarg , verb=0 , do_automask=0 , nord=3 , meth=2 , do_mclip=0 ;
THD_3dim_dataset *inset ;
MRI_IMAGE *imout , *imin ;
byte *mask=NULL ; int nvmask=0 , nmask=0 , do_mone=0 , do_byslice=0 ;
MRI_IMARR *exar=NULL ;
floatvec *fvit=NULL ; /* 26 Feb 2019 */
if( argc < 2 || strcasecmp(argv[1],"-help") == 0 ){
printf("\n"
"Usage: 3dPolyfit [options] dataset ~1~\n"
"\n"
"* Fits a polynomial in space to the input dataset and outputs that fitted dataset.\n"
"\n"
"* You can also add your own basis datasets to the fitting mix, using the\n"
" '-base' option.\n"
"\n"
"* You can get the fit coefficients using the '-1Dcoef' option.\n"
"\n"
"--------\n"
"Options: ~1~\n"
"--------\n"
"\n"
" -nord n = Maximum polynomial order (0..9) [default order=3]\n"
" [n=0 is the constant 1]\n"
" [n=-1 means only use volumes from '-base']\n"
"\n"
" -blur f = Gaussian blur input dataset (inside mask) with FWHM='f' (mm)\n"
"\n"
" -mrad r = Radius (voxels) of preliminary median filter of input\n"
" [default is no blurring of either type; you can]\n"
" [do both types (Gaussian and median), but why??]\n"
" [N.B.: median blur is slower than Gaussian]\n"
"\n"
" -prefix pp = Use 'pp' for prefix of output dataset (the fit).\n"
" [default prefix is 'Polyfit'; use NULL to skip this output]\n"
"\n"
" -resid rr = Use 'rr' for the prefix of the residual dataset.\n"
" [default is not to output residuals]\n"
"\n"
" -1Dcoef cc = Save coefficients of fit into text file cc.1D.\n"
" [default is not to save these coefficients]\n"
"\n"
" -automask = Create a mask (a la 3dAutomask)\n"
" -mask mset = Create a mask from nonzero voxels in 'mset'.\n"
" [default is not to use a mask, which is probably a bad idea]\n"
"\n"
" -mone = Scale the mean value of the fit (inside the mask) to 1.\n"
" [probably this option is not useful for anything]\n"
"\n"
" -mclip = Clip fit values outside the rectilinear box containing the\n"
" mask to the edge of that box, to avoid weird artifacts.\n"
"\n"
" -meth mm = Set 'mm' to 2 for least squares fit;\n"
" set it to 1 for L1 fit [default method=2]\n"
" [Note that L1 fitting is slower than L2 fitting!]\n"
"\n"
" -base bb = In addition to the polynomial fit, also use\n"
" the volumes in dataset 'bb' as extra basis functions.\n"
" [If you use a base dataset, then you can set nord]\n"
" [to -1, to skip using any spatial polynomial fit.]\n"
"\n"
" -verb = Print fun and useful progress reports :-)\n"
"\n"
"------\n"
"Notes: ~1~\n"
"------\n"
"* Output dataset is always stored in float format.\n"
"\n"
"* If the input dataset has more than 1 sub-brick, only sub-brick #0\n"
" is processed. To fit more than one volume, you'll have to use a script\n"
" to loop over the input sub-bricks, and then glue (3dTcat) the results\n"
" together to get a final result. A simple example:\n"
" #!/bin/tcsh\n"
" set base = model.nii\n"
" set dset = errts.nii\n"
" set nval = `3dnvals $dset`\n"
" @ vtop = $nval - 1\n"
" foreach vv ( `count 0 $vtop` )\n"
" 3dPolyfit -base \"$base\" -nord 0 -mask \"$base\" -1Dcoef QQ.$vv -prefix QQ.$vv.nii $dset\"[$vv]\"\n"
" end\n"
" 3dTcat -prefix QQall.nii QQ.0*.nii\n"
" 1dcat QQ.0*.1D > QQall.1D\n"
" \rm QQ.0*\n"
" exit 0\n"
"\n"
"* If the '-base' dataset has multiple sub-bricks, all of them are used.\n"
"\n"
"* You can use the '-base' option more than once, if desired or needed.\n"
"\n"
"* The original motivation for this program was to fit a spatial model\n"
" to a field map MRI, but that didn't turn out to be useful. Nevertheless,\n"
" I make this program available to someone who might find it beguiling.\n"
"\n"
"* If you really want, I could allow you to put sign constraints on the\n"
" fit coefficients (e.g., say that the coefficient for a given base volume\n"
" should be non-negative). But you'll have to beg for this.\n"
"\n"
"-- Emitted by RWCox\n"
) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
/*-- startup paperwork --*/
mainENTRY("3dPolyfit main"); machdep(); AFNI_logger("3dPolyfit",argc,argv);
PRINT_VERSION("3dPolyfit") ;
/*-- scan command line --*/
iarg = 1 ;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcasecmp(argv[iarg],"-base") == 0 ){
THD_3dim_dataset *bset ; int kk ; MRI_IMAGE *bim ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '-base'") ;
bset = THD_open_dataset(argv[iarg]) ;
CHECK_OPEN_ERROR(bset,argv[iarg]) ;
DSET_load(bset) ; CHECK_LOAD_ERROR(bset) ;
if( exar == NULL ) INIT_IMARR(exar) ;
for( kk=0 ; kk < DSET_NVALS(bset) ; kk++ ){
bim = THD_extract_float_brick(kk,bset) ;
if( bim != NULL ) ADDTO_IMARR(exar,bim) ;
DSET_unload_one(bset,kk) ;
}
DSET_delete(bset) ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-verb") == 0 ){
verb++ ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-hermite") == 0 ){ /* 25 Mar 2013 [New Year's Day] */
mri_polyfit_set_basis("hermite") ; /* HIDDEN */
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-byslice") == 0 ){ /* 25 Mar 2013 [New Year's Day] */
do_byslice++ ; iarg++ ; continue ; /* HIDDEN */
}
if( strcasecmp(argv[iarg],"-mask") == 0 ){
THD_3dim_dataset *mset ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '-mask'") ;
if( mask != NULL || do_automask ) ERROR_exit("Can't have two mask inputs") ;
mset = THD_open_dataset(argv[iarg]) ;
CHECK_OPEN_ERROR(mset,argv[iarg]) ;
DSET_load(mset) ; CHECK_LOAD_ERROR(mset) ;
nvmask = DSET_NVOX(mset) ;
mask = THD_makemask( mset , 0 , 0.5f, 0.0f ) ; DSET_delete(mset) ;
if( mask == NULL ) ERROR_exit("Can't make mask from dataset '%s'",argv[iarg]) ;
nmask = THD_countmask( nvmask , mask ) ;
if( nmask < 99 ) ERROR_exit("Too few voxels in mask (%d)",nmask) ;
if( verb ) INFO_message("Number of voxels in mask = %d",nmask) ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-nord") == 0 ){
nord = (int)strtol( argv[++iarg], NULL , 10 ) ;
if( nord < -1 || nord > 9 )
ERROR_exit("Illegal value after -nord :(") ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-meth") == 0 ){
meth = (int)strtol( argv[++iarg], NULL , 10 ) ;
if( meth < 1 || meth > 2 )
ERROR_exit("Illegal value after -meth :(") ;
iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-automask",5) == 0 ){
if( mask != NULL ) ERROR_exit("Can't use -mask and -automask together!") ;
do_automask++ ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-mclip",5) == 0 ){
do_mclip++ ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-mone",5) == 0 ){
do_mone++ ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-mrad") == 0 ){
mrad = strtod( argv[++iarg] , NULL ) ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-blur") == 0 ){
fwhm = strtod( argv[++iarg] , NULL ) ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-prefix") == 0 ){
prefix = argv[++iarg] ;
if( !THD_filename_ok(prefix) )
ERROR_exit("Illegal value after -prefix :(");
if( strcasecmp(prefix,"NULL") == 0 ) prefix = NULL ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-resid") == 0 ){
resid = argv[++iarg] ;
if( !THD_filename_ok(resid) )
ERROR_exit("Illegal value after -resid :(");
if( strcasecmp(resid,"NULL") == 0 ) resid = NULL ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-1Dcoef") == 0 ){ /* 26 Feb 2019 */
cfnam = argv[++iarg] ;
if( !THD_filename_ok(cfnam) )
ERROR_exit("Illegal value after -1Dcoef :(");
if( strcasecmp(cfnam,"NULL") == 0 ) cfnam = NULL ;
iarg++ ; continue ;
}
ERROR_exit("Unknown option: %s\n",argv[iarg]);
}
/*--- check for blatant errors ---*/
if( iarg >= argc )
ERROR_exit("No input dataset name on command line?");
if( prefix == NULL && resid == NULL && cfnam == NULL )
ERROR_exit("-prefix and -resid and -1Dcoef are all NULL?!") ;
if( do_byslice && cfnam != NULL ){
WARNING_message("-byslice does not work with -1Dcoef option :(") ;
cfnam = NULL ;
}
if( nord < 0 && exar == NULL )
ERROR_exit("no polynomial fit AND no -base option ==> nothing to compute :(") ;
/*-- read input --*/
if( verb ) INFO_message("Load input dataset") ;
inset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
DSET_load(inset) ; CHECK_LOAD_ERROR(inset) ;
if( DSET_NVALS(inset) > 1 )
WARNING_message( "Only processing sub-brick #0 (out of %d)" , DSET_NVALS(inset) );
/* check input mask or create automask */
if( mask != NULL ){
if( nvmask != DSET_NVOX(inset) )
ERROR_exit("-mask and input datasets don't match in voxel counts :-(") ;
} else if( do_automask ){
THD_automask_verbose( (verb > 1) ) ;
THD_automask_extclip( 1 ) ;
mask = THD_automask( inset ) ; nvmask = DSET_NVOX(inset) ;
nmask = THD_countmask( nvmask , mask ) ;
if( nmask < 99 ) ERROR_exit("Too few voxels in automask (%d)",nmask) ;
if( verb ) ININFO_message("Number of voxels in automask = %d",nmask) ;
} else {
WARNING_message("3dPolyfit is running without a mask") ;
}
#undef GOOD
#define GOOD(i) (mask == NULL || mask[i])
/* check -base input datasets */
if( exar != NULL ){
int ii,kk , nvbad=0 , nvox=DSET_NVOX(inset),nm ; float *ex , exb ;
for( kk=0 ; kk < IMARR_COUNT(exar) ; kk++ ){
if( nvox != IMARR_SUBIM(exar,kk)->nvox ){
if( IMARR_SUBIM(exar,kk)->nvox != nvbad ){
ERROR_message("-base volume (%d voxels) doesn't match input dataset grid size (%d voxels)",
IMARR_SUBIM(exar,kk)->nvox , nvox ) ;
nvbad = IMARR_SUBIM(exar,kk)->nvox ;
}
}
}
if( nvbad != 0 ) ERROR_exit("Cannot continue :-(") ;
/* subtract mean from each base input, if is a constant polynomial in the fit */
if( nord >= 0 ){
if( verb ) INFO_message("subtracting spatial mean from '-base'") ;
for( kk=0 ; kk < IMARR_COUNT(exar) ; kk++ ){
exb = 0.0f ; ex = MRI_FLOAT_PTR(IMARR_SUBIM(exar,kk)) ;
for( nm=ii=0 ; ii < nvox ; ii++ ){ if( GOOD(ii) ){ exb += ex[ii]; nm++; } }
exb /= nm ;
for( ii=0 ; ii < nvox ; ii++ ) ex[ii] -= exb ;
}
}
}
/* if blurring, edit mask a little */
if( mask != NULL && (fwhm > 0.0f || mrad > 0.0f) ){
int ii ;
ii = THD_mask_remove_isolas( DSET_NX(inset),DSET_NY(inset),DSET_NZ(inset),mask ) ;
if( ii > 0 ){
nmask = THD_countmask( nvmask , mask ) ;
if( verb )
ININFO_message("Removed %d isola%s from mask, leaving %d voxels" ,
ii,(ii==1)?"\0":"s" , nmask ) ;
if( nmask < 99 )
ERROR_exit("Too few voxels left in mask after isola removal :-(") ;
}
}
/* convert input to float, which is simpler to deal with */
imin = THD_extract_float_brick(0,inset) ;
if( imin == NULL ) ERROR_exit("Can't extract input dataset brick?! :-(") ;
DSET_unload(inset) ;
if( verb ) INFO_message("Start fitting process") ;
/* do the Gaussian blurring */
if( fwhm > 0.0f ){
if( verb ) ININFO_message("Gaussian blur: FWHM=%g mm",fwhm) ;
imin->dx = fabsf(DSET_DX(inset)) ;
imin->dy = fabsf(DSET_DY(inset)) ;
imin->dz = fabsf(DSET_DZ(inset)) ;
mri_blur3D_addfwhm( imin , mask , fwhm ) ;
}
/* do the fitting */
mri_polyfit_verb(verb) ;
if( do_byslice )
imout = mri_polyfit_byslice( imin , nord , exar , mask , mrad , meth ) ;
else
imout = mri_polyfit ( imin , nord , exar , mask , mrad , meth ) ;
/* WTF? */
if( imout == NULL )
ERROR_exit("Can't compute polynomial fit :-( !?") ;
if( resid == NULL ) mri_free(imin) ;
if( ! do_byslice )
fvit = mri_polyfit_get_fitvec() ; /* get coefficients of fit [26 Feb 2019] */
/* scale the fit dataset? */
if( do_mone ){
float sum=0.0f ; int nsum=0 , ii,nvox ; float *par=MRI_FLOAT_PTR(imout) ;
nvox = imout->nvox ;
for( ii=0 ; ii < nvox ; ii++ ){
if( mask != NULL && mask[ii] == 0 ) continue ;
sum += par[ii] ; nsum++ ;
}
if( nsum > 0 && sum != 0.0f ){
sum = nsum / sum ;
if( verb ) ININFO_message("-mone: scaling fit by %g",sum) ;
for( ii=0 ; ii < nvox ; ii++ ) par[ii] *= sum ;
}
}
/* if there's a mask, clip values outside of its box */
#undef PF
#define PF(i,j,k) par[(i)+(j)*nx+(k)*nxy]
if( mask != NULL && do_mclip ){
int xm,xp,ym,yp,zm,zp , ii,jj,kk , nx,ny,nz,nxy ; float *par ;
MRI_IMAGE *bim = mri_empty_conforming( imout , MRI_byte ) ;
mri_fix_data_pointer(mask,bim) ;
if( verb ) ININFO_message("-mclip: polynomial fit to autobox of mask") ;
MRI_autobbox( bim , &xm,&xp , &ym,&yp , &zm,&zp ) ;
mri_clear_data_pointer(bim) ; mri_free(bim) ;
nx = imout->nx ; ny = imout->ny ; nz = imout->nz ; nxy = nx*ny ;
par = MRI_FLOAT_PTR(imout) ;
for( ii=0 ; ii < xm ; ii++ )
for( kk=0 ; kk < nz ; kk++ )
for( jj=0 ; jj < ny ; jj++ ) PF(ii,jj,kk) = PF(xm,jj,kk) ;
for( ii=xp+1 ; ii < nx ; ii++ )
for( kk=0 ; kk < nz ; kk++ )
for( jj=0 ; jj < ny ; jj++ ) PF(ii,jj,kk) = PF(xp,jj,kk) ;
for( jj=0 ; jj < ym ; jj++ )
for( kk=0 ; kk < nz ; kk++ )
for( ii=0 ; ii < nx ; ii++ ) PF(ii,jj,kk) = PF(ii,ym,kk) ;
for( jj=yp+1 ; jj < ny ; jj++ )
for( kk=0 ; kk < nz ; kk++ )
for( ii=0 ; ii < nx ; ii++ ) PF(ii,jj,kk) = PF(ii,yp,kk) ;
for( kk=0 ; kk < zm ; kk++ )
for( jj=0 ; jj < ny ; jj++ )
for( ii=0 ; ii < nx ; ii++ ) PF(ii,jj,kk) = PF(ii,jj,zm) ;
for( kk=zp+1 ; kk < nz ; kk++ )
for( jj=0 ; jj < ny ; jj++ )
for( ii=0 ; ii < nx ; ii++ ) PF(ii,jj,kk) = PF(ii,jj,zp) ;
}
if( mask != NULL ) free(mask) ;
/* write outputs */
if( prefix != NULL ){
THD_3dim_dataset *outset = EDIT_empty_copy( inset ) ;
EDIT_dset_items( outset ,
ADN_prefix , prefix ,
ADN_nvals , 1 ,
ADN_ntt , 0 ,
ADN_none ) ;
EDIT_substitute_brick( outset , 0 , MRI_float , MRI_FLOAT_PTR(imout) ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dPolyfit" , argc,argv , outset ) ;
DSET_write(outset) ;
WROTE_DSET(outset) ;
}
if( resid != NULL ){
THD_3dim_dataset *outset = EDIT_empty_copy( inset ) ;
float *inar=MRI_FLOAT_PTR(imin) , *outar=MRI_FLOAT_PTR(imout) ;
int nx,ny,nz , nxyz , kk ;
nx = imout->nx ; ny = imout->ny ; nz = imout->nz ; nxyz = nx*ny*nz ;
for( kk=0 ; kk < nxyz ; kk++ ) outar[kk] = inar[kk] - outar[kk] ;
mri_free(imin) ;
EDIT_dset_items( outset ,
ADN_prefix , resid ,
ADN_nvals , 1 ,
ADN_ntt , 0 ,
ADN_none ) ;
EDIT_substitute_brick( outset , 0 , MRI_float , MRI_FLOAT_PTR(imout) ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dPolyfit" , argc,argv , outset ) ;
DSET_write(outset) ;
WROTE_DSET(outset) ;
}
if( cfnam != NULL && fvit != NULL ){ /* won't work with '-byslice' */
char *qn ;
qn = STRING_HAS_SUFFIX(cfnam,".1D") ? cfnam : modify_afni_prefix(cfnam,NULL,".1D") ;
mri_write_floatvec( qn , fvit ) ;
}
exit(0) ;
}
int main( int argc , char *argv[] )
{
int iarg , ct , do_GM=0 ;
int do_T2=0 ; float T2_uperc=98.5f ; byte *T2_mask=NULL ;
char *prefix = "Unifized" ;
THD_3dim_dataset *inset=NULL , *outset=NULL ;
MRI_IMAGE *imin , *imout ;
float clfrac=0.2f ;
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf("\n"
"Usage: 3dUnifize [options] inputdataset\n\n"
"* The input dataset is supposed to be a T1-weighted volume,\n"
" possibly already skull-stripped (e.g., via 3dSkullStrip).\n"
" ++ However, this program can be a useful step to take BEFORE\n"
" 3dSkullStrip, since the latter program can fail if the input\n"
" volume is strongly shaded -- 3dUnifize will (mostly) remove\n"
" such shading artifacts.\n"
"* The output dataset has the white matter (WM) intensity approximately\n"
" uniformized across space, and scaled to peak at about 1000.\n"
"* The output dataset is always stored in float format!\n"
"* If the input dataset has more than 1 sub-brick, only sub-brick\n"
" #0 will be processed!\n"
"* Method: Obi-Wan's personal variant of Ziad's sneaky trick.\n"
" (If you want to know what his trick is, you'll have to ask him, or\n"
" read Obi-Wan's source code, which is a world of ecstasy and exaltation,\n"
" or just read all the way to the end of this help output.)\n"
"* The principal motive for this program is for use in an image\n"
" registration script, and it may or may not be useful otherwise.\n"
"\n"
"--------\n"
"Options:\n"
"--------\n"
" -prefix pp = Use 'pp' for prefix of output dataset.\n"
" -input dd = Alternative way to specify input dataset.\n"
" -T2 = Treat the input as if it were T2-weighted, rather than\n"
" T1-weighted. This processing is done simply by inverting\n"
" the image contrast, processing it as if that result were\n"
" T1-weighted, and then re-inverting the results.\n"
" ++ This option is NOT guaranteed to be useful for anything!\n"
" ++ Of course, nothing in AFNI comes with a guarantee :-)\n"
" ++ If you want to be REALLY sneaky, giving this option twice\n"
" will skip the second inversion step, so the result will\n"
" look like a T1-weighted volume (except at the edges and\n"
" near blood vessels).\n"
" ++ Might be useful for skull-stripping T2-weighted datasets.\n"
" ++ Don't try the '-T2 -T2' trick on FLAIR-T2-weighted datasets.\n"
" The results aren't pretty!\n"
" -GM = Also scale to unifize 'gray matter' = lower intensity voxels\n"
" (to aid in registering images from different scanners).\n"
" ++ This option is recommended for use with 3dQwarp when\n"
" aligning 2 T1-weighted volumes, in order to make the\n"
" WM-GM contrast about the same for the datasets, even\n"
" if they don't come from the same scanner/pulse-sequence.\n"
" ++ Note that standardizing the contrasts with 3dUnifize will help\n"
" 3dQwarp match the source dataset to the base dataset. If you\n"
" later want the original source dataset to be warped, you can\n"
" do so using the 3dNwarpApply program.\n"
" -Urad rr = Sets the radius (in voxels) of the ball used for the sneaky trick.\n"
" ++ Default value is %.1f, and should be changed proportionally\n"
" if the dataset voxel size differs significantly from 1 mm.\n"
" -ssave ss = Save the scale factor used at each voxel into a dataset 'ss'.\n"
" ++ This is the white matter scale factor, and does not include\n"
" the factor from the '-GM' option (if that was included).\n"
" ++ The input dataset is multiplied by the '-ssave' image\n"
" (voxel-wise) to get the WM-unifized image.\n"
" ++ Another volume (with the same grid dimensions) could be\n"
" scaled the same way using 3dcalc, if that is needed.\n"
" -quiet = Don't print the fun fun fun progress messages (but whyyyy?).\n"
" ++ For the curious, the codes used are:\n"
" A = Automask\n"
" D = Duplo down (process a half-size volume)\n"
" V = Voxel-wise histograms to get local scale factors\n"
" U = duplo Up (convert local scale factors to full-size volume)\n"
" W = multiply by White matter factors\n"
" G = multiply by Gray matter factors [cf the -GM option]\n"
" I = contrast inversion [cf the -T2 option]\n"
" ++ 'Duplo down' means to scale the input volume to be half the\n"
" grid size in each direction for speed when computing the\n"
" voxel-wise histograms. The sub-sampling is done using the\n"
" median of the central voxel value and its 6 nearest neighbors.\n"
"\n"
"------------------------------------------\n"
"Special options for Jedi AFNI Masters ONLY:\n"
"------------------------------------------\n"
" -rbt R b t = Specify the 3 parameters for the algorithm, as 3 numbers\n"
" following the '-rbt':\n"
" R = radius; same as given by option '-Urad' [default=%.1f]\n"
" b = bottom percentile of normalizing data range [default=%.1f]\n"
" r = top percentile of normalizing data range [default=%.1f]\n"
"\n"
" -T2up uu = Set the upper percentile point used for T2-T1 inversion.\n"
" The default value is 98.5 (for no good reason), and 'uu' is\n"
" allowed to be anything between 90 and 100 (inclusive).\n"
" ++ The histogram of the data is built, and the uu-th percentile\n"
" point value is called 'U'. The contrast inversion is simply\n"
" given by output_value = max( 0 , U - input_value ).\n"
"\n"
" -clfrac cc = Set the automask 'clip level fraction' to 'cc', which\n"
" must be a number between 0.1 and 0.9.\n"
" A small 'cc' means to make the initial threshold\n"
" for clipping (a la 3dClipLevel) smaller, which\n"
" will tend to make the mask larger. [default=0.1]\n"
" ++ [22 May 2013] The previous version of this program used a\n"
" clip level fraction of 0.5, which proved to be too large\n"
" for some users, who had images with very strong shading issues.\n"
" Thus, the default value for this parameter was lowered to 0.1.\n"
" ++ [24 May 2016] The default value for this parameter was\n"
" raised to 0.2, since the lower value often left a lot of\n"
" noise outside the head on non-3dSkullStrip-ed datasets.\n"
" You can still manually set -clfrac to 0.1 if you need to\n"
" correct for very large shading artifacts.\n"
" ++ If the results of 3dUnifize have a lot of noise outside the head,\n"
" then using '-clfrac 0.5' value will probably help.\n"
#ifndef USE_ALL_VALS
"\n"
" -useall = The 'old' way of operating was to use all dataset values\n"
" in the local WM histogram. The 'new' way [May 2016] is to\n"
" only use positive values. If you want to use the 'old' way,\n"
" then this option is what you want.\n"
#endif
"\n"
"-- Feb 2013 - by Obi-Wan Unifobi\n"
#ifdef USE_OMP
"-- This code uses OpenMP to speed up the slowest part (voxel-wise histograms).\n"
#endif
, Uprad , Uprad , Upbot , Uptop ) ;
printf("\n"
"----------------------------------------------------------------------------\n"
"HOW IT WORKS (Ziad's sneaky trick is revealed at last! And more.)\n"
"----------------------------------------------------------------------------\n"
"The basic idea is that white matter in T1-weighted images is reasonably\n"
"uniform in intensity, at least when averaged over 'large-ish' regions.\n"
"\n"
"The first step is to create a local white matter intensity volume.\n"
"Around each voxel (inside the volume 'automask'), the ball of values\n"
"within a fixed radius (default=18.3 voxels) is extracted and these\n"
"numbers are sorted. The values in the high-intensity range of the\n"
"histogram (default=70%% to 80%%) are averaged. The result from this\n"
"step is a smooth 3D map of the 'white matter intensity' (WMI).\n"
"\n"
" [The parameters of the above process can be altered with the '-rbt' option.]\n"
" [For speed, the WMI map is produced on an image that is half-size in all ]\n"
" [directions ('Duplo down'), and then is expanded back to the full-size ]\n"
" [volume ('Duplo up'). The automask procedure can be somewhat controlled ]\n"
" [via the '-clfrac' option. The default setting is designed to deal with ]\n"
" [heavily shaded images, where the WMI varies by a factor of 5 or more over ]\n"
" [the image volume. ]\n"
"\n"
"The second step is to scale the value at every voxel location x in the input\n"
"volume by the factor 1000/WMI(x), so that the 'white matter intensity' is\n"
"now uniform-ized to be 1000 everywhere. (This is Ziad's 'trick'; it is easy,\n"
"works well, and doesn't require fitting some spatial model to the data: the\n"
"data provides its own model.)\n"
"\n"
"If the '-GM' option is used, then this scaled volume is further processed\n"
"to make the lower intensity values (presumably gray matter) have a contrast\n"
"similar to that from a collection of 3 Tesla MP-RAGE images that were\n"
"acquired at the NIH. (This procedure is not Ziad's fault, and should be\n"
"blamed on the reclusive Obi-Wan Unifobi.)\n"
"\n"
"From the WM-uniform-ized volume, the median of all values larger than 1000\n"
"is computed; call this value P. P-1000 represents the upward dispersion\n"
"of the high-intensity (white matter) voxels in the volume. This value is\n"
"'reflected' below 1000 to Q = 1000 - 2*(P-1000), and Q is taken to be the\n"
"upper bound for gray matter voxel intensities. A lower bound for gray\n"
"matter voxel values is estimated via the 'clip fraction' algorithm as\n"
"implemented in program 3dClipLevel; call this lower bound R. The median\n"
"of all values between R and Q is computed; call this value G, which is taken\n"
"to be a 'typical' gray matter voxel instensity. Then the values z in the\n"
"entire volume are linearly scaled by the formula\n"
" z_out = (1000-666)/(1000-G) * (z_in-1000) + 1000\n"
"so that the WM uniform-ized intensity of 1000 remains at 1000, and the gray\n"
"matter median intensity of G is mapped to 666. (Values z_out that end up\n"
"negative are set to 0; as a result, some of CSF might end up as 0.)\n"
"The value 666 was chosen because it gave results visually comparable to\n"
"various NIH-generated 3 Tesla T1-weighted datasets. (Any suggestions that\n"
"this value was chosen for other reasons will be treated as 'beastly'.)\n"
"\n"
"To recap: the WM uniform-ization process provides a linear scaling factor\n"
"that varies for each voxel ('local'), while the GM normalization process\n"
"uses a global linear scaling. The GM process is optional, and is simply\n"
"designed to make the various T1-weighted images look similar.\n"
"\n"
"-----** CAVEAT **-----\n"
"This procedure was primarily developed to aid in 3D registration, especially\n"
"when using 3dQwarp, so that the registration algorithms are trying to match\n"
"images that are alike. It is *NOT* intended to be used for quantification\n"
"purposes, such as Voxel Based Morphometry! That would better be done via\n"
"the 3dSeg program, which is far more complicated.\n"
"----------------------------------------------------------------------------\n"
) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
mainENTRY("3dUnifize main"); machdep(); AFNI_logger("3dUnifize",argc,argv);
PRINT_VERSION("3dUnifize") ;
ct = NI_clock_time() ;
/*-- scan command line --*/
THD_automask_set_clipfrac(0.1f) ; /* 22 May 2013 */
THD_automask_extclip(1) ; /* 19 Dec 2014 */
iarg = 1 ;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcmp(argv[iarg],"-clfrac") == 0 || strcmp(argv[iarg],"-mfrac") == 0 ){ /* 22 May 2013 */
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
clfrac = (float)strtod( argv[iarg] , NULL ) ;
if( clfrac < 0.1f || clfrac > 0.9f )
ERROR_exit("-clfrac value %f is illegal!",clfrac) ;
THD_automask_set_clipfrac(clfrac) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-prefix") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
prefix = argv[iarg] ;
if( !THD_filename_ok(prefix) ) ERROR_exit("Illegal value after -prefix!") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ssave") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
sspref = strdup(argv[iarg]) ;
if( !THD_filename_ok(sspref) ) ERROR_exit("Illegal value after -ssave!") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-input") == 0 || strcmp(argv[iarg],"-inset") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
if( inset != NULL ) ERROR_exit("Can't use '%s' twice" ,argv[iarg-1]) ;
inset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-Urad") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
Uprad = (float)strtod(argv[iarg],NULL) ;
if( Uprad < 5.0f || Uprad > 40.0f )
ERROR_exit("Illegal value %f after option -Urad",Uprad) ;
iarg++ ; continue ;
}
#ifndef USE_ALL_VALS
if( strcmp(argv[iarg],"-useall") == 0 ){ /* 17 May 2016 */
USE_ALL_VALS = 1 ; iarg++ ; continue ;
}
#else
if( strcmp(argv[iarg],"-useall") == 0 ){
WARNING_message("-useall option is disabled in this version") ;
iarg++ ; continue ;
}
#endif
if( strcmp(argv[iarg],"-param") == 0 || /*--- HIDDEN OPTION ---*/
strcmp(argv[iarg],"-rbt" ) == 0 ){
if( ++iarg >= argc-2 ) ERROR_exit("Need 3 arguments (R pb pt) after '%s'",argv[iarg-1]) ;
Uprad = (float)strtod(argv[iarg++],NULL) ;
Upbot = (float)strtod(argv[iarg++],NULL) ;
Uptop = (float)strtod(argv[iarg++],NULL) ;
if( Uprad < 5.0f || Uprad > 40.0f ||
Upbot < 30.0f || Upbot > 80.0f ||
Uptop <= Upbot || Uptop > 90.0f )
ERROR_exit("Illegal values (R pb pt) after '%s'",argv[iarg-4]) ;
continue ;
}
if( strcasecmp(argv[iarg],"-GM") == 0 ){
do_GM++ ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-T2") == 0 ){ /* 18 Dec 2014 */
do_T2++ ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-T2up") == 0 ){ /* 18 Dec 2014 */
T2_uperc = (float)strtod( argv[++iarg] , NULL ) ;
if( T2_uperc < 90.0f || T2_uperc > 100.0f )
ERROR_exit("-T2up value is out of range 90..100 :-(") ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-quiet") == 0 ){
verb = 0 ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-verb") == 0 ){
verb++ ; iarg++ ; continue ;
}
ERROR_exit("Unknown option: %s\n",argv[iarg]);
}
/* read input dataset, if not already there */
if( inset == NULL ){
if( iarg >= argc ) ERROR_exit("No dataset name on command line?\n") ;
inset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
}
if( verb ) fprintf(stderr," + Pre-processing: ") ;
/* load input from disk */
DSET_load( inset ) ; CHECK_LOAD_ERROR(inset) ;
if( DSET_NVALS(inset) > 1 )
WARNING_message("Only processing sub-brick #0 (out of %d)",DSET_NVALS(inset)) ;
/* make a float copy for processing */
imin = mri_to_float( DSET_BRICK(inset,0) ) ; DSET_unload(inset) ;
if( imin == NULL ) ERROR_exit("Can't copy input dataset brick?!") ;
#if 0
THD_cliplevel_search(imin) ; exit(0) ; /* experimentation only */
#endif
THD_automask_set_clipfrac(clfrac) ;
/* invert T2? */
if( do_T2 ){
if( verb ) fprintf(stderr,"I") ;
T2_mask = mri_automask_image(imin) ;
mri_invertcontrast_inplace( imin , T2_uperc , T2_mask ) ;
}
/* do the actual work */
imout = mri_WMunifize(imin) ; /* local WM scaling */
free(imin) ;
if( sspref != NULL && sclim != NULL ){ /* 25 Jun 2013 */
STATUS("output -ssave") ;
outset = EDIT_empty_copy( inset ) ;
EDIT_dset_items( outset ,
ADN_prefix , sspref ,
ADN_nvals , 1 ,
ADN_ntt , 0 ,
ADN_none ) ;
EDIT_substitute_brick( outset , 0 , MRI_float , MRI_FLOAT_PTR(sclim) ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dUnifize" , argc,argv , outset ) ;
DSET_write(outset) ; outset = NULL ;
}
if( sclim != NULL ){ mri_free(sclim) ; sclim = NULL ; }
if( imout == NULL ){ /* this is bad-ositiness */
if( verb ) fprintf(stderr,"\n") ;
ERROR_exit("Can't compute Unifize-d dataset for some reason :-(") ;
}
if( do_GM ) mri_GMunifize(imout) ; /* global GM scaling */
if( do_T2 == 1 ){ /* re-invert T2? */
if( verb ) fprintf(stderr,"I") ;
mri_invertcontrast_inplace( imout , T2_uperc , T2_mask ) ;
} else if( do_T2 == 2 ){ /* don't re-invert, but clip off bright edges */
mri_clipedges_inplace( imout , PKVAL*1.111f , PKVAL*1.055f ) ;
}
if( verb ) fprintf(stderr,"\n") ;
/* create output dataset, and write it into the historical record */
outset = EDIT_empty_copy( inset ) ;
EDIT_dset_items( outset ,
ADN_prefix , prefix ,
ADN_nvals , 1 ,
ADN_ntt , 0 ,
ADN_none ) ;
EDIT_substitute_brick( outset , 0 , MRI_float , MRI_FLOAT_PTR(imout) ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dUnifize" , argc,argv , outset ) ;
DSET_write(outset) ;
WROTE_DSET(outset) ;
DSET_delete(outset) ; DSET_delete(inset) ;
/* vamoose the ranch */
if( verb ){
double cput = COX_cpu_time() ;
if( cput > 0.05 )
INFO_message("===== CPU time = %.1f sec Elapsed = %.1f\n",
COX_cpu_time() , 0.001*(NI_clock_time()-ct) ) ;
else
INFO_message("===== Elapsed = %.1f sec\n", 0.001*(NI_clock_time()-ct) ) ;
}
exit(0) ;
}
