int
main(int argc, char *argv[]) {
char **av, fname[STRLEN], *out_fname, *subject_name, *cp ;
int ac, nargs, i, n, noint = 0, options ;
int msec, minutes, seconds, nsubjects, input ;
struct timeb start ;
GCA *gca ;
MRI *mri_seg, *mri_tmp, *mri_inputs ;
TRANSFORM *transform ;
LTA *lta;
GCA_BOUNDARY *gcab ;
Progname = argv[0] ;
ErrorInit(NULL, NULL, NULL) ;
DiagInit(NULL, NULL, NULL) ;
TimerStart(&start) ;
parms.use_gradient = 0 ;
spacing = 8 ;
/* rkt: check for and handle version tag */
nargs = handle_version_option
(argc, argv,
"$Id: mri_gcab_train.c,v 1.4 2011/03/16 20:23:33 fischl Exp $",
"$Name: $");
if (nargs && argc - nargs == 1)
exit (0);
argc -= nargs;
// parse command line args
ac = argc ;
av = argv ;
for ( ; argc > 1 && ISOPTION(*argv[1]) ; argc--, argv++) {
nargs = get_option(argc, argv) ;
argc -= nargs ;
argv += nargs ;
}
printf("reading gca from %s\n", argv[1]) ;
gca = GCAread(argv[1]) ;
if (!gca)
exit(Gerror) ;
if (!strlen(subjects_dir)) /* hasn't been set on command line */
{
cp = getenv("SUBJECTS_DIR") ;
if (!cp)
ErrorExit(ERROR_BADPARM, "%s: SUBJECTS_DIR not defined in environment",
Progname);
strcpy(subjects_dir, cp) ;
if (argc < 4)
usage_exit(1) ;
}
// options parsed. subjects and gca name remaining
out_fname = argv[argc-1] ;
nsubjects = argc-3 ;
for (options = i = 0 ; i < nsubjects ; i++) {
if (argv[i+1][0] == '-') {
nsubjects-- ;
options++ ;
}
}
printf("training on %d subject and writing results to %s\n",
nsubjects, out_fname) ;
n = 0 ;
gcab = GCABalloc(gca, 8, 0, 30, 10, target_label);
strcpy(gcab->gca_fname, argv[1]) ;
// going through the subject one at a time
for (nargs = i = 0 ; i < nsubjects+options ; i++) {
subject_name = argv[i+2] ;
//////////////////////////////////////////////////////////////
printf("***************************************"
"************************************\n");
printf("processing subject %s, %d of %d...\n", subject_name,i+1-nargs,
nsubjects);
if (stricmp(subject_name, "-NOINT") == 0) {
printf("not using intensity information for subsequent subjects...\n");
noint = 1 ;
nargs++ ;
continue ;
} else if (stricmp(subject_name, "-INT") == 0) {
printf("using intensity information for subsequent subjects...\n");
noint = 0 ;
nargs++ ;
continue ;
}
// reading this subject segmentation
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, seg_dir) ;
if (Gdiag & DIAG_SHOW && DIAG_VERBOSE_ON)
fprintf(stderr, "Reading segmentation from %s...\n", fname) ;
mri_seg = MRIread(fname) ;
if (!mri_seg)
ErrorExit(ERROR_NOFILE, "%s: could not read segmentation file %s",
Progname, fname) ;
if ((mri_seg->type != MRI_UCHAR) && (mri_seg->type != MRI_FLOAT)) {
ErrorExit
(ERROR_NOFILE,
"%s: segmentation file %s is not type UCHAR or FLOAT",
Progname, fname) ;
}
if (binarize) {
int j ;
for (j = 0 ; j < 256 ; j++) {
if (j == binarize_in)
MRIreplaceValues(mri_seg, mri_seg, j, binarize_out) ;
else
MRIreplaceValues(mri_seg, mri_seg, j, 0) ;
}
}
if (insert_fname) {
MRI *mri_insert ;
sprintf(fname, "%s/%s/mri/%s",
subjects_dir, subject_name, insert_fname) ;
mri_insert = MRIread(fname) ;
if (mri_insert == NULL)
ErrorExit(ERROR_NOFILE,
"%s: could not read volume from %s for insertion",
Progname, insert_fname) ;
MRIbinarize(mri_insert, mri_insert, 1, 0, insert_label) ;
MRIcopyLabel(mri_insert, mri_seg, insert_label) ;
MRIfree(&mri_insert) ;
}
replaceLabels(mri_seg) ;
MRIeraseBorderPlanes(mri_seg, 1) ;
for (input = 0 ; input < gca->ninputs ; input++) {
//////////// set the gca type //////////////////////////////
// is this T1/PD training?
// how can we allow flash data training ???????
// currently checks the TE, TR, FA to be the same for all inputs
// thus we cannot allow flash data training.
////////////////////////////////////////////////////////////
sprintf(fname, "%s/%s/mri/%s",
subjects_dir, subject_name,input_names[input]);
if (DIAG_VERBOSE_ON)
printf("reading co-registered input from %s...\n", fname) ;
fprintf(stderr, " reading input %d: %s\n", input, fname);
mri_tmp = MRIread(fname) ;
if (!mri_tmp)
ErrorExit
(ERROR_NOFILE,
"%s: could not read image from file %s", Progname, fname) ;
// input check 1
if (getSliceDirection(mri_tmp) != MRI_CORONAL) {
ErrorExit
(ERROR_BADPARM,
"%s: must be in coronal direction, but it is not\n",
fname);
}
// input check 2
if (mri_tmp->xsize != 1 || mri_tmp->ysize != 1 || mri_tmp->zsize != 1) {
ErrorExit
(ERROR_BADPARM,
"%s: must have 1mm voxel size, but have (%f, %f, %f)\n",
fname, mri_tmp->xsize, mri_tmp->ysize, mri_tmp->ysize);
}
// input check 3 is removed. now we can handle c_(ras) != 0 case
// input check 4
if (i == 0) {
TRs[input] = mri_tmp->tr ;
FAs[input] = mri_tmp->flip_angle ;
TEs[input] = mri_tmp->te ;
} else if (!FEQUAL(TRs[input],mri_tmp->tr) ||
!FEQUAL(FAs[input],mri_tmp->flip_angle) ||
!FEQUAL(TEs[input], mri_tmp->te))
ErrorExit
(ERROR_BADPARM,
"%s: subject %s input volume %s: sequence parameters "
"(%2.1f, %2.1f, %2.1f)"
"don't match other inputs (%2.1f, %2.1f, %2.1f)",
Progname, subject_name, fname,
mri_tmp->tr, DEGREES(mri_tmp->flip_angle), mri_tmp->te,
TRs[input], DEGREES(FAs[input]), TEs[input]) ;
// first time do the following
if (input == 0) {
int nframes = gca->ninputs ;
///////////////////////////////////////////////////////////
mri_inputs =
MRIallocSequence(mri_tmp->width, mri_tmp->height, mri_tmp->depth,
mri_tmp->type, nframes) ;
if (!mri_inputs)
ErrorExit
(ERROR_NOMEMORY,
"%s: could not allocate input volume %dx%dx%dx%d",
mri_tmp->width, mri_tmp->height, mri_tmp->depth,nframes) ;
MRIcopyHeader(mri_tmp, mri_inputs) ;
}
// -mask option ////////////////////////////////////////////
if (mask_fname)
{
MRI *mri_mask ;
sprintf(fname, "%s/%s/mri/%s",
subjects_dir, subject_name, mask_fname);
printf("reading volume %s for masking...\n", fname) ;
mri_mask = MRIread(fname) ;
if (!mri_mask)
ErrorExit(ERROR_NOFILE, "%s: could not open mask volume %s.\n",
Progname, fname) ;
MRImask(mri_tmp, mri_mask, mri_tmp, 0, 0) ;
MRIfree(&mri_mask) ;
}
MRIcopyFrame(mri_tmp, mri_inputs, 0, input) ;
MRIfree(&mri_tmp) ;
}// end of inputs per subject
/////////////////////////////////////////////////////////
// xform_name is given, then we can use the consistent c_(r,a,s) for gca
/////////////////////////////////////////////////////////
if (xform_name)
{
// we read talairach.xfm which is a RAS-to-RAS
sprintf(fname, "%s/%s/mri/transforms/%s",
subjects_dir, subject_name, xform_name) ;
if (Gdiag & DIAG_SHOW && DIAG_VERBOSE_ON)
printf("INFO: reading transform file %s...\n", fname);
if (!FileExists(fname))
{
fprintf(stderr,"ERROR: cannot find transform file %s\n",fname);
exit(1);
}
transform = TransformRead(fname);
if (!transform)
ErrorExit(ERROR_NOFILE, "%s: could not read transform from file %s",
Progname, fname);
modify_transform(transform, mri_inputs, gca);
// Here we do 2 things
// 1. modify gca direction cosines to
// that of the transform destination (both linear and non-linear)
// 2. if ras-to-ras transform,
// then change it to vox-to-vox transform (linear case)
// modify transform to store inverse also
TransformInvert(transform, mri_inputs) ;
// verify inverse
lta = (LTA *) transform->xform;
}
else
{
GCAreinit(mri_inputs, gca);
// just use the input value, since dst = src volume
transform = TransformAlloc(LINEAR_VOXEL_TO_VOXEL, NULL) ;
}
////////////////////////////////////////////////////////////////////
// train gca
////////////////////////////////////////////////////////////////////
// segmentation is seg volume
// inputs is the volumes of all inputs
// transform is for this subject
// noint is whether to use intensity information or not
GCABtrain(gcab, mri_inputs, mri_seg, transform, target_label) ;
MRIfree(&mri_seg) ;
MRIfree(&mri_inputs) ;
TransformFree(&transform) ;
}
GCABcompleteTraining(gcab) ;
if (smooth > 0) {
printf("regularizing conditional densities with smooth=%2.2f\n", smooth) ;
GCAregularizeConditionalDensities(gca, smooth) ;
}
if (navgs) {
printf("applying mean filter %d times to conditional densities\n", navgs) ;
GCAmeanFilterConditionalDensities(gca, navgs) ;
}
printf("writing trained GCAB to %s...\n", out_fname) ;
if (GCABwrite(gcab, out_fname) != NO_ERROR)
ErrorExit
(ERROR_BADFILE, "%s: could not write gca to %s", Progname, out_fname) ;
if (Gdiag & DIAG_WRITE && DIAG_VERBOSE_ON)
{
MRI *mri ;
mri = GCAbuildMostLikelyVolume(gca, NULL) ;
MRIwrite(mri, "m.mgz") ;
MRIfree(&mri) ;
}
if (histo_fname) {
FILE *fp ;
int histo_counts[10000], xn, yn, zn, max_count ;
GCA_NODE *gcan ;
memset(histo_counts, 0, sizeof(histo_counts)) ;
fp = fopen(histo_fname, "w") ;
if (!fp)
ErrorExit(ERROR_BADFILE, "%s: could not open histo file %s",
Progname, histo_fname) ;
max_count = 0 ;
for (xn = 0 ; xn < gca->node_width; xn++) {
for (yn = 0 ; yn < gca->node_height ; yn++) {
for (zn = 0 ; zn < gca->node_depth ; zn++) {
gcan = &gca->nodes[xn][yn][zn] ;
if (gcan->nlabels < 1)
continue ;
if (gcan->nlabels == 1 && IS_UNKNOWN(gcan->labels[0]))
continue ;
histo_counts[gcan->nlabels]++ ;
if (gcan->nlabels > max_count)
max_count = gcan->nlabels ;
}
}
}
max_count = 20 ;
for (xn = 1 ; xn < max_count ; xn++)
fprintf(fp, "%d %d\n", xn, histo_counts[xn]) ;
fclose(fp) ;
}
GCAfree(&gca) ;
msec = TimerStop(&start) ;
seconds = nint((float)msec/1000.0f) ;
minutes = seconds / 60 ;
seconds = seconds % 60 ;
printf("classifier array training took %d minutes"
" and %d seconds.\n", minutes, seconds) ;
exit(0) ;
return(0) ;
}
int
main(int argc, char *argv[])
{
char *gca_fname, *in_fname, *out_fname, **av, *xform_fname, fname[STRLEN] ;
MRI *mri_in, *mri_norm = NULL, *mri_tmp, *mri_ctrl = NULL ;
GCA *gca ;
int ac, nargs, nsamples, msec, minutes, seconds;
int i, struct_samples, norm_samples = 0, n, input, ninputs ;
struct timeb start ;
GCA_SAMPLE *gcas, *gcas_norm = NULL, *gcas_struct ;
TRANSFORM *transform = NULL ;
char cmdline[CMD_LINE_LEN], line[STRLEN], *cp, subject[STRLEN], sdir[STRLEN], base_name[STRLEN] ;
FILE *fp ;
make_cmd_version_string
(argc, argv,
"$Id: mri_cal_normalize.c,v 1.2.2.1 2011/08/31 00:32:41 nicks Exp $",
"$Name: stable5 $", cmdline);
/* rkt: check for and handle version tag */
nargs = handle_version_option
(argc, argv,
"$Id: mri_cal_normalize.c,v 1.2.2.1 2011/08/31 00:32:41 nicks Exp $",
"$Name: stable5 $");
if (nargs && argc - nargs == 1)
exit (0);
argc -= nargs;
setRandomSeed(-1L) ;
Progname = argv[0] ;
DiagInit(NULL, NULL, NULL) ;
ErrorInit(NULL, NULL, NULL) ;
ac = argc ;
av = argv ;
for ( ; argc > 1 && ISOPTION(*argv[1]) ; argc--, argv++)
{
nargs = get_option(argc, argv) ;
argc -= nargs ;
argv += nargs ;
}
if (argc < 6)
ErrorExit
(ERROR_BADPARM,
"usage: %s [<options>] <longitudinal time point file> <in vol> <atlas> <transform file> <out vol> \n",
Progname) ;
in_fname = argv[2] ;
gca_fname = argv[3] ;
xform_fname = argv[4] ;
out_fname = argv[5] ;
transform = TransformRead(xform_fname) ;
if (transform == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not read transform from %s", Progname, xform_fname) ;
if (read_ctrl_point_fname)
{
mri_ctrl = MRIread(read_ctrl_point_fname) ;
if (mri_ctrl == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not read precomputed control points from %s",
Progname, read_ctrl_point_fname) ;
}
TimerStart(&start) ;
printf("reading atlas from '%s'...\n", gca_fname) ;
fflush(stdout) ;
gca = GCAread(gca_fname) ;
if (gca == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not open GCA %s.\n",Progname, gca_fname) ;
GCAregularizeConditionalDensities(gca, .5) ;
FileNamePath(argv[1], sdir) ;
cp = strrchr(sdir, '/') ;
if (cp)
{
strcpy(base_name, cp+1) ;
*cp = 0 ; // remove last component of path, which is base subject name
}
ninputs = 0 ;
fp = fopen(argv[1], "r") ;
if (fp == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not read time point file %s", argv[1]) ;
do
{
cp = fgetl(line, STRLEN-1, fp) ;
if (cp != NULL && strlen(cp) > 0)
{
subjects[ninputs] = (char *)calloc(strlen(cp)+1, sizeof(char)) ;
strcpy(subjects[ninputs], cp) ;
ninputs++ ;
}
} while (cp != NULL && strlen(cp) > 0) ;
fclose(fp) ;
printf("processing %d timepoints in SUBJECTS_DIR %s...\n", ninputs, sdir) ;
for (input = 0 ; input < ninputs ; input++)
{
sprintf(subject, "%s.long.%s", subjects[input], base_name) ;
printf("reading subject %s - %d of %d\n", subject, input+1, ninputs) ;
sprintf(fname, "%s/%s/mri/%s", sdir, subject, in_fname) ;
mri_tmp = MRIread(fname) ;
if (!mri_tmp)
ErrorExit(ERROR_NOFILE, "%s: could not read input MR volume from %s",
Progname, fname) ;
MRImakePositive(mri_tmp, mri_tmp) ;
if (mri_tmp && ctrl_point_fname && !mri_ctrl)
{
mri_ctrl = MRIallocSequence(mri_tmp->width, mri_tmp->height,
mri_tmp->depth,MRI_FLOAT, nregions*2) ; // labels and means
MRIcopyHeader(mri_tmp, mri_ctrl) ;
}
if (input == 0)
{
mri_in =
MRIallocSequence(mri_tmp->width, mri_tmp->height, mri_tmp->depth,
mri_tmp->type, ninputs) ;
if (!mri_in)
ErrorExit(ERROR_NOMEMORY,
"%s: could not allocate input volume %dx%dx%dx%d",
mri_tmp->width,mri_tmp->height,mri_tmp->depth,ninputs) ;
MRIcopyHeader(mri_tmp, mri_in) ;
}
if (mask_fname)
{
int i ;
MRI *mri_mask ;
mri_mask = MRIread(mask_fname) ;
if (!mri_mask)
ErrorExit(ERROR_NOFILE, "%s: could not open mask volume %s.\n",
Progname, mask_fname) ;
for (i = 1 ; i < WM_MIN_VAL ; i++)
MRIreplaceValues(mri_mask, mri_mask, i, 0) ;
MRImask(mri_tmp, mri_mask, mri_tmp, 0, 0) ;
MRIfree(&mri_mask) ;
}
MRIcopyFrame(mri_tmp, mri_in, 0, input) ;
MRIfree(&mri_tmp) ;
}
MRIaddCommandLine(mri_in, cmdline) ;
GCAhistoScaleImageIntensitiesLongitudinal(gca, mri_in, 1) ;
{
int j ;
gcas = GCAfindAllSamples(gca, &nsamples, NULL, 1) ;
printf("using %d sample points...\n", nsamples) ;
GCAcomputeSampleCoords(gca, mri_in, gcas, nsamples, transform) ;
if (sample_fname)
GCAtransformAndWriteSamples
(gca, mri_in, gcas, nsamples, sample_fname, transform) ;
for (j = 0 ; j < 1 ; j++)
{
for (n = 1 ; n <= nregions ; n++)
{
for (norm_samples = i = 0 ; i < NSTRUCTURES ; i++)
{
if (normalization_structures[i] == Gdiag_no)
DiagBreak() ;
printf("finding control points in %s....\n",
cma_label_to_name(normalization_structures[i])) ;
gcas_struct = find_control_points(gca, gcas, nsamples, &struct_samples, n,
normalization_structures[i], mri_in, transform, min_prior,
ctl_point_pct) ;
discard_unlikely_control_points(gca, gcas_struct, struct_samples, mri_in, transform,
cma_label_to_name(normalization_structures[i])) ;
if (mri_ctrl && ctrl_point_fname) // store the samples
copy_ctrl_points_to_volume(gcas_struct, struct_samples, mri_ctrl, n-1) ;
if (i)
{
GCA_SAMPLE *gcas_tmp ;
gcas_tmp = gcas_concatenate(gcas_norm, gcas_struct, norm_samples, struct_samples) ;
free(gcas_norm) ;
norm_samples += struct_samples ;
gcas_norm = gcas_tmp ;
}
else
{
gcas_norm = gcas_struct ; norm_samples = struct_samples ;
}
}
printf("using %d total control points "
"for intensity normalization...\n", norm_samples) ;
if (normalized_transformed_sample_fname)
GCAtransformAndWriteSamples(gca, mri_in, gcas_norm, norm_samples,
normalized_transformed_sample_fname,
transform) ;
mri_norm = GCAnormalizeSamplesAllChannels(mri_in, gca, gcas_norm, file_only ? 0 :norm_samples,
transform, ctl_point_fname, bias_sigma) ;
if (Gdiag & DIAG_WRITE)
{
char fname[STRLEN] ;
sprintf(fname, "norm%d.mgz", n) ;
printf("writing normalized volume to %s...\n", fname) ;
MRIwrite(mri_norm, fname) ;
sprintf(fname, "norm_samples%d.mgz", n) ;
GCAtransformAndWriteSamples(gca, mri_in, gcas_norm, norm_samples,
fname, transform) ;
}
MRIcopy(mri_norm, mri_in) ; /* for next pass through */
MRIfree(&mri_norm) ;
}
}
}
// now do cross-time normalization to bring each timepoint closer to the mean at each location
{
MRI *mri_frame1, *mri_frame2, *mri_tmp ;
double rms_before, rms_after ;
int i ;
mri_tmp = MRIcopy(mri_in, NULL) ;
mri_frame1 = MRIcopyFrame(mri_in, NULL, 0, 0) ;
mri_frame2 = MRIcopyFrame(mri_in, NULL, 1, 0) ;
rms_before = MRIrmsDiff(mri_frame1, mri_frame2) ;
printf("RMS before = %2.2f\n", rms_before) ;
MRIfree(&mri_frame1) ; MRIfree(&mri_frame2) ;
for (i = 50 ; i <= 50 ; i += 25)
{
MRIcopy(mri_tmp, mri_in) ;
normalize_timepoints_with_samples(mri_in, gcas_norm, norm_samples, i) ;
mri_frame1 = MRIcopyFrame(mri_in, NULL, 0, 0) ;
mri_frame2 = MRIcopyFrame(mri_in, NULL, 1, 0) ;
rms_after = MRIrmsDiff(mri_frame1, mri_frame2) ;
MRIfree(&mri_frame1) ; MRIfree(&mri_frame2) ;
printf("RMS after (%d) = %2.2f\n", i, rms_after) ;
}
}
{
MRI *mri_frame1, *mri_frame2 ;
double rms_after ;
int i ;
mri_tmp = MRIcopy(mri_in, NULL) ;
for (i = 10 ; i <= 10 ; i += 10)
{
MRIcopy(mri_tmp, mri_in) ;
normalize_timepoints(mri_in, 2.0, i) ;
mri_frame1 = MRIcopyFrame(mri_in, NULL, 0, 0) ;
mri_frame2 = MRIcopyFrame(mri_in, NULL, 1, 0) ;
rms_after = MRIrmsDiff(mri_frame1, mri_frame2) ;
MRIfree(&mri_frame1) ; MRIfree(&mri_frame2) ;
printf("RMS after intensity cohering = %2.2f\n", rms_after) ;
}
}
for (input = 0 ; input < ninputs ; input++)
{
sprintf(fname, "%s/%s.long.%s/mri/%s", sdir, subjects[input], base_name, out_fname) ;
printf("writing normalized volume to %s...\n", fname) ;
if (MRIwriteFrame(mri_in, fname, input) != NO_ERROR)
ErrorExit(ERROR_BADFILE, "%s: could not write normalized volume to %s",Progname, fname);
}
if (ctrl_point_fname)
{
printf("writing control points to %s\n", ctrl_point_fname) ;
MRIwrite(mri_ctrl, ctrl_point_fname) ;
MRIfree(&mri_ctrl) ;
}
MRIfree(&mri_in) ;
printf("freeing GCA...") ;
if (gca)
GCAfree(&gca) ;
printf("done.\n") ;
msec = TimerStop(&start) ;
seconds = nint((float)msec/1000.0f) ;
minutes = seconds / 60 ;
seconds = seconds % 60 ;
printf("normalization took %d minutes and %d seconds.\n",
minutes, seconds) ;
if (diag_fp)
fclose(diag_fp) ;
exit(0) ;
return(0) ;
}