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)