static int
compute_cluster_statistics(MRI_SURFACE *mris, MRI *mri_profiles, MATRIX **m_covs, VECTOR **v_means, int k) {
int i, vno, cluster, nsamples, num[MAX_CLUSTERS];
int singular, cno_pooled, cno ;
MATRIX *m1, *mpooled, *m_inv_covs[MAX_CLUSTERS] ;
VECTOR *v1 ;
FILE *fp ;
double det, det_pooled ;
memset(num, 0, sizeof(num)) ;
nsamples = mri_profiles->nframes ;
v1 = VectorAlloc(nsamples, MATRIX_REAL) ;
m1 = MatrixAlloc(nsamples, nsamples, MATRIX_REAL) ;
mpooled = MatrixAlloc(nsamples, nsamples, MATRIX_REAL) ;
for (cluster = 0 ; cluster < k ; cluster++) {
VectorClear(v_means[cluster]) ;
MatrixClear(m_covs[cluster]) ;
}
// compute means
// fp = fopen("co.dat", "w") ;
fp = NULL ;
for (vno = 0 ; vno < mris->nvertices ; vno++) {
cluster = mris->vertices[vno].curv ;
for (i = 0 ; i < nsamples ; i++) {
VECTOR_ELT(v1, i+1) = MRIgetVoxVal(mri_profiles, vno, 0, 0, i) ;
if (cluster == 0 && fp)
fprintf(fp, "%f ", VECTOR_ELT(v1, i+1));
}
if (cluster == 0 && fp)
fprintf(fp, "\n") ;
num[cluster]++ ;
VectorAdd(v_means[cluster], v1, v_means[cluster]) ;
}
if (fp)
fclose(fp) ;
for (cluster = 0 ; cluster < k ; cluster++)
if (num[cluster] > 0)
VectorScalarMul(v_means[cluster], 1.0/(double)num[cluster], v_means[cluster]) ;
// compute inverse covariances
for (vno = 0 ; vno < mris->nvertices ; vno++) {
cluster = mris->vertices[vno].curv ;
for (i = 0 ; i < nsamples ; i++)
VECTOR_ELT(v1, i+1) = MRIgetVoxVal(mri_profiles, vno, 0, 0, i) ;
VectorSubtract(v_means[cluster], v1, v1) ;
VectorOuterProduct(v1, v1, m1) ;
MatrixAdd(m_covs[cluster], m1, m_covs[cluster]) ;
MatrixAdd(mpooled, m1, mpooled) ;
}
MatrixScalarMul(mpooled, 1.0/(double)mris->nvertices, mpooled) ;
cno_pooled = MatrixConditionNumber(mpooled) ;
det_pooled = MatrixDeterminant(mpooled) ;
for (cluster = 0 ; cluster < k ; cluster++)
if (num[cluster] > 0)
MatrixScalarMul(m_covs[cluster], 1.0/(double)num[cluster], m_covs[cluster]) ;
// invert all the covariance matrices
MatrixFree(&m1) ;
singular = 0 ;
for (cluster = 0 ; cluster < k ; cluster++) {
m1 = MatrixInverse(m_covs[cluster], NULL) ;
cno = MatrixConditionNumber(m_covs[cluster]) ;
det = MatrixDeterminant(m_covs[cluster]) ;
if (m1 == NULL)
singular++ ;
while (cno > 100*cno_pooled || 100*det < det_pooled) {
if (m1)
MatrixFree(&m1) ;
m1 = MatrixScalarMul(mpooled, 0.1, NULL) ;
MatrixAdd(m_covs[cluster], m1, m_covs[cluster]) ;
MatrixFree(&m1) ;
cno = MatrixConditionNumber(m_covs[cluster]) ;
m1 = MatrixInverse(m_covs[cluster], NULL) ;
det = MatrixDeterminant(m_covs[cluster]) ;
}
m_inv_covs[cluster] = m1 ;
}
for (cluster = 0 ; cluster < k ; cluster++) {
if (m_inv_covs[cluster] == NULL)
DiagBreak() ;
else {
MatrixFree(&m_covs[cluster]) ;
m_covs[cluster] = m_inv_covs[cluster] ;
// MatrixIdentity(m_covs[cluster]->rows, m_covs[cluster]);
}
}
MatrixFree(&mpooled) ;
VectorFree(&v1) ;
return(NO_ERROR) ;
}
int
main(int argc, char *argv[]) {
char **av, *cp ;
int ac, nargs, i, dof, no_transform, which, sno = 0, nsubjects = 0 ;
MRI *mri=0, *mri_mean = NULL, *mri_std=0, *mri_T1=0,*mri_binary=0,*mri_dof=NULL,
*mri_priors = NULL ;
char *subject_name, *out_fname, fname[STRLEN] ;
/* LTA *lta;*/
MRI *mri_tmp=0 ;
/* rkt: check for and handle version tag */
nargs = handle_version_option (argc, argv, "$Id: mri_make_template.c,v 1.26 2011/03/02 00:04:22 nicks Exp $", "$Name: stable5 $");
if (nargs && argc - nargs == 1)
exit (0);
argc -= nargs;
Progname = argv[0] ;
ErrorInit(NULL, NULL, NULL) ;
DiagInit(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 (!strlen(subjects_dir)) {
cp = getenv("SUBJECTS_DIR") ;
if (!cp)
ErrorExit(ERROR_BADPARM,"%s: SUBJECTS_DIR not defined in environment.\n",
Progname) ;
strcpy(subjects_dir, cp) ;
}
if (argc < 3) usage_exit(1) ;
out_fname = argv[argc-1] ;
no_transform = first_transform ;
if (binary_name) /* generate binarized volume with priors and */
{ /* separate means and variances */
for (which = BUILD_PRIORS ; which <= OFF_STATS ; which++) {
/* for each subject specified on cmd line */
for (dof = 0, i = 1 ; i < argc-1 ; i++) {
if (*argv[i] == '-') /* don't do transform for next subject */
{ no_transform = 1 ;
continue ;
}
dof++ ;
subject_name = argv[i] ;
if (which != BUILD_PRIORS) {
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, T1_name);
fprintf(stderr, "%d of %d: reading %s...\n", i, argc-2, fname) ;
mri_T1 = MRIread(fname) ;
if (!mri_T1)
ErrorExit(ERROR_NOFILE,"%s: could not open volume %s",
Progname,fname);
}
sprintf(fname, "%s/%s/mri/%s",subjects_dir,subject_name,binary_name);
fprintf(stderr, "%d of %d: reading %s...\n", i, argc-2, fname) ;
mri_binary = MRIread(fname) ;
if (!mri_binary)
ErrorExit(ERROR_NOFILE,"%s: could not open volume %s",
Progname,fname);
/* only count voxels which are mostly labeled */
MRIbinarize(mri_binary, mri_binary, WM_MIN_VAL, 0, 100) ;
if (transform_fname && no_transform-- <= 0) {
sprintf(fname, "%s/%s/mri/transforms/%s",
subjects_dir, subject_name, transform_fname) ;
fprintf(stderr, "reading transform %s...\n", fname) ;
////////////////////////////////////////////////////////
#if 1
{
TRANSFORM *transform ;
transform = TransformRead(fname) ;
if (transform == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not open transform file %s\n",Progname, fname) ;
mri_tmp = TransformApply(transform, mri_T1, NULL) ;
TransformFree(&transform) ;
}
#else
lta = LTAreadEx(fname);
if (lta == NULL)
ErrorExit(ERROR_NOFILE,
"%s: could not open transform file %s\n",
Progname, fname) ;
/* LTAtransform() runs either MRIapplyRASlinearTransform()
for RAS2RAS or MRIlinearTransform() for Vox2Vox. */
/* MRIlinearTransform() calls MRIlinearTransformInterp() */
mri_tmp = LTAtransform(mri_T1, NULL, lta);
MRIfree(&mri_T1) ;
mri_T1 = mri_tmp ;
LTAfree(<a);
lta = NULL;
#endif
if (DIAG_VERBOSE_ON)
fprintf(stderr, "transform application complete.\n") ;
}
if (which == BUILD_PRIORS) {
mri_priors =
MRIupdatePriors(mri_binary, mri_priors) ;
} else {
if (!mri_mean) {
mri_dof = MRIalloc(mri_T1->width, mri_T1->height, mri_T1->depth,
MRI_UCHAR) ;
mri_mean =
MRIalloc(mri_T1->width, mri_T1->height,mri_T1->depth,MRI_FLOAT);
mri_std =
MRIalloc(mri_T1->width,mri_T1->height,mri_T1->depth,MRI_FLOAT);
if (!mri_mean || !mri_std)
ErrorExit(ERROR_NOMEMORY, "%s: could not allocate templates.\n",
Progname) ;
}
if (DIAG_VERBOSE_ON)
fprintf(stderr, "updating mean and variance estimates...\n") ;
if (which == ON_STATS) {
MRIaccumulateMaskedMeansAndVariances(mri_T1, mri_binary, mri_dof,
90, 100, mri_mean, mri_std) ;
fprintf(stderr, "T1 = %d, binary = %d, mean = %2.1f\n",
(int)MRIgetVoxVal(mri_T1, 141,100,127,0),
MRIvox(mri_binary, 141,100,127),
MRIFvox(mri_mean, 141,100,127)) ;
} else /* computing means and vars for off */
MRIaccumulateMaskedMeansAndVariances(mri_T1, mri_binary, mri_dof,
0, WM_MIN_VAL-1,
mri_mean, mri_std) ;
MRIfree(&mri_T1) ;
}
MRIfree(&mri_binary) ;
}
if (which == BUILD_PRIORS) {
mri = MRIcomputePriors(mri_priors, dof, NULL) ;
MRIfree(&mri_priors) ;
fprintf(stderr, "writing priors to %s...\n", out_fname) ;
} else {
MRIcomputeMaskedMeansAndStds(mri_mean, mri_std, mri_dof) ;
mri_mean->dof = dof ;
fprintf(stderr, "writing T1 means with %d dof to %s...\n", mri_mean->dof,
out_fname) ;
if (!which)
MRIwrite(mri_mean, out_fname) ;
else
MRIappend(mri_mean, out_fname) ;
MRIfree(&mri_mean) ;
fprintf(stderr, "writing T1 variances to %s...\n", out_fname);
if (dof <= 1)
MRIreplaceValues(mri_std, mri_std, 0, 1) ;
mri = mri_std ;
}
if (!which)
MRIwrite(mri, out_fname) ;
else
MRIappend(mri, out_fname) ;
MRIfree(&mri) ;
}
}
else {
/* for each subject specified on cmd line */
if (xform_mean_fname) {
m_xform_mean = MatrixAlloc(4,4,MATRIX_REAL) ;
/* m_xform_covariance = MatrixAlloc(12,12,MATRIX_REAL) ;*/
}
dof = 0;
for (i = 1 ; i < argc-1 ; i++) {
if (*argv[i] == '-') {
/* don't do transform for next subject */
no_transform = 1 ;
continue ;
}
dof++ ;
subject_name = argv[i] ;
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, T1_name);
fprintf(stderr, "%d of %d: reading %s...\n", i, argc-2, fname) ;
mri_T1 = MRIread(fname) ;
if (!mri_T1)
ErrorExit(ERROR_NOFILE,"%s: could not open volume %s",Progname,fname);
check_mri(mri_T1) ;
if (binarize)
MRIbinarize(mri_T1, mri_T1, binarize, 0, 1) ;
if (erode) {
int i ;
printf("eroding input %d times\n", erode) ;
for (i = 0 ; i < erode ; i++)
MRIerode(mri_T1, mri_T1) ;
}
if (open) {
int i ;
printf("opening input %d times\n", open) ;
for (i = 0 ; i < open ; i++)
MRIerode(mri_T1, mri_T1) ;
for (i = 0 ; i < open ; i++)
MRIdilate(mri_T1, mri_T1) ;
}
check_mri(mri_T1) ;
if (transform_fname) {
sprintf(fname, "%s/%s/mri/transforms/%s",
subjects_dir, subject_name, transform_fname) ;
fprintf(stderr, "reading transform %s...\n", fname) ;
////////////////////////////////////////////////////////
#if 1
{
TRANSFORM *transform ;
transform = TransformRead(fname) ;
if (transform == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not open transform file %s\n",Progname, fname) ;
mri_tmp = TransformApply(transform, mri_T1, NULL) ;
if (DIAG_VERBOSE_ON)
MRIwrite(mri_tmp, "t1.mgz") ;
TransformFree(&transform) ;
}
#else
lta = LTAreadEx(fname);
if (lta == NULL)
ErrorExit(ERROR_NOFILE,
"%s: could not open transform file %s\n",
Progname, fname) ;
printf("transform matrix -----------------------\n");
MatrixPrint(stdout,lta->xforms[0].m_L);
/* LTAtransform() runs either MRIapplyRASlinearTransform()
for RAS2RAS or MRIlinearTransform() for Vox2Vox. */
/* MRIlinearTransform() calls MRIlinearTransformInterp() */
mri_tmp = LTAtransform(mri_T1, NULL, lta);
printf("----- -----------------------\n");
LTAfree(<a);
#endif
MRIfree(&mri_T1);
mri_T1 = mri_tmp ; // reassign pointers
if (DIAG_VERBOSE_ON)
fprintf(stderr, "transform application complete.\n") ;
}
if (!mri_mean) {
mri_mean =
MRIalloc(mri_T1->width, mri_T1->height, mri_T1->depth, MRI_FLOAT) ;
mri_std =
MRIalloc(mri_T1->width, mri_T1->height, mri_T1->depth, MRI_FLOAT) ;
if (!mri_mean || !mri_std)
ErrorExit(ERROR_NOMEMORY, "%s: could not allocate templates.\n",
Progname) ;
// if(transform_fname == NULL){
if (DIAG_VERBOSE_ON)
printf("Copying geometry\n");
MRIcopyHeader(mri_T1,mri_mean);
MRIcopyHeader(mri_T1,mri_std);
// }
}
check_mri(mri_mean) ;
if (!stats_only) {
if (DIAG_VERBOSE_ON)
fprintf(stderr, "updating mean and variance estimates...\n") ;
MRIaccumulateMeansAndVariances(mri_T1, mri_mean, mri_std) ;
}
check_mri(mri_mean) ;
if (DIAG_VERBOSE_ON)
MRIwrite(mri_mean, "t2.mgz") ;
MRIfree(&mri_T1) ;
no_transform = 0;
} /* end loop over subjects */
if (xform_mean_fname) {
FILE *fp ;
VECTOR *v = NULL, *vT = NULL ;
MATRIX *m_vvT = NULL ;
int rows, cols ;
nsubjects = sno ;
fp = fopen(xform_covariance_fname, "w") ;
if (!fp)
ErrorExit(ERROR_NOFILE, "%s: could not open covariance file %s",
Progname, xform_covariance_fname) ;
fprintf(fp, "nsubjects=%d\n", nsubjects) ;
MatrixScalarMul(m_xform_mean, 1.0/(double)nsubjects, m_xform_mean) ;
printf("means:\n") ;
MatrixPrint(stdout, m_xform_mean) ;
MatrixAsciiWrite(xform_mean_fname, m_xform_mean) ;
/* subtract the mean from each transform */
rows = m_xform_mean->rows ;
cols = m_xform_mean->cols ;
for (sno = 0 ; sno < nsubjects ; sno++) {
MatrixSubtract(m_xforms[sno], m_xform_mean, m_xforms[sno]) ;
v = MatrixReshape(m_xforms[sno], v, rows*cols, 1) ;
vT = MatrixTranspose(v, vT) ;
m_vvT = MatrixMultiply(v, vT, m_vvT) ;
if (!m_xform_covariance)
m_xform_covariance =
MatrixAlloc(m_vvT->rows, m_vvT->cols,MATRIX_REAL) ;
MatrixAdd(m_vvT, m_xform_covariance, m_xform_covariance) ;
MatrixAsciiWriteInto(fp, m_xforms[sno]) ;
}
MatrixScalarMul(m_xform_covariance, 1.0/(double)nsubjects,
m_xform_covariance) ;
printf("covariance:\n") ;
MatrixPrint(stdout, m_xform_covariance) ;
MatrixAsciiWriteInto(fp, m_xform_covariance) ;
fclose(fp) ;
if (stats_only)
exit(0) ;
}
MRIcomputeMeansAndStds(mri_mean, mri_std, dof) ;
check_mri(mri_mean) ;
check_mri(mri_std) ;
mri_mean->dof = dof ;
if (smooth) {
MRI *mri_kernel, *mri_smooth ;
printf("applying smoothing kernel\n") ;
mri_kernel = MRIgaussian1d(smooth, 100) ;
mri_smooth = MRIconvolveGaussian(mri_mean, NULL, mri_kernel) ;
MRIfree(&mri_kernel) ;
MRIfree(&mri_mean) ;
mri_mean = mri_smooth ;
}
fprintf(stderr, "\nwriting T1 means with %d dof to %s...\n", mri_mean->dof,
out_fname) ;
MRIwrite(mri_mean, out_fname) ;
MRIfree(&mri_mean) ;
if (dof <= 1) /* can't calculate variances - set them to reasonable val */
{
// src dst
MRIreplaceValues(mri_std, mri_std, 0, 1) ;
}
if (!novar) {
// mri_std contains the variance here (does it?? I don't think so -- BRF)
if (!var_fname) {
fprintf(stderr, "\nwriting T1 standard deviations to %s...\n", out_fname);
MRIappend(mri_std, out_fname) ;
} else {
fprintf(stderr, "\nwriting T1 standard deviations to %s...\n", var_fname);
MRIwrite(mri_std, var_fname) ;
}
}
MRIfree(&mri_std) ;
if (mri)
MRIfree(&mri);
} /* end if binarize */
return(0) ;
}
