similarity = params.similarity #'crl1' 'cc', 'mi', 'nmi', 'cr', 'slr'
interp = params.interp #'pv', 'tri',
renormalize = True
optimizer = 'powell'
print('Setting up registration...')
print 'Similarity:',similarity
tic = time.time()
R = HistogramRegistration(moving, static, similarity=similarity,
interp=interp, renormalize=renormalize)
T = R.optimize('affine', optimizer=optimizer)
toc = time.time()
print('Registration time: %f sec' % (toc - tic))
warpDir='warp'
names=[os.path.join(warpDir,name) for name in os.listdir(warpDir)]
for name in names:
#---warp using the non-linear deformation
toWarp=nib.load(name)
toWarp=nib.Nifti1Image(toWarp.get_data().squeeze(), toWarp.get_affine())
toWarp=nifti2nipy(toWarp)
#toWarp=np.copy(toWarp, order='C')
baseWarp=rcommon.getBaseFileName(name)
warped= resample(toWarp, T.inv(), reference=static, interp_order=0)
fmoved='warpedAffine_'+baseWarp+'_'+baseFixed+'.nii.gz'
nib.save(nipy2nifti(warped, strict=True), fmoved)
data = img.get_data()
data, mask = median_otsu(data)
affine = img.get_affine()
static_id = 0
moving_id = 20
static = nifti2nipy(nib.Nifti1Image(data[..., static_id], affine))
moving = nifti2nipy(nib.Nifti1Image(data[..., moving_id], affine))
similarity = 'crl1' # 'cc', 'mi', 'nmi', 'cr', 'slr'
interp = 'pv' # 'tri',
renormalize = True
optimizer = 'powell'
print('Setting up registration...')
tic = time.time()
R = HistogramRegistration(moving, static, similarity=similarity,
interp=interp, renormalize=renormalize)
T = R.optimize('affine', optimizer=optimizer)
toc = time.time()
print(' Registration time: %f sec' % (toc - tic))
moving_new = resample(moving, T.inv(), reference=static)
nib.save(nipy2nifti(static, strict=True), 'static.nii.gz')
nib.save(nipy2nifti(moving, strict=True), 'moving.nii.gz')
nib.save(nipy2nifti(moving_new, strict=True), 'moved.nii.gz')
if __name__ == '__main__':
fmoving = params.in_file
fstatic = params.reference
fmoved = params.out_file
print(fmoving + ' --> ' + fstatic)
static = nifti2nipy(nib.load(fstatic))
moving = nifti2nipy(nib.load(fmoving))
similarity = params.similarity #'crl1' 'cc', 'mi', 'nmi', 'cr', 'slr'
interp = params.interp #'pv', 'tri',
renormalize = True
optimizer = 'powell'
print('Setting up registration...')
tic = time.time()
R = HistogramRegistration(moving, static, similarity=similarity,
interp=interp, renormalize=renormalize)
T = R.optimize('affine', optimizer=optimizer)
toc = time.time()
print('Registration time: %f sec' % (toc - tic))
moving_new = resample(moving, T.inv(), reference=static)
nib.save(nipy2nifti(moving_new, strict=True), fmoved)
similarity = params.similarity #'crl1' 'cc', 'mi', 'nmi', 'cr', 'slr'
interp = params.interp #'pv', 'tri',
renormalize = True
optimizer = 'powell'
print('Setting up registration...')
print 'Similarity:', similarity
tic = time.time()
R = HistogramRegistration(moving,
static,
similarity=similarity,
interp=interp,
renormalize=renormalize)
T = R.optimize('affine', optimizer=optimizer)
toc = time.time()
print('Registration time: %f sec' % (toc - tic))
warpDir = 'warp'
names = [os.path.join(warpDir, name) for name in os.listdir(warpDir)]
for name in names:
#---warp using the non-linear deformation
toWarp = nib.load(name)
toWarp = nib.Nifti1Image(toWarp.get_data().squeeze(),
toWarp.get_affine())
toWarp = nifti2nipy(toWarp)
#toWarp=np.copy(toWarp, order='C')
baseWarp = rcommon.getBaseFileName(name)
warped = resample(toWarp, T.inv(), reference=static, interp_order=0)
fmoved = 'warpedAffine_' + baseWarp + '_' + baseFixed + '.nii.gz'
nib.save(nipy2nifti(warped, strict=True), fmoved)
