def step_last(self):
# Assign attributes to local variables for convenience.
u = self._u
mask = thin(
find_boundaries(gvoronoi(label(u, connectivity=1)), mode='inner'))
if u is None:
raise ValueError(
"the levelset function is not set (use set_levelset)")
data = self.data
# Determine c0 and c1.
inside = u > 0
outside = u <= 0
c0 = data[outside].sum() / float(outside.sum())
c1 = data[inside].sum() / float(inside.sum())
# Image attachment.
dres = np.array(np.gradient(u))
abs_dres = np.abs(dres).sum(0)
aux = abs_dres * (self.lambda1 * (data - c1)**2 - self.lambda2 *
(data - c0)**2)
res = np.copy(u)
res[aux < 0] = 1
res[aux > 0] = 0
# Smoothing.
for i in range(self.smoothing):
res = curvop(res)
res[mask] = 0
self._u = res
def levelset_geo_separete(img,
labels,
niter=10,
prop=-1,
advec=-0.5,
curve=-0.5):
seg = sitk.GetImageFromArray((labels > 0).astype(np.uint8))
init_ls = sitk.SignedMaurerDistanceMap(seg,
insideIsPositive=True,
useImageSpacing=True)
mask = find_boundaries(gvoronoi(label(labels, connectivity=1)),
mode='inner')
img1 = img.copy()
img1[mask] = 0
img_T1 = sitk.GetImageFromArray(img1)
lsFilter = sitk.GeodesicActiveContourLevelSetImageFilter()
lsFilter.SetMaximumRMSError(0.02)
lsFilter.SetNumberOfIterations(niter)
lsFilter.SetAdvectionScaling(advec)
lsFilter.SetCurvatureScaling(curve)
lsFilter.SetPropagationScaling(prop)
# lsFilter.ReverseExpansionDirectionOn()
ls = lsFilter.Execute(init_ls, sitk.Cast(img_T1, sitk.sitkFloat32))
return label(sitk.GetArrayFromImage(ls) > 0, connectivity=1)
def test_gvoronoi():
labeled = np.zeros((128,128))
labeled[0,0] = 1
labeled[-1,-1] = 2
regions = gvoronoi(labeled)
Y,X = np.where(regions == 1)
assert np.all(Y+X < 128)
def test_gvoronoi():
labeled = np.zeros((128, 128))
labeled[0, 0] = 1
labeled[-1, -1] = 2
regions = gvoronoi(labeled)
Y, X = np.where(regions == 1)
assert np.all(Y + X < 128)
def test_compare_w_scipy():
np.random.seed(2322)
for i in range(8):
labeled = np.zeros((128,128))
for p in range(16):
y = np.random.randint(128)
x = np.random.randint(128)
labeled[y,x] = p+1
sp = scipy_gvoronoi(labeled)
mh = gvoronoi(labeled)
assert np.all(sp == mh)
def test_compare_w_scipy():
np.random.seed(2322)
for i in xrange(8):
labeled = np.zeros((128, 128))
for p in xrange(16):
y = np.random.randint(128)
x = np.random.randint(128)
labeled[y, x] = p + 1
sp = scipy_gvoronoi(labeled)
mh = gvoronoi(labeled)
assert np.all(sp == mh)
