def testMultimodalRigidTransformationMultiScale3D_ecqmmf(betaGT, level):
leftName = 'data/t2/t2_icbm_normal_1mm_pn0_rf0.rawb'
rightName = 'data/t1/t1_icbm_normal_1mm_pn0_rf0.rawb'
#rightName='data/t2/t2_icbm_normal_1mm_pn0_rf0.rawb'
#leftName='data/t1/t1_icbm_normal_1mm_pn0_rf0.rawb'
betaGTRads = np.array(betaGT, dtype=np.float64)
betaGTRads[0:3] = np.copy(np.pi * betaGTRads[0:3] / 180.0)
ns = 181
nr = 217
nc = 181
print 'Loading volume...'
left = np.fromfile(leftName, dtype=np.ubyte).reshape(ns, nr, nc)
left = left.astype(np.float64)
print 'Generating pyramid at level', level, '...'
right = np.fromfile(rightName, dtype=np.ubyte).reshape(ns, nr, nc)
right = right.astype(np.float64)
right = rcommon.applyRigidTransformation3D(right, betaGTRads)
leftPyramid = [i for i in rcommon.pyramid_gaussian_3D(left, level)]
rightPyramid = [i for i in rcommon.pyramid_gaussian_3D(right, level)]
print 'Estimation started.'
beta = estimateMultiModalRigidTransformationMultiscale3D(
leftPyramid, rightPyramid)
print 'Estimation finished.'
print 'Ground truth:', betaGT
plotSlicePyramidsAxial(leftPyramid, rightPyramid)
return beta
def testMultimodalRigidTransformationMultiScale3D_ecqmmf(betaGT, level):
leftName='data/t2/t2_icbm_normal_1mm_pn0_rf0.rawb'
rightName='data/t1/t1_icbm_normal_1mm_pn0_rf0.rawb'
#rightName='data/t2/t2_icbm_normal_1mm_pn0_rf0.rawb'
#leftName='data/t1/t1_icbm_normal_1mm_pn0_rf0.rawb'
betaGTRads=np.array(betaGT, dtype=np.float64)
betaGTRads[0:3]=np.copy(np.pi*betaGTRads[0:3]/180.0)
ns=181
nr=217
nc=181
print 'Loading volume...'
left=np.fromfile(leftName, dtype=np.ubyte).reshape(ns,nr,nc)
left=left.astype(np.float64)
print 'Generating pyramid at level',level,'...'
right=np.fromfile(rightName, dtype=np.ubyte).reshape(ns,nr,nc)
right=right.astype(np.float64)
right=rcommon.applyRigidTransformation3D(right, betaGTRads)
leftPyramid=[i for i in rcommon.pyramid_gaussian_3D(left, level)]
rightPyramid=[i for i in rcommon.pyramid_gaussian_3D(right, level)]
print 'Estimation started.'
beta=estimateMultiModalRigidTransformationMultiscale3D(leftPyramid, rightPyramid)
print 'Estimation finished.'
print 'Ground truth:', betaGT
plotSlicePyramidsAxial(leftPyramid, rightPyramid)
return beta
def testEstimateMonomodalDiffeomorphicField3DMultiScale(lambdaParam):
fnameMoving = 'data/affineRegistered/templateT1ToIBSR01T1.nii.gz'
fnameFixed = 'data/t1/IBSR18/IBSR_01/IBSR_01_ana_strip.nii.gz'
moving = nib.load(fnameMoving)
fixed = nib.load(fnameFixed)
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 = 3
#maskMoving=np.ones_like(moving)
#maskFixed=np.ones_like(fixed)
movingPyramid = [
img for img in rcommon.pyramid_gaussian_3D(moving, level,
np.ones_like(moving))
]
fixedPyramid = [
img for img in rcommon.pyramid_gaussian_3D(fixed, level,
np.ones_like(fixed))
]
rcommon.plotOverlaidPyramids3DCoronal(movingPyramid, fixedPyramid)
#maxOuterIter=[100,100,100,100,100,100,100,100,100]
maxOuterIter = [3, 3, 3, 3, 3, 3, 3, 3, 3]
#maxOuterIter=[10,20,50,100, 100, 100]
displacement = estimateMonomodalDiffeomorphicField3DMultiScale(
movingPyramid, fixedPyramid, lambdaParam, maxOuterIter, 0, None)
warped = tf.warp_volume(movingPyramid[0], displacement)
np.save('displacement_templateT1ToIBSR01T1_diff.npy', displacement)
np.save('warped_templateT1ToIBSR01T1_diff.npy', warped)
def testRigidTransformationMultiScale3D(betaGT, level):
betaGTRads=np.array(betaGT, dtype=np.float64)
betaGTRads[0:3]=np.copy(np.pi*betaGTRads[0:3]/180.0)
ns=181
nr=217
nc=181
print 'Loading volume...'
inImg=np.fromfile('data/t2/t2_icbm_normal_1mm_pn0_rf0.rawb', dtype=np.ubyte).reshape(ns,nr,nc)
inImg=inImg.astype(np.float64)
print 'Generating pyramid at level',level,'...'
left=inImg
right=rcommon.applyRigidTransformation3D(inImg, betaGTRads)
leftPyramid=[i for i in rcommon.pyramid_gaussian_3D(left, level)]
rightPyramid=[i for i in rcommon.pyramid_gaussian_3D(right, level)]
plotSlicePyramidsAxial(leftPyramid, rightPyramid)
print 'Estimation started.'
beta=estimateRigidTransformationMultiscale3D(leftPyramid, rightPyramid)
print 'Estimation finished.'
print 'Ground truth:', betaGT
return beta
def testIntersubjectRigidRegistration(fname0, fname1, level, outfname):
nib_left = nib.load(fname0)
nib_right = nib.load(fname1)
left=nib_left.get_data().astype(np.double).squeeze()
right=nib_right.get_data().astype(np.double).squeeze()
leftPyramid=[i for i in rcommon.pyramid_gaussian_3D(left, level)]
rightPyramid=[i for i in rcommon.pyramid_gaussian_3D(right, level)]
plotSlicePyramidsAxial(leftPyramid, rightPyramid)
print 'Estimation started.'
beta=estimateRigidTransformationMultiscale3D(leftPyramid, rightPyramid)
print 'Estimation finished.'
rcommon.applyRigidTransformation3D(left, beta)
sl=np.array(left.shape)//2
sr=np.array(right.shape)//2
rcommon.overlayImages(left[sl[0],:,:], leftPyramid[0][sr[0],:,:])
rcommon.overlayImages(left[sl[0],:,:], right[sr[0],:,:])
affine_transform=AffineTransform('ijk', ['aligned-z=I->S','aligned-y=P->A', 'aligned-x=L->R'], np.eye(4))
left=Image(left, affine_transform)
nipy.save_image(left,outfname)
return beta
def testRigidTransformationMultiScale3D(betaGT, level):
betaGTRads = np.array(betaGT, dtype=np.float64)
betaGTRads[0:3] = np.copy(np.pi * betaGTRads[0:3] / 180.0)
ns = 181
nr = 217
nc = 181
print 'Loading volume...'
inImg = np.fromfile('data/t2/t2_icbm_normal_1mm_pn0_rf0.rawb',
dtype=np.ubyte).reshape(ns, nr, nc)
inImg = inImg.astype(np.float64)
print 'Generating pyramid at level', level, '...'
left = inImg
right = rcommon.applyRigidTransformation3D(inImg, betaGTRads)
leftPyramid = [i for i in rcommon.pyramid_gaussian_3D(left, level)]
rightPyramid = [i for i in rcommon.pyramid_gaussian_3D(right, level)]
plotSlicePyramidsAxial(leftPyramid, rightPyramid)
print 'Estimation started.'
beta = estimateRigidTransformationMultiscale3D(leftPyramid, rightPyramid)
print 'Estimation finished.'
print 'Ground truth:', betaGT
return beta
def testIntersubjectRigidRegistration(fname0, fname1, level, outfname):
nib_left = nib.load(fname0)
nib_right = nib.load(fname1)
left = nib_left.get_data().astype(np.double).squeeze()
right = nib_right.get_data().astype(np.double).squeeze()
leftPyramid = [i for i in rcommon.pyramid_gaussian_3D(left, level)]
rightPyramid = [i for i in rcommon.pyramid_gaussian_3D(right, level)]
plotSlicePyramidsAxial(leftPyramid, rightPyramid)
print 'Estimation started.'
beta = estimateRigidTransformationMultiscale3D(leftPyramid, rightPyramid)
print 'Estimation finished.'
rcommon.applyRigidTransformation3D(left, beta)
sl = np.array(left.shape) // 2
sr = np.array(right.shape) // 2
rcommon.overlayImages(left[sl[0], :, :], leftPyramid[0][sr[0], :, :])
rcommon.overlayImages(left[sl[0], :, :], right[sr[0], :, :])
affine_transform = AffineTransform(
'ijk', ['aligned-z=I->S', 'aligned-y=P->A', 'aligned-x=L->R'],
np.eye(4))
left = Image(left, affine_transform)
nipy.save_image(left, outfname)
return beta
def testEstimateMonomodalDiffeomorphicField3DMultiScale(lambdaParam):
fnameMoving='data/affineRegistered/templateT1ToIBSR01T1.nii.gz'
fnameFixed='data/t1/IBSR18/IBSR_01/IBSR_01_ana_strip.nii.gz'
moving = nib.load(fnameMoving)
fixed= nib.load(fnameFixed)
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=3
#maskMoving=np.ones_like(moving)
#maskFixed=np.ones_like(fixed)
movingPyramid=[img for img in rcommon.pyramid_gaussian_3D(moving, level, np.ones_like(moving))]
fixedPyramid=[img for img in rcommon.pyramid_gaussian_3D(fixed, level, np.ones_like(fixed))]
rcommon.plotOverlaidPyramids3DCoronal(movingPyramid, fixedPyramid)
#maxOuterIter=[100,100,100,100,100,100,100,100,100]
maxOuterIter=[3,3,3,3,3,3,3,3,3]
#maxOuterIter=[10,20,50,100, 100, 100]
displacement=estimateMonomodalDiffeomorphicField3DMultiScale(movingPyramid, fixedPyramid, lambdaParam, maxOuterIter, 0,None)
warped=tf.warp_volume(movingPyramid[0], displacement)
np.save('displacement_templateT1ToIBSR01T1_diff.npy', displacement)
np.save('warped_templateT1ToIBSR01T1_diff.npy', warped)
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()
