def _getmask(pia, wm, polys, shape):
from .. import polyutils
mask = sparse.csr_matrix((len(wm), np.prod(shape)))
from tvtk.api import tvtk
measure = tvtk.MassProperties()
planes = tvtk.PlaneCollection()
for norm in np.vstack([-np.eye(3), np.eye(3)]):
planes.append(tvtk.Plane(normal=norm))
ccs = tvtk.ClipClosedSurface(clipping_planes=planes)
feats = tvtk.FeatureEdges(boundary_edges=1,
non_manifold_edges=0,
manifold_edges=0,
feature_edges=0)
feats.set_input(ccs.output)
surf = polyutils.Surface(pia, polys)
for i, (pts, faces) in enumerate(surf.polyhedra(wm)):
if len(pts) > 0:
poly = tvtk.PolyData(points=pts, polys=faces)
measure.set_input(poly)
measure.update()
totalvol = measure.volume
ccs.set_input(poly)
measure.set_input(ccs.output)
bmin = pts.min(0).round().astype(int)
bmax = (pts.max(0).round() + 1).astype(int)
vidx = np.mgrid[bmin[0]:bmax[0], bmin[1]:bmax[1],
bmin[2]:bmax[2]]
for vox in vidx.reshape(3, -1).T:
try:
idx = np.ravel_multi_index(vox[::-1], shape)
for plane, m in zip(planes,
[.5, .5, .5, -.5, -.5, -.5]):
plane.origin = vox + m
ccs.update()
if ccs.output.number_of_cells > 2:
measure.update()
mask[i, idx] = measure.volume
except ValueError:
print('Voxel not in volume: (%d, %d, %d)' % tuple(vox))
mask.data[mask.indptr[i]:mask.indptr[i + 1]] /= mask[i].sum()
return mask
def volumen_voxels(imagen):
mask3d = imagen > int(sys.argv[2])
mask3d = mask3d.astype(int)
objeto = tvtk.ImageData(spacing=(1, 1, 1), origin=(0, 0, 0))
objeto.point_data.scalars = mask3d.ravel()
objeto.point_data.scalars.name = 'scalars'
objeto.dimensions = imagen.shape
iso = tvtk.ImageMarchingCubes()
configure_input(iso, objeto)
mass = tvtk.MassProperties()
configure_input(mass, iso)
volumen3d = mass.volume
print "volumen en voxels por tratamiento 3d:", volumen3d
nGFPfinal = (mask3d == 1).sum()
fGmascarafinal = np.multiply(mask3d, imagen)
intensidadmedia = float((fGmascarafinal).sum()) / volumen3d
print "la intensidad media con el tratamiento 3d es:", intensidadmedia
print "el volumen haciendo la suma de los voxels de la mask es:", nGFPfinal
intensidadmedia = float((fGmascarafinal).sum()) / nGFPfinal
print "la intensidad media con la suma de voxels de la mask es:", intensidadmedia
return mask3d
def measure_volume(pts, polys):
from tvtk.api import tvtk
pd = tvtk.PolyData(points=pts, polys=polys)
mp = tvtk.MassProperties(input=pd)
return mp.volume
def volumen_voxels(imagen):
nGFP = [0 for x in range(0, int(sys.argv[2]) / int(sys.argv[3]) + 1)]
meanGFP = [0 for x in range(0, int(sys.argv[2]) / int(sys.argv[3]) + 1)]
ndatos = 0
for umbral in range(0,
int(sys.argv[2]) + int(sys.argv[3]), int(sys.argv[3])):
mascaraG = imagen > umbral
nGFP[ndatos] = (mascaraG == 1).sum()
if nGFP[ndatos] != 0:
fGmascara = np.multiply(mascaraG, imagen)
meanGFP[ndatos] = float((fGmascara).sum()) / nGFP[ndatos]
else:
meanGFP[ndatos] = 0
ndatos += 1
f = open(sys.argv[1], "w")
for nG in nGFP:
f.write(str(nG))
f.write(" ")
f.write("\n")
for mG in meanGFP:
f.write(str(mG))
f.write(" ")
f.write("\n")
ndatosmenos1 = ndatos - 1
comparacion = np.zeros((ndatosmenos1))
for i in range(ndatosmenos1):
if nGFP[i] != 0:
comparacion[i] = float(nGFP[i + 1]) / nGFP[i]
else:
comparacion[i] = 0
difumb = 1.0
encontrado = 0
while encontrado == 0:
encontrado = 0
difumb = difumb - 0.005
contador = 0
for i in range(ndatosmenos1):
if comparacion[i] > difumb:
contador += 1
if contador == 3:
umbrales = (i - 1) * int(sys.argv[3])
encontrado = 1
else:
contador = 0
mask3d = imagen > umbrales
mask3d = mask3d.astype(int)
objeto = tvtk.ImageData(spacing=(1, 1, 1), origin=(0, 0, 0))
objeto.point_data.scalars = mask3d.ravel()
objeto.point_data.scalars.name = 'scalars'
objeto.dimensions = imagen.shape
iso = tvtk.ImageMarchingCubes()
configure_input(iso, objeto)
mass = tvtk.MassProperties()
configure_input(mass, iso)
volumen3d = mass.volume
f.write(str(umbrales))
f.write("\n")
f.close()
print "el umbral final es:", umbrales
print "volumen en voxels por tratamiento 3d:", volumen3d
nGFPfinal = (mask3d == 1).sum()
fGmascarafinal = np.multiply(mask3d, imagen)
intensidadmedia = float((fGmascarafinal).sum()) / volumen3d
print "la intensidad media con el tratamiento 3d es:", intensidadmedia
print "el volumen haciendo la suma de los voxels de la mask es:", nGFPfinal
intensidadmedia = float((fGmascarafinal).sum()) / nGFPfinal
print "la intensidad media con la suma de voxels de la mask es:", intensidadmedia
return mask3d