MRI.setGrid(grid2D)
BFI.setGrid(grid2D)
MRI /= ca.Max(MRI)
BFI_VE = ca.Image3D(grid2D, BFI.memType())
MRI_VE = ca.Image3D(grid2D, MRI.memType())
ca.Copy(MRI_VE, MRI)
ca.Copy(BFI_VE, BFI)
cc.SetRegionLTE(MRI_VE, MRI, 0.13, 1)
MRI_VE *= -1
square = ca.Image3D(grid2D, BFI.memType())
cc.CreateRect(square, [0, 0], [440, 440])
BFI_VE *= square
cc.VarianceEqualize_I(BFI_VE, sigma=5.0)
cc.VarianceEqualize_I(MRI_VE, sigma=5.0)
grid_orig = BFI_VE.grid().copy()
grid_new = cc.MakeGrid(grid_orig.size(), [1, 1, 1], 'center')
BFI_VE.setGrid(grid_new)
MRI_VE.setGrid(grid_new)
BFI_VE_def = ca.Image3D(grid_new, BFI_VE.memType())
# do rigid reg first
# A = AffineReg(BFI_VE, MRI_VE, constraint='rigid', plot=debug)
A = AffineReg(BFI_VE, MRI_VE, plot=debug, maxIter=400, verbose=0)[1]
cc.ApplyAffineReal(BFI_VE_def, BFI_VE, A)
# cd.DispImage(BFI_VE_def)
# cd.DispImage(MRI_VE)
# hA = ca.Field3D(BFI_VE.grid(), BFI_VE.memType())
def main():
# Extract the Monkey number and section number from the command line
global frgNum
global secOb
mkyNum = sys.argv[1]
secNum = sys.argv[2]
frgNum = int(sys.argv[3])
write = True
# if not os.path.exists(os.path.expanduser('~/korenbergNAS/3D_database/Working/configuration_files/SidescapeRelateBlockface/M{0}/section_{1}/include_configFile.yaml'.format(mkyNum,secNum))):
# cf = initial(secNum, mkyNum)
try:
secOb = Config.Load(
secSpec,
pth.expanduser(
'~/korenbergNAS/3D_database/Working/configuration_files/SidescapeRelateBlockface/M{0}/section_{1}/include_configFile.yaml'
.format(mkyNum, secNum)))
except IOError as e:
try:
temp = Config.LoadYAMLDict(pth.expanduser(
'~/korenbergNAS/3D_database/Working/configuration_files/SidescapeRelateBlockface/M{0}/section_{1}/include_configFile.yaml'
.format(mkyNum, secNum)),
include=False)
secOb = Config.MkConfig(temp, secSpec)
except IOError:
print 'It appears there is no configuration file for this section. Please initialize one and restart.'
sys.exit()
if frgNum == int(secOb.yamlList[frgNum][-6]):
Fragmenter()
try:
secOb = Config.Load(
secSpec,
pth.expanduser(
'~/korenbergNAS/3D_database/Working/configuration_files/SidescapeRelateBlockface/M{0}/section_{1}/include_configFile.yaml'
.format(mkyNum, secNum)))
except IOError:
print 'It appeas that the include yaml file list does not match your fragmentation number. Please check them and restart.'
sys.exit()
if not pth.exists(
pth.expanduser(secOb.ssiOutPath + 'frag{0}'.format(frgNum))):
common.Mkdir_p(
pth.expanduser(secOb.ssiOutPath + 'frag{0}'.format(frgNum)))
if not pth.exists(
pth.expanduser(secOb.bfiOutPath + 'frag{0}'.format(frgNum))):
common.Mkdir_p(
pth.expanduser(secOb.bfiOutPath + 'frag{0}'.format(frgNum)))
if not pth.exists(
pth.expanduser(secOb.ssiSrcPath + 'frag{0}'.format(frgNum))):
os.mkdir(pth.expanduser(secOb.ssiSrcPath + 'frag{0}'.format(frgNum)))
if not pth.exists(
pth.expanduser(secOb.bfiSrcPath + 'frag{0}'.format(frgNum))):
os.mkdir(pth.expanduser(secOb.bfiSrcPath + 'frag{0}'.format(frgNum)))
frgOb = Config.MkConfig(secOb.yamlList[frgNum], frgSpec)
ssiSrc, bfiSrc, ssiMsk, bfiMsk = Loader(frgOb, ca.MEM_HOST)
#Extract the saturation Image from the color iamge
bfiHsv = common.FieldFromNPArr(
matplotlib.colors.rgb_to_hsv(
np.rollaxis(np.array(np.squeeze(bfiSrc.asnp())), 0, 3)),
ca.MEM_HOST)
bfiHsv.setGrid(bfiSrc.grid())
bfiSat = ca.Image3D(bfiSrc.grid(), bfiHsv.memType())
ca.Copy(bfiSat, bfiHsv, 1)
#Histogram equalize, normalize and mask the blockface saturation image
bfiSat = cb.HistogramEqualize(bfiSat, 256)
bfiSat.setGrid(bfiSrc.grid())
bfiSat *= -1
bfiSat -= ca.Min(bfiSat)
bfiSat /= ca.Max(bfiSat)
bfiSat *= bfiMsk
bfiSat.setGrid(bfiSrc.grid())
#Write out the blockface region after adjusting the colors with a format that supports header information
if write:
common.SaveITKImage(
bfiSat,
pth.expanduser(secOb.bfiSrcPath +
'frag{0}/M{1}_01_bfi_section_{2}_frag{0}_sat.nrrd'.
format(frgNum, secOb.mkyNum, secOb.secNum)))
#Set the sidescape grid relative to that of the blockface
ssiSrc.setGrid(ConvertGrid(ssiSrc.grid(), bfiSat.grid()))
ssiMsk.setGrid(ConvertGrid(ssiMsk.grid(), bfiSat.grid()))
ssiSrc *= ssiMsk
#Write out the sidescape masked image in a format that stores the header information
if write:
common.SaveITKImage(
ssiSrc,
pth.expanduser(secOb.ssiSrcPath +
'frag{0}/M{1}_01_ssi_section_{2}_frag{0}.nrrd'.
format(frgNum, secOb.mkyNum, secOb.secNum)))
#Update the image parameters of the sidescape image for future use
frgOb.imSize = ssiSrc.size().tolist()
frgOb.imOrig = ssiSrc.origin().tolist()
frgOb.imSpac = ssiSrc.spacing().tolist()
updateFragOb(frgOb)
#Find the affine transform between the two fragments
bfiAff, ssiAff, aff = Affine(bfiSat, ssiSrc, frgOb)
updateFragOb(frgOb)
#Write out the affine transformed images in a format that stores header information
if write:
common.SaveITKImage(
bfiAff,
pth.expanduser(
secOb.bfiOutPath +
'frag{0}/M{1}_01_bfi_section_{2}_frag{0}_aff_ssi.nrrd'.format(
frgNum, secOb.mkyNum, secOb.secNum)))
common.SaveITKImage(
ssiAff,
pth.expanduser(
secOb.ssiOutPath +
'frag{0}/M{1}_01_ssi_section_{2}_frag{0}_aff_bfi.nrrd'.format(
frgNum, secOb.mkyNum, secOb.secNum)))
bfiVe = bfiAff.copy()
ssiVe = ssiSrc.copy()
cc.VarianceEqualize_I(bfiVe, sigma=frgOb.sigVarBfi, eps=frgOb.epsVar)
cc.VarianceEqualize_I(ssiVe, sigma=frgOb.sigVarSsi, eps=frgOb.epsVar)
#As of right now, the largest pre-computed FFT table is 2048, so resample onto that grid for registration
regGrd = ConvertGrid(
cc.MakeGrid(ca.Vec3Di(2048, 2048, 1), ca.Vec3Df(1, 1, 1),
ca.Vec3Df(0, 0, 0)), ssiSrc.grid())
ssiReg = ca.Image3D(regGrd, ca.MEM_HOST)
bfiReg = ca.Image3D(regGrd, ca.MEM_HOST)
cc.ResampleWorld(ssiReg, ssiVe)
cc.ResampleWorld(bfiReg, bfiVe)
#Create the default configuration object for IDiff Matching and then set some parameters
idCf = Config.SpecToConfig(IDiff.Matching.MatchingConfigSpec)
idCf.compute.useCUDA = True
idCf.io.outputPrefix = '/home/sci/blakez/IDtest/'
#Run the registration
ssiDef, phi = DefReg(ssiReg, bfiReg, frgOb, ca.MEM_DEVICE, idCf)
#Turn the deformation into a displacement field so it can be applied to the large tif with C++ code
affV = phi.copy()
cc.ApplyAffineReal(affV, phi, np.linalg.inv(frgOb.affine))
ca.HtoV_I(affV)
#Apply the found deformation to the input ssi
ssiSrc.toType(ca.MEM_DEVICE)
cc.HtoReal(phi)
affPhi = phi.copy()
ssiBfi = ssiSrc.copy()
upPhi = ca.Field3D(ssiSrc.grid(), phi.memType())
cc.ApplyAffineReal(affPhi, phi, np.linalg.inv(frgOb.affine))
cc.ResampleWorld(upPhi, affPhi, bg=2)
cc.ApplyHReal(ssiBfi, ssiSrc, upPhi)
# ssiPhi = ca.Image3D(ssiSrc.grid(), phi.memType())
# upPhi = ca.Field3D(ssiSrc.grid(), phi.memType())
# cc.ResampleWorld(upPhi, phi, bg=2)
# cc.ApplyHReal(ssiPhi, ssiSrc, upPhi)
# ssiBfi = ssiSrc.copy()
# cc.ApplyAffineReal(ssiBfi, ssiPhi, np.linalg.inv(frgOb.affine))
# #Apply affine to the deformation
# affPhi = phi.copy()
# cc.ApplyAffineReal(affPhi, phi, np.linalg.inv(frgOb.affine))
if write:
common.SaveITKImage(
ssiBfi,
pth.expanduser(
secOb.ssiOutPath +
'frag{0}/M{1}_01_ssi_section_{2}_frag{0}_def_bfi.nrrd'.format(
frgNum, secOb.mkyNum, secOb.secNum)))
cc.WriteMHA(
affPhi,
pth.expanduser(
secOb.ssiOutPath +
'frag{0}/M{1}_01_ssi_section_{2}_frag{0}_to_bfi_real.mha'.
format(frgNum, secOb.mkyNum, secOb.secNum)))
cc.WriteMHA(
affV,
pth.expanduser(
secOb.ssiOutPath +
'frag{0}/M{1}_01_ssi_section_{2}_frag{0}_to_bfi_disp.mha'.
format(frgNum, secOb.mkyNum, secOb.secNum)))
#Create the list of names that the deformation should be applied to
# nameList = ['M15_01_0956_SideLight_DimLED_10x_ORG.tif',
# 'M15_01_0956_TyrosineHydroxylase_Ben_10x_Stitching_c1_ORG.tif',
# 'M15_01_0956_TyrosineHydroxylase_Ben_10x_Stitching_c2_ORG.tif',
# 'M15_01_0956_TyrosineHydroxylase_Ben_10x_Stitching_c3_ORG.tif']
# appLarge(nameList, affPhi)
common.DebugHere()
# realLM[:,1] = realLM[:,1] - 127.5
# flipLM = np.fliplr(realLM)
# # Solve for the TPS based off of the landmakrs
# spline = SolveSpline(flipLM)
# h = SplineToHField(spline, T2Grid, memT)
# print ca.MinMax(h)
# liveDef = T2.copy()
# cc.ApplyHReal(liveDef,live,h)
# Variance equalize the volumes and blur the live
T2_VE = ca.Image3D(T2.grid(), memT)
live_VE = ca.Image3D(liveDef.grid(), memT)
ca.Copy(T2_VE, T2)
cc.VarianceEqualize_I(T2_VE, sigma=5)
ca.Copy(live_VE, liveDef)
cc.VarianceEqualize_I(live_VE, sigma=5)
gausfilt = ca.GaussianFilterGPU()
gausfilt.updateParams(live_VE.size(), ca.Vec3Df(3, 3, 3), ca.Vec3Di(3, 3, 3))
live_VEfilt = ca.Image3D(live_VE.grid(), memT)
temp = ca.Image3D(live_VE.grid(), memT)
gausfilt.filter(live_VEfilt, live_VE, temp)
dispslice = [128, 120, 128]
# Display some initial images
cd.Disp3Pane(live_VEfilt,
rng=[-3, 3],
sliceIdx=dispslice,
title='Live VE Filtered')
cd.Disp3Pane(T2_VE, rng=[-3, 3], sliceIdx=dispslice, title='T2 VE')
spline = apps.SolveSpline(landmarks)
h = apps.SplineToHField(spline, M13_aff.grid(), memT)
def_TPS = ca.Image3D(M13_aff.grid(), memT)
cc.ApplyHReal(def_TPS, def_aff, h)
if write:
cc.WriteMHA(def_TPS, M15dir + 'TPS/M15_01_TPS_to_M13.mha')
cc.WriteMHA(h, M15dir + 'TPS/M15_01_TPS_Field_to_M13.mha')
del def_aff, h
gc.collect()
M13_aff /= ca.Max(M13_aff)
def_TPS /= ca.Max(def_TPS)
cc.VarianceEqualize_I(M13_aff, sigma=2, eps=0.01)
cc.VarianceEqualize_I(def_TPS, sigma=7, eps=0.1)
eps = 0.02
sigma_I = 0.09
nIter_I = 200
[def_ID, theta, energy] = apps.IDiff(def_TPS,
M13_aff,
eps,
sigma_I,
nIter_I,
plot=True,
verbose=1)
if write:
cc.WriteMHA(def_ID, M15dir + 'IDiff/M15_01_ID_to_M13.mha')