def calculateOpposingWeights(size, sigmoidHalfWidthRelativeToStackSize=0.05):
print 'calculating weights for opposing stacks fusion'
size = (size[0], size[1], size[2] + 2)
halfY = 0.9
nZPlanes = size[2]
sigmoidHalfWidthInPixels = nZPlanes * sigmoidHalfWidthRelativeToStackSize
halfY = 0.9 # half width is defined as the x value corresponding to y=halfY
sigmoidA = n.log(1. / halfY - 1.) / sigmoidHalfWidthInPixels
zs = n.linspace(0, size[2] - 1, size[2])
zsigmoid1 = n.abs(1 / (1 + n.exp(sigmoidA * (zs - size[2] / 2.))))
#zsigmoid2 = n.abs(1/(1+n.exp(sigmoidA*(-zs+size[2]/2.))))
zyplane = n.ones(size[1:])
zyplane1 = zyplane * zsigmoid1
#zyplane2 = zyplane*zsigmoid2
zyplane1 = zyplane1.astype(n.float32)
#zyplane2 = zyplane2.astype(n.float32)
w1 = (n.ones(size, dtype=n.uint16) * zyplane1).swapaxes(0, 1).swapaxes(
1, 2).swapaxes(0, 1)
#w2 = (n.ones(size,dtype=n.uint16)*zyplane2).swapaxes(0,1).swapaxes(1,2).swapaxes(0,1)
w1 = sitk.GetImageFromArray(w1)
w2 = beads.transformStack([1., 0, 0, 0, 1, 0, 0, 0, -1, 0, 0, size[2] - 2],
w1,
outShape=(size[0], size[1], size[2] - 2))
w1 = beads.transformStack([1., 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 2],
w1,
outShape=(size[0], size[1], size[2] - 2))
return [w1, w2]
def fuseStacks(s, weights, p=None):
if p != None:
for iis in range(len(s)):
s[iis] = beads.transformStack(p[iis],
s[iis],
outShape=s[0].GetSize())
# pdb.set_trace()
if weights is None:
print 'fusing stacks by averaging'
N = len(s)
tmp = sitk.Cast(s[0], 6) / N
for i in range(N - 1):
tmp += sitk.Cast(s[i + 1], 6) / N
return sitk.Cast(tmp, 3)
print 'fusing stacks by using weight matrices'
for iweight in range(len(weights)):
weights[iweight].SetSpacing(s[iweight].GetSpacing())
weights[iweight].SetOrigin(s[iweight].GetOrigin())
#for iweight in range(len(weights)):
#weights[iweight] = weights[iweight]*sitk.Cast(s[iweight],6)
result = weights[0] * sitk.Cast(s[0], 6)
for iweight in range(1, len(weights)):
result += weights[iweight] * sitk.Cast(s[iweight], 6)
result = sitk.Cast(result, 3)
return result
def fuseOpposingStacksOld(p1,p2,s1,s2,normalizeIntensities=True,axis=0):
print 'fusing (normalize intensities %s)' %(['OFF','ON'][int(normalizeIntensities)])
s1 = beads.transformStack(invertParams(p1),s1)
s2 = beads.transformStack(invertParams(p2),s2)
s1 = sitk.GetArrayFromImage(s1)
s2 = sitk.GetArrayFromImage(s2)
if normalizeIntensities:
n1,n2 = n.mean(s1),n.mean(s2)
else:
n1,n2 = 1.,1.
length = s1.shape[axis]
s1 = s1.swapaxes(0,axis)
s2 = s2.swapaxes(0,axis)
for z in range(length):
w1 = 1/(1+n.exp(-40./length*(z-length/2.)))
w2 = 1/(1+n.exp(40./length*(z-length/2.)))
s1[z,:,:] = (w1*s1[z,:,:]+w2*s2[z,:,:])/(w1+w2)
return sitk.GetImageFromArray(s1.swapaxes(0,axis))
def fuseOpposingStacksOld(p1, p2, s1, s2, normalizeIntensities=True, axis=0):
print 'fusing (normalize intensities %s)' % (['OFF', 'ON'
][int(normalizeIntensities)])
s1 = beads.transformStack(invertParams(p1), s1)
s2 = beads.transformStack(invertParams(p2), s2)
s1 = sitk.GetArrayFromImage(s1)
s2 = sitk.GetArrayFromImage(s2)
if normalizeIntensities:
n1, n2 = n.mean(s1), n.mean(s2)
else:
n1, n2 = 1., 1.
length = s1.shape[axis]
s1 = s1.swapaxes(0, axis)
s2 = s2.swapaxes(0, axis)
for z in range(length):
w1 = 1 / (1 + n.exp(-40. / length * (z - length / 2.)))
w2 = 1 / (1 + n.exp(40. / length * (z - length / 2.)))
s1[z, :, :] = (w1 * s1[z, :, :] + w2 * s2[z, :, :]) / (w1 + w2)
return sitk.GetImageFromArray(s1.swapaxes(0, axis))
def fuseOpposingStacks(p1, p2, s1, s2, axis=0):
s1 = beads.transformStack(invertParams(p1), s1)
s2 = beads.transformStack(invertParams(p2), s2)
size = s1.GetSize()
s1 = sitk.GetArrayFromImage(s1)
s2 = sitk.GetArrayFromImage(s2)
# halfY = 0.9
nZPlanes = size[2]
sigmoidHalfWidthInPixels = nZPlanes * 0.05
halfY = 0.9 # half width is defined as the x value corresponding to y=halfY
sigmoidA = n.log(1. / halfY - 1.) / sigmoidHalfWidthInPixels
length = s1.shape[axis]
s1 = s1.swapaxes(0, axis)
s2 = s2.swapaxes(0, axis)
for z in range(length):
w1 = n.abs(1 / (1 + n.exp(sigmoidA * (z - size[2] / 2.))))
w2 = n.abs(1 / (1 + n.exp(sigmoidA * (-z + size[2] / 2.))))
s1[z, :, :] = (w1 * s1[z, :, :] + w2 * s2[z, :, :]) / (w1 + w2)
return sitk.GetImageFromArray(s1.swapaxes(0, axis))
def fuseOpposingStacks(p1,p2,s1,s2,axis=0):
s1 = beads.transformStack(invertParams(p1),s1)
s2 = beads.transformStack(invertParams(p2),s2)
size = s1.GetSize()
s1 = sitk.GetArrayFromImage(s1)
s2 = sitk.GetArrayFromImage(s2)
# halfY = 0.9
nZPlanes = size[2]
sigmoidHalfWidthInPixels = nZPlanes*0.05
halfY = 0.9 # half width is defined as the x value corresponding to y=halfY
sigmoidA = n.log(1./halfY-1.)/sigmoidHalfWidthInPixels
length = s1.shape[axis]
s1 = s1.swapaxes(0,axis)
s2 = s2.swapaxes(0,axis)
for z in range(length):
w1 = n.abs(1/(1+n.exp(sigmoidA*(z-size[2]/2.))))
w2 = n.abs(1/(1+n.exp(sigmoidA*(-z+size[2]/2.))))
s1[z,:,:] = (w1*s1[z,:,:]+w2*s2[z,:,:])/(w1+w2)
return sitk.GetImageFromArray(s1.swapaxes(0,axis))
def calculateOpposingWeights(size,sigmoidHalfWidthRelativeToStackSize=0.05):
print 'calculating weights for opposing stacks fusion'
size = (size[0],size[1],size[2]+2)
halfY = 0.9
nZPlanes = size[2]
sigmoidHalfWidthInPixels = nZPlanes*sigmoidHalfWidthRelativeToStackSize
halfY = 0.9 # half width is defined as the x value corresponding to y=halfY
sigmoidA = n.log(1./halfY-1.)/sigmoidHalfWidthInPixels
zs = n.linspace(0,size[2]-1,size[2])
zsigmoid1 = n.abs(1/(1+n.exp(sigmoidA*(zs-size[2]/2.))))
#zsigmoid2 = n.abs(1/(1+n.exp(sigmoidA*(-zs+size[2]/2.))))
zyplane = n.ones(size[1:])
zyplane1 = zyplane*zsigmoid1
#zyplane2 = zyplane*zsigmoid2
zyplane1 = zyplane1.astype(n.float32)
#zyplane2 = zyplane2.astype(n.float32)
w1 = (n.ones(size,dtype=n.uint16)*zyplane1).swapaxes(0,1).swapaxes(1,2).swapaxes(0,1)
#w2 = (n.ones(size,dtype=n.uint16)*zyplane2).swapaxes(0,1).swapaxes(1,2).swapaxes(0,1)
w1 = sitk.GetImageFromArray(w1)
w2 = beads.transformStack([1.,0,0,0,1,0,0,0,-1,0,0,size[2]-2],w1,outShape=(size[0],size[1],size[2]-2))
w1 = beads.transformStack([1.,0,0,0,1,0,0,0,1,0,0,2],w1,outShape=(size[0],size[1],size[2]-2))
return [w1,w2]
def fuseStacks(s,weights,p=None):
if p != None:
for iis in range(len(s)):
s[iis] = beads.transformStack(p[iis],s[iis],outShape=s[0].GetSize())
# pdb.set_trace()
if weights is None:
print 'fusing stacks by averaging'
N = len(s)
tmp = sitk.Cast(s[0],6)/N
for i in range(N-1):
tmp += sitk.Cast(s[i+1],6)/N
return sitk.Cast(tmp,3)
print 'fusing stacks by using weight matrices'
for iweight in range(len(weights)):
weights[iweight].SetSpacing(s[iweight].GetSpacing())
weights[iweight].SetOrigin(s[iweight].GetOrigin())
#for iweight in range(len(weights)):
#weights[iweight] = weights[iweight]*sitk.Cast(s[iweight],6)
result = weights[0]*sitk.Cast(s[0],6)
for iweight in range(1,len(weights)):
result += weights[iweight]*sitk.Cast(s[iweight],6)
result = sitk.Cast(result,3)
return result
