def testEstimateMultimodalSyN3DMultiScale(fnameMoving, fnameFixed, fnameAffine, warpDir, lambdaParam):
'''
testEstimateMultimodalDiffeomorphicField3DMultiScale('IBSR_01_ana_strip.nii.gz', 't1_icbm_normal_1mm_pn0_rf0_peeled.nii.gz', 'IBSR_01_ana_strip_t1_icbm_normal_1mm_pn0_rf0_peeledAffine.txt', 100)
'''
print 'Registering', fnameMoving, 'to', fnameFixed,'with lambda=',lambdaParam
sys.stdout.flush()
moving = nib.load(fnameMoving)
fixed= nib.load(fnameFixed)
referenceShape=np.array(fixed.shape, dtype=np.int32)
M=moving.get_affine()
F=fixed.get_affine()
if not fnameAffine:
T=np.eye(4)
else:
T=rcommon.readAntsAffine(fnameAffine)
initAffine=np.linalg.inv(M).dot(T.dot(F))
print initAffine
moving=moving.get_data().squeeze().astype(np.float64)
fixed=fixed.get_data().squeeze().astype(np.float64)
moving=np.copy(moving, order='C')
fixed=np.copy(fixed, order='C')
moving=(moving-moving.min())/(moving.max()-moving.min())
fixed=(fixed-fixed.min())/(fixed.max()-fixed.min())
level=2
maskMoving=moving>0
maskFixed=fixed>0
movingPyramid=[img for img in rcommon.pyramid_gaussian_3D(moving, level, maskMoving)]
fixedPyramid=[img for img in rcommon.pyramid_gaussian_3D(fixed, level, maskFixed)]
#maxOuterIter=[25,50,100,100, 100, 100]
maxOuterIter=[2,2,2,2,2,2]
baseMoving=rcommon.getBaseFileName(fnameMoving)
baseFixed=rcommon.getBaseFileName(fnameFixed)
# if(os.path.exists('disp_'+baseMoving+'_'+baseFixed+'.npy')):
# displacement=np.load('disp_'+baseMoving+'_'+baseFixed+'.npy')
# else:
displacement, directInverse=estimateMultimodalSyN3DMultiScale(movingPyramid, fixedPyramid, initAffine, lambdaParam, maxOuterIter, 0)
tf.prepend_affine_to_displacement_field(displacement, initAffine)
# np.save('disp_'+baseMoving+'_'+baseFixed+'.npy', displacement)
#####Warp all requested volumes
#---first the target using tri-linear interpolation---
moving=nib.load(fnameMoving).get_data().squeeze().astype(np.float64)
moving=np.copy(moving, order='C')
warped=np.array(tf.warp_volume(moving, displacement)).astype(np.int16)
imgWarped=nib.Nifti1Image(warped, F)
imgWarped.to_filename('warpedDiff_'+baseMoving+'_'+baseFixed+'.nii.gz')
#---warp using affine only
moving=nib.load(fnameMoving).get_data().squeeze().astype(np.int32)
moving=np.copy(moving, order='C')
warped=np.array(tf.warp_discrete_volumeNNAffine(moving, referenceShape, initAffine)).astype(np.int16)
imgWarped=nib.Nifti1Image(warped, F)#The affine transformation is the reference's one
imgWarped.to_filename('warpedAffine_'+baseMoving+'_'+baseFixed+'.nii.gz')
#---now the rest of the targets using nearest neighbor
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).get_data().squeeze().astype(np.int32)
toWarp=np.copy(toWarp, order='C')
baseWarp=rcommon.getBaseFileName(name)
warped=np.array(tf.warp_discrete_volumeNN(toWarp, displacement)).astype(np.int16)
imgWarped=nib.Nifti1Image(warped, F)#The affine transformation is the reference's one
imgWarped.to_filename('warpedDiff_'+baseWarp+'_'+baseFixed+'.nii.gz')
#---warp using affine inly
warped=np.array(tf.warp_discrete_volumeNNAffine(toWarp, referenceShape, initAffine)).astype(np.int16)
imgWarped=nib.Nifti1Image(warped, F)#The affine transformation is the reference's one
imgWarped.to_filename('warpedAffine_'+baseWarp+'_'+baseFixed+'.nii.gz')
#---finally, the deformed lattices (forward, inverse and resdidual)---
lambdaParam=0.9
maxIter=100
tolerance=1e-4
print 'Computing inverse...'
inverse=np.array(tf.invert_vector_field3D(displacement, lambdaParam, maxIter, tolerance))
residual=np.array(tf.compose_vector_fields3D(displacement, inverse))
saveDeformedLattice3D(displacement, 'latticeDispDiff_'+baseMoving+'_'+baseFixed+'.nii.gz')
saveDeformedLattice3D(inverse, 'latticeInvDiff_'+baseMoving+'_'+baseFixed+'.nii.gz')
saveDeformedLattice3D(residual, 'latticeResdiff_'+baseMoving+'_'+baseFixed+'.nii.gz')
residual=np.sqrt(np.sum(residual**2,3))
print "Mean residual norm:", residual.mean()," (",residual.std(), "). Max residual norm:", residual.max()
def testEstimateMultimodalSyN3DMultiScale(fnameMoving, fnameFixed, fnameAffine,
warpDir, lambdaParam):
'''
testEstimateMultimodalDiffeomorphicField3DMultiScale('IBSR_01_ana_strip.nii.gz', 't1_icbm_normal_1mm_pn0_rf0_peeled.nii.gz', 'IBSR_01_ana_strip_t1_icbm_normal_1mm_pn0_rf0_peeledAffine.txt', 100)
'''
print 'Registering', fnameMoving, 'to', fnameFixed, 'with lambda=', lambdaParam
sys.stdout.flush()
moving = nib.load(fnameMoving)
fixed = nib.load(fnameFixed)
referenceShape = np.array(fixed.shape, dtype=np.int32)
M = moving.get_affine()
F = fixed.get_affine()
if not fnameAffine:
T = np.eye(4)
else:
T = rcommon.readAntsAffine(fnameAffine)
initAffine = np.linalg.inv(M).dot(T.dot(F))
print initAffine
moving = moving.get_data().squeeze().astype(np.float64)
fixed = fixed.get_data().squeeze().astype(np.float64)
moving = np.copy(moving, order='C')
fixed = np.copy(fixed, order='C')
moving = (moving - moving.min()) / (moving.max() - moving.min())
fixed = (fixed - fixed.min()) / (fixed.max() - fixed.min())
level = 2
maskMoving = moving > 0
maskFixed = fixed > 0
movingPyramid = [
img for img in rcommon.pyramid_gaussian_3D(moving, level, maskMoving)
]
fixedPyramid = [
img for img in rcommon.pyramid_gaussian_3D(fixed, level, maskFixed)
]
#maxOuterIter=[25,50,100,100, 100, 100]
maxOuterIter = [2, 2, 2, 2, 2, 2]
baseMoving = rcommon.getBaseFileName(fnameMoving)
baseFixed = rcommon.getBaseFileName(fnameFixed)
# if(os.path.exists('disp_'+baseMoving+'_'+baseFixed+'.npy')):
# displacement=np.load('disp_'+baseMoving+'_'+baseFixed+'.npy')
# else:
displacement, directInverse = estimateMultimodalSyN3DMultiScale(
movingPyramid, fixedPyramid, initAffine, lambdaParam, maxOuterIter, 0)
tf.prepend_affine_to_displacement_field(displacement, initAffine)
# np.save('disp_'+baseMoving+'_'+baseFixed+'.npy', displacement)
#####Warp all requested volumes
#---first the target using tri-linear interpolation---
moving = nib.load(fnameMoving).get_data().squeeze().astype(np.float64)
moving = np.copy(moving, order='C')
warped = np.array(tf.warp_volume(moving, displacement)).astype(np.int16)
imgWarped = nib.Nifti1Image(warped, F)
imgWarped.to_filename('warpedDiff_' + baseMoving + '_' + baseFixed +
'.nii.gz')
#---warp using affine only
moving = nib.load(fnameMoving).get_data().squeeze().astype(np.int32)
moving = np.copy(moving, order='C')
warped = np.array(
tf.warp_discrete_volumeNNAffine(moving, referenceShape,
initAffine)).astype(np.int16)
imgWarped = nib.Nifti1Image(
warped, F) #The affine transformation is the reference's one
imgWarped.to_filename('warpedAffine_' + baseMoving + '_' + baseFixed +
'.nii.gz')
#---now the rest of the targets using nearest neighbor
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).get_data().squeeze().astype(np.int32)
toWarp = np.copy(toWarp, order='C')
baseWarp = rcommon.getBaseFileName(name)
warped = np.array(tf.warp_discrete_volumeNN(
toWarp, displacement)).astype(np.int16)
imgWarped = nib.Nifti1Image(
warped, F) #The affine transformation is the reference's one
imgWarped.to_filename('warpedDiff_' + baseWarp + '_' + baseFixed +
'.nii.gz')
#---warp using affine inly
warped = np.array(
tf.warp_discrete_volumeNNAffine(toWarp, referenceShape,
initAffine)).astype(np.int16)
imgWarped = nib.Nifti1Image(
warped, F) #The affine transformation is the reference's one
imgWarped.to_filename('warpedAffine_' + baseWarp + '_' + baseFixed +
'.nii.gz')
#---finally, the deformed lattices (forward, inverse and resdidual)---
lambdaParam = 0.9
maxIter = 100
tolerance = 1e-4
print 'Computing inverse...'
inverse = np.array(
tf.invert_vector_field3D(displacement, lambdaParam, maxIter,
tolerance))
residual = np.array(tf.compose_vector_fields3D(displacement, inverse))
saveDeformedLattice3D(
displacement,
'latticeDispDiff_' + baseMoving + '_' + baseFixed + '.nii.gz')
saveDeformedLattice3D(
inverse, 'latticeInvDiff_' + baseMoving + '_' + baseFixed + '.nii.gz')
saveDeformedLattice3D(
residual, 'latticeResdiff_' + baseMoving + '_' + baseFixed + '.nii.gz')
residual = np.sqrt(np.sum(residual**2, 3))
print "Mean residual norm:", residual.mean(), " (", residual.std(
), "). Max residual norm:", residual.max()
if argc<3:
print 'Displacement-field file name expected.'
sys.exit(0)
dispName=sys.argv[2]
displacement=np.load(dispName)
lambdaParam=0.9
maxIter=100
tolerance=1e-4
if argc>3:
lambdaParam=float(sys.argv[3])
if argc>4:
maxIter=int(sys.argv[4])
if argc>5:
tolerance=float(sys.argv[5])
print 'Inverting displacement: ',dispName, '. With parameters: lambda=',lambdaParam, '. Maxiter=',maxIter, '. Tolerance=',tolerance,'...'
inverse=np.array(tf.invert_vector_field3D(displacement, lambdaParam, maxIter, tolerance))
invName="inv"+dispName
print 'Saving inverse as:', invName
np.save(invName, inverse)
print 'Computing inversion error...'
residual=np.array(tf.compose_vector_fields3D(displacement, inverse))
residualName="res"+dispName
print 'Saving residual as:', residualName
np.save(residualName, residual)
residual=np.sqrt(np.sum(residual**2,3))
print "Mean residual norm:", residual.mean()," (",residual.std(), "). Max residual norm:", residual.max()
sys.exit(0)
elif(sys.argv[1]=='npy2nifti'):
if argc<3:
print 'File name expected.'
sys.exit(0)
