def saveLandmarkModel(ls, dirsave, ptcode, ctcode, cropname, what):
""" Save graph with landmarks; do not store volumes again
Use within or outside class LandmarkSelector
"""
import os
s = ls.s
s2 = ls.s_landmarks
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange # keep for reference
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta' + suffix] = s['meta' + suffix]
s2.what = what
s2.params = 'LandmarkSelector'
s2.stentType = s.stenttype
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'landmarks' + what)
ssdf.save(os.path.join(dirsave, filename), s2)
print('')
print('saved to disk to {}.'.format(os.path.join(dirsave, filename)))
def set(self, key, object, save_now=True):
""" set(key, object, save_now=True)
Add an object to the database, using the given key.
If save_now is True, will save the database to disk now.
"""
# Correct key
key = self._key2key(key)
#print 'set', key
# Test object
if ssdf.isstruct(object):
pass
if isinstance(object, (int, float, str, np.ndarray, tuple, list)):
pass # Default ssdf compatible
elif ssdf.is_compatible_class(object):
pass # Compatible
else:
raise ValueError('The given object is not ssdf compatible.')
# Store last key
self._lastkey = key
# Store object in db
self._db[key] = object
# Save?
if save_now and self._fname:
ssdf.save(self._fname, self._db)
def save_segmentation(basedir, ptcode, ctcode, cropname, seeds, model, s,
stentType=None, what='avgreg', params=None):
""" store segmentation in new ssdf or load and add
s = ssdf of volume from which we segment
s2 = ssdf of segmentation model
"""
# Build struct
s2 = vv.ssdf.new()
# We do not need croprange, but keep for reference
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta'+suffix] = s['meta'+suffix]
s2.what = what
s2.params = params
s2.stentType = stentType
# Store model
s2.model = model.pack()
s2.seeds = seeds.pack()
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'model'+what)
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk in {} as {}.'.format(basedir, filename) )
def add_segmentation_ssdf(basedir, ptcode, ctcode, cropname, seeds, model,
graphname, s2=None, modelname='modelavgreg',
stentType=None, params=None):
""" Add a model to an existing ssdf but separate from the existing graph
s2 = ssdf of existing model to add new segmentation graph in ssdf
graphname = name of new graph to save in ssdf
"""
if s2 is None:
s2 = loadmodel(basedir, ptcode, ctcode, cropname, modelname) # unpacks to graph
s2['params'+graphname] = params
s2['stentType'+graphname] = stentType
# Store model
if model is not None: # step 2 and 3 were performed otherwise NoneType
s2['model'+graphname] = model
s2['seeds'+graphname] = seeds
else: # store seeds as model
s2['model'+graphname] = seeds.copy()
s2['seeds'+graphname] = seeds
# pack all graphs to ssdf for save
for key in dir(s2):
if key.startswith('model'):
s2[key] = s2[key].pack()
if key.startswith('seeds'):
s2[key] = s2[key].pack()
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, modelname)
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk in {} as {}.'.format(basedir, filename) )
def make_model_dynamic(basedir, ptcode, ctcode, cropname, what='avgreg'):
""" Read deforms and model to make model dynamic, ie, add deforms to edges
and nodes in the graph
"""
# Load deforms
s = loadvol(basedir, ptcode, ctcode, cropname, 'deforms')
deformkeys = []
for key in dir(s):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s[key] for key in deformkeys]
deforms = [pirt.DeformationFieldBackward(*fields) for fields in deforms]
paramsreg = s.params
# Load model
s = loadmodel(basedir, ptcode, ctcode, cropname, 'model'+what)
for key in dir(s):
if key.startswith('model'):
model = s[key]
# Combine ...
incorporate_motion_nodes(model, deforms, s.origin) # adds deforms PointSets
incorporate_motion_edges(model, deforms, s.origin) # adds deforms PointSets
s[key] = model.pack()
# also pack seeds before save
if key.startswith('seeds'):
s[key] = s[key].pack()
# Save back
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'model'+what)
s.paramsreg = paramsreg
ssdf.save(os.path.join(basedir, ptcode, filename), s)
print('saved dynamic to disk in {} as {}.'.format(basedir, filename) )
def cropaveraged(basedir,
ptcode,
ctcode,
crop_in='stent',
what='avg5090',
crop_out='body'):
""" Crop averaged volume of stent
With loadvol, load ssdf containing an averaged volume and save new cropped ssdf
"""
s = loadvol(basedir, ptcode, ctcode, crop_in, what)
vol = s.vol
# Open cropper tool
print('Set the appropriate cropping range for "%s" '
'and click finish to continue' % crop_out)
print('Loading... be patient')
fig = vv.figure()
fig.title = 'Cropping for "%s"' % crop_out
vol_crop = cropper.crop3d(vol, fig)
fig.Destroy()
if vol_crop.shape == vol.shape:
raise RuntimeError('User cancelled (no crop)')
# Calculate crop range from origin
rz = int(vol_crop.origin[0] / vol_crop.sampling[0] + 0.5)
rz = rz, rz + vol_crop.shape[0]
ry = int(vol_crop.origin[1] / vol_crop.sampling[1] + 0.5)
ry = ry, ry + vol_crop.shape[1]
rx = int(vol_crop.origin[2] / vol_crop.sampling[2] + 0.5)
rx = rx, rx + vol_crop.shape[2]
# Initialize struct
s2 = ssdf.new()
s2.sampling = vol_crop.sampling # z, y, x voxel size in mm
s2.stenttype = s.stenttype
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta' + suffix] = s['meta' + suffix]
# Set new croprange, origin and vol
offset = [i[0] for i in s.croprange] # origin of crop_in
s2.croprange = ([rz[0] + offset[0], rz[1] + offset[0]
], [ry[0] + offset[1], ry[1] + offset[1]],
[rx[0] + offset[2], rx[1] + offset[2]])
s2.origin = vol_crop.origin
s2.vol = vol_crop
# Export and save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, crop_out, what)
file_out = os.path.join(basedir, ptcode, filename)
ssdf.save(file_out, s2)
def test_pack1(self):
# Custom stent
g = StentGraph(summary='dit is een stent!', lala=3)
g.add_node((10, 20), foo=3)
g.add_node((30, 40), foo=5)
g.add_edge((1, 1), (2, 2), bar=10)
g.add_edge((10, 20), (1, 1), bar=20)
fname = '/home/almar/test.ssdf'
ssdf.save(fname, g.pack())
g2 = StentGraph()
g2.unpack(ssdf.load(fname))
#print(nx.is_isomorphic(g, g2))
assert nx.is_isomorphic(g, g2)
def makeLandmarkModelDynamic(basedir,
ptcode,
ctcode,
cropname,
what='landmarksavgreg',
savedir=None):
""" Make model dynamic with deforms from registration
(and store/overwrite to disk)
"""
#todo: change in default and merge with branch landmarks?
import pirt
from stentseg.motion.dynamic import (incorporate_motion_nodes,
incorporate_motion_edges)
from visvis import ssdf
import os
if savedir is None:
savedir = basedir
# Load deforms
s = loadvol(basedir, ptcode, ctcode, cropname, 'deforms')
deformkeys = []
for key in dir(s):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s[key] for key in deformkeys]
deforms = [pirt.DeformationFieldBackward(*fields) for fields in deforms]
paramsreg = s.params
# Load model where landmarks were stored
# s2 = loadmodel(savedir, ptcode, ctcode, cropname, what)
fname = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, what)
s2 = ssdf.load(os.path.join(savedir, fname))
# Turn into graph model
model = stentgraph.StentGraph()
model.unpack(s2[what])
# Combine ...
incorporate_motion_nodes(model, deforms, s2.origin)
incorporate_motion_edges(model, deforms, s2.origin)
# Save back
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, what)
s2.model = model.pack()
s2.paramsreg = paramsreg
ssdf.save(os.path.join(savedir, filename), s2)
print('saved to disk to {}.'.format(os.path.join(savedir, filename)))
def test_pack2(self):
# Auto generate
import random
n = 500
p = dict(
(i, (random.gauss(0, 2), random.gauss(0, 2))) for i in range(n))
g_ = nx.random_geometric_graph(n, 0.1, dim=3, pos=p)
g = StentGraph(summary='dit is een stent!', lala=3)
g.add_nodes_from(g_.nodes_iter())
g.add_edges_from(g_.edges_iter())
fname = '/home/almar/test.ssdf'
ssdf.save(fname, g.pack())
g2 = StentGraph()
g2.unpack(ssdf.load(fname))
#print(nx.is_isomorphic(g, g2))
assert nx.is_isomorphic(g, g2)
def save(self, fname=None):
""" save(fname=None)
Save the results to disk now. If fname is not given, the last used
fname is used. If there is no fname available, will raise a runtime
error.
"""
# Use given or stored fname?
if fname is None:
fname = self._fname
else:
self._fname = fname
# Check if there is an fname available
if fname is None:
raise RuntimeError('No known filename to write to.')
# Save
ssdf.save(fname, self._db)
def saveaveraged(basedir, ptcode, ctcode, cropname, phases):
""" Step C: Save average of a number of volumes (phases in cardiac cycle)
Load ssdf containing all phases and save averaged volume as new ssdf
"""
filename = '%s_%s_%s_phases.ssdf' % (ptcode, ctcode, cropname)
file_in = os.path.join(basedir, ptcode, filename)
if not os.path.exists(file_in):
raise RuntimeError('Could not find ssdf for given input %s' % ptcode,
ctcode, cropname)
s = ssdf.load(file_in)
s_avg = ssdf.new()
averaged = np.zeros(s.vol0.shape, np.float64)
if phases[1] < phases[0]:
phaserange = list(range(0, 100, 10))
for i in range(phases[1] + 10, phases[0], 10):
phaserange.remove(i)
else:
phaserange = range(phases[0], phases[1] + 10, 10)
for phase in phaserange:
averaged += s['vol%i' % phase]
s_avg['meta%i' % phase] = s['meta%i' % phase]
averaged *= 1.0 / len(phaserange)
averaged = averaged.astype('float32')
s_avg.vol = averaged
s_avg.sampling = s.sampling # z, y, x voxel size in mm
s_avg.origin = s.origin
s_avg.stenttype = s.stenttype
s_avg.croprange = s.croprange
s_avg.ctcode = s.ctcode
s_avg.ptcode = s.ptcode
avg = 'avg' + str(phases[0]) + str(phases[1])
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, avg)
file_out = os.path.join(basedir, ptcode, filename)
ssdf.save(file_out, s_avg)
def add_segmentation_graph(basedir, ptcode, ctcode, cropname, seeds, model,
s2=None, graphname='', modelname='modelavgreg'):
""" add segmentation to an existing graph
s2 = ssdf of existing segmentation model to add graph to this model
graphname = model is default storename for model but can also be
modelbranch for example if this was used in add_segmentation_ssdf
"""
if s2 is None:
s2 = loadmodel(basedir, ptcode, ctcode, cropname, modelname) # unpacks
graphold = s2['model'+graphname]
seedsold = s2['seeds'+graphname]
# add seeds graph
seedsold.add_nodes_from(seeds.nodes(data=True)) # including attributes if any
# add nodes and edges to graph model
if model is not None: # step 2 and 3 were performed otherwise NoneType
graphold.add_nodes_from(model.nodes(data=True))
graphold.add_edges_from(model.edges(data=True))
else: # store seeds with model
graphold.add_nodes_from(seeds.nodes(data=True))
# Store model
s2['model'+graphname] = graphold
s2['seeds'+graphname] = seedsold
# pack all graphs to ssdf for save
for key in dir(s2):
if key.startswith('model'):
s2[key] = s2[key].pack()
if key.startswith('seeds'):
s2[key] = s2[key].pack()
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, modelname)
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk in {} as {}.'.format(basedir, filename) )
# s2.stenttype = s.stenttype
# s2.croprange = s.croprange
# Obtain deform fields
for i in range(N):
fields = [field for field in reg.get_deform(i).as_backward()
] # fields of z,y,x
s2['deform%i' % i] = fields
s2.sampling = s2.deform0[
0].sampling # Sampling of deform is different!
s2.originDeforms = s2.deform0[0].origin # But origin is zero
s2.params = reg.params
# Save
filename = '%s_%s.ssdf' % (fileTr, 'deforms')
ssdf.save(os.path.join(dirsaveinsilico, ptcode, filename), s2)
print("deforms saved to disk.")
# Store averaged volume, where the volumes are registered
# create average volume from *all* volumes deformed to the "center"
N = len(reg._ims)
mean_vol = np.zeros(reg._ims[0].shape, 'float64')
for i in range(N):
vol, deform = reg._ims[i], reg.get_deform(i) # reg._ims[0]==volOr
mean_vol += deform.as_backward().apply_deformation(vol)
mean_vol *= 1.0 / N
# Create struct
s_avg = ssdf.new()
#s_avg.meta = s['meta'+oriPhase]
s_avg.sampling = sampling2 # z, y, x
s = processFont(fontname)
ss.append(s)
# process to pack together
sr, sb, si = ss[0], ss[1], ss[2]
for fonttype in ['b', 'i']:
s = ss[{'b': 1, 'i': 2}[fonttype]]
# cut interesting part of image in i or b
[Iy, Ix] = np.where(s.data > 0)
y1 = Iy.max()
data = s.data[0:y1 + 1, :]
# paste that part in image of regular
[Iy, Ix] = np.where(sr.data > 0)
y1 = Iy.max()
y2 = y1 + data.shape[0]
sr.data[y1:y2] = data
# correct origin of chars
for i in range(s.origin.shape[0]):
s.origin[i, 1] += y1
# copy information to struct of sr
sr['charcodes_' + fonttype] = s.charcodes
sr['origin_' + fonttype] = s.origin
sr['size_' + fonttype] = s.size
sr['width_' + fonttype] = s.width
# store
base[font] = sr
ssdf.save(path + 'fonts.ssdf', base)
ssdf.save(path + '../visvisResources/fonts.ssdf', base)
def on_key(event):
"""KEY commands for user interaction
'DELETE = remove seed in nodes1 closest to [picked point]'
'PageDown = remove graph posterior (y-axis) to [picked point] (use for spine seeds)'
'n = add [picked point] (SHIFT+R-click) as seed'
"""
global label
global sd
if event.key == vv.KEY_DELETE:
if len(selected_nodes) == 0:
# remove node closest to picked point
node = _utils_GUI.snap_picked_point_to_graph(sd._nodes1,
vol,
label,
nodesOnly=True)
sd._nodes1.remove_node(node)
view = a1.GetView()
a1.Clear()
label = DrawModelAxes(vol,
sd._nodes1,
a1,
clim=clim,
showVol=showVol,
removeStent=False)
a1.SetView(view)
if event.text == 'n':
# add picked seed to nodes_1
coord2 = get_picked_seed(vol, label)
sd._nodes1.add_node(tuple(coord2))
view = a1.GetView()
point = vv.plot(coord2[0],
coord2[1],
coord2[2],
mc='b',
ms='o',
mw=8,
alpha=0.5,
axes=a1)
a1.SetView(view)
if event.key == vv.KEY_PAGEDOWN:
# remove false seeds posterior to picked point, e.g. for spine
label = _utils_GUI.remove_nodes_by_selected_point(sd._nodes1,
vol,
a1,
label,
clim,
showVol=showVol)
if event.text == 't':
# redo step1
view = a1.GetView()
a1.Clear()
sd._params = p
sd.Step1()
label = DrawModelAxes(vol,
sd._nodes1,
a1,
clim=clim,
showVol=showVol,
removeStent=False) # lc, mc
a1.SetView(view)
if event.key == vv.KEY_ESCAPE:
model = sd._nodes1
# Build struct
s2 = vv.ssdf.new()
# We do not need croprange, but keep for reference
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta' + suffix] = s['meta' + suffix]
s2.what = what
s2.params = p
s2.stentType = stentType
# Store model
s2.model = model.pack()
# get filename
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'stentseeds' + what)
# check if file already exists to not overwrite automatically
if os.path.exists(os.path.join(dirsave, ptcode, filename)):
#todo: shell jams after providing answer?
print('File already exists')
answer = str(
input("\nWould you like to"
" overwrite (y), save different (u) or cancel (c)? "))
if answer == 'u':
filename = '%s_%s_%s_%s_2.ssdf' % (ptcode, ctcode, cropname,
'stentseeds' + what)
ssdf.save(os.path.join(dirsave, ptcode, filename), s2)
print("Ssdf saved to:")
print(os.path.join(dirsave, ptcode))
elif answer == 'y':
ssdf.save(os.path.join(dirsave, ptcode, filename), s2)
print("Ssdf saved to:")
print(os.path.join(dirsave, ptcode))
else:
try: # check folder existance
ssdf.save(os.path.join(dirsave, ptcode, filename), s2)
except FileNotFoundError: # if dirsave does not exist, create
os.makedirs(os.path.join(dirsave, ptcode))
ssdf.save(os.path.join(dirsave, ptcode, filename), s2)
print("Ssdf saved to:")
print(os.path.join(dirsave, ptcode))
def on_key(event):
"""KEY commands for user interaction
'UP/DOWN = show/hide nodes'
'DELETE = remove edge [select 2 nodes] or pop node [select 1 node] '
'or remove seed in nodes1 closest to [picked point]'
'PageDown = remove graph posterior (y-axis) to [picked point] (use for spine seeds)'
'ALT = clean graph: remove residual clusters, pop, corner'
'CTRL+SHIFT = add [picked point] (SHIFT+R-click) as seed'
"""
global label
global node_points
global sd
if event.key == vv.KEY_DOWN:
# hide nodes
t1.visible = False
t2.visible = False
t3.visible = False
for node_point in node_points:
node_point.visible = False
if event.key == vv.KEY_UP:
# show nodes
for node_point in node_points:
node_point.visible = True
if event.key == vv.KEY_DELETE:
if len(selected_nodes) == 0:
# remove node closest to picked point
node = _utils_GUI.snap_picked_point_to_graph(sd._nodes1,
vol,
label,
nodesOnly=True)
sd._nodes1.remove_node(node)
view = a1.GetView()
a1.Clear()
label = DrawModelAxes(vol,
sd._nodes1,
a1,
clim=clim,
showVol=showVol,
removeStent=False)
a1.SetView(view)
if len(selected_nodes) == 2:
# remove edge
select1 = selected_nodes[0].node
select2 = selected_nodes[1].node
c = sd._nodes3.edge[select1][select2]['cost']
ct = sd._nodes3.edge[select1][select2]['ctvalue']
path = sd._nodes3.edge[select1][select2]['path']
l = stentgraph._edge_length(sd._nodes3, select1, select2)
sd._nodes3.remove_edge(select1, select2)
stentgraph.pop_nodes(sd._nodes3) # pop residual nodes
# Visualize removed edge, show keys and deselect nodes
selected_nodes[1].faceColor = 'b'
selected_nodes[0].faceColor = 'b'
selected_nodes.clear()
t1.text = 'Edge ctvalue: \b{%1.2f HU}' % ct
t2.text = 'Edge cost: \b{%1.7f }' % c
t3.text = 'Edge length: \b{%1.2f mm}' % l
t1.visible = True
t2.visible = True
t3.visible = True
view = a3.GetView()
pp = Pointset(path)
line = vv.solidLine(pp, radius=0.2)
line.faceColor = 'r'
# a3.SetView(view)
if len(selected_nodes) == 1:
# pop node
select1 = selected_nodes[0].node
stentgraph._pop_node(sd._nodes3, select1) # asserts degree == 2
selected_nodes[0].faceColor = 'w'
selected_nodes.clear()
if event.key == vv.KEY_ALT:
# ALT will FINISH model
stentgraph.prune_clusters(sd._nodes3,
3) #remove residual nodes/clusters
stentgraph.pop_nodes(sd._nodes3)
stentgraph.add_corner_nodes(sd._nodes3,
th=sd._params.graph_angleVector,
angTh=sd._params.graph_angleTh)
# Create mesh and visualize
view = a3.GetView()
a3.Clear()
DrawModelAxes(vol,
sd._nodes3,
a3,
meshColor=meshColor,
clim=clim,
showVol=showVol,
lc='b',
mw=8,
lw=0.2)
_utils_GUI.vis_spared_edges(sd._nodes3)
a3.SetView(view)
print(
'----DO NOT FORGET TO SAVE THE MODEL TO DISK; RUN _SAVE_SEGMENTATION----'
)
if event.text == 'n':
# add picked seed to nodes_1
coord2 = get_picked_seed(vol, label)
sd._nodes1.add_node(tuple(coord2))
view = a1.GetView()
point = vv.plot(coord2[0],
coord2[1],
coord2[2],
mc='b',
ms='o',
mw=8,
alpha=0.5,
axes=a1)
a1.SetView(view)
if event.text == 'p':
# protect node from pop
pickedNode = _utils_GUI.snap_picked_point_to_graph(sd._nodes1,
vol,
label,
nodesOnly=True)
sd._nodes1.add_node(pickedNode, nopop=True)
sd._nodes2.add_node(pickedNode, nopop=True)
view = a1.GetView()
point = vv.plot(pickedNode[0],
pickedNode[1],
pickedNode[2],
mc='y',
ms='o',
mw=8,
alpha=0.5,
axes=a1)
a1.SetView(view)
# now rerun step 3
if event.key == vv.KEY_PAGEDOWN:
# remove false seeds posterior to picked point, e.g. for spine
try:
_utils_GUI.remove_nodes_by_selected_point(sd._nodes3,
vol,
a3,
label,
clim,
showVol=showVol)
except ValueError: # false nodes already cleaned by Step3
pass
_utils_GUI.remove_nodes_by_selected_point(sd._nodes2,
vol,
a2,
label,
clim,
showVol=showVol)
label = _utils_GUI.remove_nodes_by_selected_point(sd._nodes1,
vol,
a1,
label,
clim,
showVol=showVol)
if event.text == '1':
# redo step1
view = a1.GetView()
a1.Clear()
a2.Clear()
a3.Clear()
sd._params = p
sd.Step1()
label = DrawModelAxes(vol,
sd._nodes1,
a1,
clim=clim,
showVol=showVol,
removeStent=False) # lc, mc
a1.SetView(view)
if event.text == '2':
# redo step2 and 3
view = a2.GetView()
a2.Clear()
a3.Clear()
sd._params = p
sd.Step2()
sd.Step3(cleanNodes=cleanNodes)
DrawModelAxes(vol,
sd._nodes2,
a2,
clim=clim,
showVol=showVol,
removeStent=False)
DrawModelAxes(vol,
sd._nodes3,
a3,
meshColor=meshColor,
clim=clim,
showVol=showVol,
removeStent=False)
a2.SetView(view)
if event.text == '3':
view = a3.GetView()
a3.Clear()
sd._params = p
sd.Step3(cleanNodes=cleanNodes)
DrawModelAxes(vol,
sd._nodes3,
a3,
meshColor=meshColor,
clim=clim,
showVol=showVol,
removeStent=False)
node_points = _utils_GUI.interactive_node_points(sd._nodes3, scale=0.6)
_utils_GUI.node_points_callbacks(node_points,
selected_nodes,
pick=False)
a3.SetView(view)
if event.text == 's':
# SAVE SEGMENTATION
# make centerline points of segmentation
paths_as_pp = points_from_edges_in_graph(sd._nodes3, type='order')
ringpoints = paths_as_pp[0].T
# Get graph model
model = sd._nodes3
seeds = sd._nodes1
Draw = sd.Draw
# Build struct
s2 = vv.ssdf.new()
# We do not need croprange, but keep for reference
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta' + suffix] = s['meta' + suffix]
s2.what = what
s2.params = p
s2.stentType = stentType
# Store model
s2.model = model.pack()
s2.seeds = seeds.pack()
s2.Draw = Draw
s2.ringpoints = ringpoints
#s2.mesh = ssdf.new()
# Save
savedir = select_dir(
r'C:\Users\Gebruiker\Google Drive\Afstuderen\Rings')
filename = '%s_%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'model' + what, ring)
ssdf.save(os.path.join(savedir, filename), s2)
print('saved to disk in {} as {}.'.format(savedir, filename))
def __init__(self,ptcode,ctcode,basedir, seed_th=[600], show=True,
normalize=False, modelname='model'):
import os
import numpy as np
import visvis as vv
from visvis import ssdf
from stentseg.utils import PointSet, _utils_GUI
from stentseg.utils.datahandling import select_dir, loadvol, loadmodel
from stentseg.stentdirect.stentgraph import create_mesh
from stentseg.stentdirect import stentgraph, StentDirect, getDefaultParams
from stentseg.stentdirect import AnacondaDirect, EndurantDirect, NellixDirect
from stentseg.utils.visualization import show_ctvolume
from stentseg.utils.picker import pick3d, label2worldcoordinates, label2volindices
import scipy
from scipy import ndimage
import copy
# Select dataset to register
cropname = 'prox'
# phase = 10
#dataset = 'avgreg'
#what = str(phase) + dataset # avgreg
what = 'avgreg'
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, what)
# sampling was not properly stored after registration for all cases: reset sampling
vol_org = copy.deepcopy(s.vol)
s.vol.sampling = [vol_org.sampling[1], vol_org.sampling[1], vol_org.sampling[2]] # z,y,x
s.sampling = s.vol.sampling
vol = s.vol
## Initialize segmentation parameters
stentType = 'nellix' # 'zenith';'nellix' runs modified pruning algorithm in Step3
p = getDefaultParams(stentType)
p.seed_threshold = seed_th # step 1 [lower th] or [lower th, higher th]
# p.seedSampleRate = 7 # step 1, nellix
p.whatphase = what
## Perform segmentation
# Instantiate stentdirect segmenter object
if stentType == 'anacondaRing':
sd = AnacondaDirect(vol, p) # inherit _Step3_iter from AnacondaDirect class
#runtime warning using anacondadirect due to mesh creation, ignore
elif stentType == 'endurant':
sd = EndurantDirect(vol, p)
elif stentType == 'nellix':
sd = NellixDirect(vol, p)
else:
sd = StentDirect(vol, p)
## show histogram and normalize
# f = vv.figure(3)
# a = vv.gca()
# vv.hist(vol, drange=(300,vol.max()))
# normalize vol to certain limit
if normalize:
sd.Step0(3071)
vol = sd._vol
# b= vv.hist(vol, drange=(300,3071))
# b.color = (1,0,0)
## Perform step 1 for seeds
sd.Step1()
## Visualize
if show:
fig = vv.figure(2); vv.clf()
fig.position = 0.00, 22.00, 1920.00, 1018.00
clim = (0,2000)
# Show volume and model as graph
a1 = vv.subplot(121)
a1.daspect = 1,1,-1
# t = vv.volshow(vol, clim=clim)
t = show_ctvolume(vol, axis=a1, showVol='MIP', clim =clim, isoTh=250,
removeStent=False, climEditor=True)
label = pick3d(vv.gca(), vol)
sd._nodes1.Draw(mc='b', mw = 2) # draw seeded nodes
#sd._nodes2.Draw(mc='b', lc = 'g') # draw seeded and MCP connected nodes
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
# Show volume and cleaned up graph
a2 = vv.subplot(122)
a2.daspect = 1,1,-1
sd._nodes1.Draw(mc='b', mw = 2) # draw seeded nodes
# t = vv.volshow(vol, clim=clim)
# label = pick3d(vv.gca(), vol)
# sd._nodes2.Draw(mc='b', lc='g')
# sd._nodes3.Draw(mc='b', lc='g')
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
# # Show the mesh
#===============================================================================
# a3 = vv.subplot(133)
# a3.daspect = 1,1,-1
# t = vv.volshow(vol, clim=clim)
# pick3d(vv.gca(), vol)
# #sd._nodes3.Draw(mc='b', lc='g')
# m = vv.mesh(bm)
# m.faceColor = 'g'
# # _utils_GUI.vis_spared_edges(sd._nodes3)
# vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
#===============================================================================
# Use same camera
a1.camera = a2.camera #= a3.camera
switch = True
a1.axis.visible = switch
a2.axis.visible = switch
#a3.axis.visible = switch
## Store segmentation to disk
# Get graph model
model = sd._nodes1
# Build struct
s2 = vv.ssdf.new()
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta'+suffix] = s['meta'+suffix]
s2.what = what
s2.params = p
s2.stentType = stentType
# Store model (not also volume)
s2.model = model.pack()
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, modelname+ what)
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk as {}.'.format(filename) )
## Make model dynamic (and store/overwrite to disk)
#===============================================================================
#
# import pirt
# from stentsegf.motion.dynamic import incorporate_motion_nodes, incorporate_motion_edges
#
# # Load deforms
# s = loadvol(basedir, ptcode, ctcode, cropname, '10deforms')
# deformkeys = []
# for key in dir(s):
# if key.startswith('deform'):
# deformkeys.append(key)
# deforms = [s[key] for key in deformkeys]
# deforms = [pirt.DeformationFieldBackward(*fields) for fields in deforms]
# paramsreg = s.params
#
# # Load model
# s = loadmodel(basedir, ptcode, ctcode, cropname, 'model'+what)
# model = s.model
#
# # Combine ...
# incorporate_motion_nodes(model, deforms, s.origin)
# incorporate_motion_edges(model, deforms, s.origin)
#
# # Save back
# filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'model'+what)
# s.model = model.pack()
# s.paramsreg = paramsreg
# ssdf.save(os.path.join(basedir, ptcode, filename), s)
# print('saved to disk as {}.'.format(filename) )
#===============================================================================
def savecropvols(vols,
basedir,
ptcode,
ctcode,
cropname,
stenttype,
sampling=None,
meta=None):
""" Step B: Crop and Save SSDF
Input: vols from Step A
Save 2 or 10 volumes (cardiac cycle phases) in one ssdf file
Cropper tool opens to manually set the appropriate cropping range in x,y,z
Click 'finish' to continue saving
Meta information (dicom), origin, stenttype and cropping range are saved
"""
try:
vol0 = vv.Aarray(
vols[0], vols[0].meta.sampling) # vv.Aarray defines origin: 0,0,0
except AttributeError:
print('AttributeError no meta with vol, use given sampling')
vol0 = vv.Aarray(vols[0], sampling)
# Open cropper tool
print('Set the appropriate cropping range for "%s" '
'and click finish to continue' % cropname)
print('Loading... be patient')
fig = vv.figure()
fig.title = 'Cropping for "%s"' % cropname
#vol_crop = cropper.crop3d(vol0, fig)
vol_crop = crop3d(vol0, fig) # use local while error with cropper
fig.Destroy()
if vol_crop.shape == vol0.shape:
print('User did not crop')
# Calculate crop range from origin
rz = int(vol_crop.origin[0] / vol_crop.sampling[0] + 0.5)
rz = rz, rz + vol_crop.shape[0]
ry = int(vol_crop.origin[1] / vol_crop.sampling[1] + 0.5)
ry = ry, ry + vol_crop.shape[1]
rx = int(vol_crop.origin[2] / vol_crop.sampling[2] + 0.5)
rx = rx, rx + vol_crop.shape[2]
# Initialize struct
s = ssdf.new()
s.sampling = vol_crop.sampling # z, y, x voxel size in mm
s.origin = vol_crop.origin
s.croprange = rz, ry, rx # in world coordinates
s.stenttype = stenttype
s.ctcode = ctcode
s.ptcode = ptcode
# Export and save
if len(vols) == 1: # when static ct
s.vol = vols[0][rz[0]:rz[1], ry[0]:ry[1], rx[0]:rx[1]]
s.meta = vols[0].meta
vols[0].meta.PixelData = None # avoid ssdf warning
filename = '%s_%s_%s_phase.ssdf' % (ptcode, ctcode, cropname)
else: # dynamic ct
for volnr in range(0, len(vols)):
phase = volnr * 10
if len(vols) == 2: # when only diastolic/systolic volume
try:
phase = vols[
volnr].meta.SeriesDescription[:2] # '78%, iDose'
phase = int(phase)
except AttributeError: # has no meta
phase = volnr
s['vol%i' % phase] = vols[volnr][rz[0]:rz[1], ry[0]:ry[1],
rx[0]:rx[1]]
try:
s['meta%i' % phase] = vols[volnr].meta
vols[volnr].meta.PixelData = None # avoid ssdf warning
except AttributeError: # has no meta
pass
# s['meta%i'% phase] = meta # given input var
# todo: meta type now error TypeError: unorderable types: DataElement() < DataElement()
filename = '%s_%s_%s_phases.ssdf' % (ptcode, ctcode, cropname)
file_out = os.path.join(basedir, ptcode, filename)
ssdf.save(file_out, s)
print()
print('ssdf saved to {}.'.format(file_out))
# get deforms of centerline path as array
assert model.number_of_edges() == 1 # cll should be 1 path
centerlineEdge = model.edges()[0] # the two nodes that define the edge
centerlineDeforms = model.edge[centerlineEdge[0]][
centerlineEdge[1]]['pathdeforms']
# store in dict of centerlineMat
if key == 'model':
centerlineMat[
'centerline_deforms'] = centerlineDeforms # list with PointSet arrays
elif key == 'model_2':
centerlineMat[
'centerline2_2_deforms'] = centerlineDeforms # list with PointSet arrays
else:
print('No model found with known name')
# pack model for save
s[key] = model.pack()
# Save back ssdf
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, what + '_dynamic')
s.paramsreg = paramsreg
ssdf.save(os.path.join(basedirstl, ptcode, filename), s)
print('saved dynamic to disk in {} as {}.'.format(basedirstl, filename))
# Save back mat
newMatName = '%s_%s_%s_%s.mat' % (ptcode, ctcode, cropname, what + '_dynamic')
scipy.io.savemat(os.path.join(basedirstl, ptcode, newMatName), centerlineMat)
print('')
print('Dynamic centerline was stored as {}'.format(newMatName))
print('')
storevar['startpoint'] = start1
storevar['endpoint'] = end1
scipy.io.savemat(storemat, storevar)
print('')
print('centerline2 was stored as.mat to {}'.format(storemat))
print('')
# save ssdf
model = centerline_nodes
# Build struct
s2 = vv.ssdf.new()
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta' + suffix] = s['meta' + suffix]
s2.what = what
# Store model
s2.startpoint = start1
s2.endpoint = end1
s2.params = params
s2.centerline = centerline2
s2.model = model.pack()
# get filename
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'centerline')
ssdf.save(os.path.join(targetdir, filename), s2)
print("Centerline saved to ssdf in :")
print(os.path.join(targetdir, filename))
def _Save(self):
try:
ssdf.save(self._fname, self._s)
except IOError:
pass # Maybe an installed frozen application (no write-rights)
s2.croprange = s.croprange
# Obtain deform fields
for i in range(N):
phase = i * 10
fields = [field for field in reg.get_deform(i).as_backward()]
s2['deform%i' % phase] = fields
s2.sampling = s2.deform0[
0].sampling # Sampling of deform is different!
#s2.origin = s2.deform0[0].origin # But origin is zero
s2.originDeforms = s2.deform0[0].origin # But origin is zero
s2.params = reg.params
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'deforms')
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print("deforms saved to disk.")
# Store averaged volume, where the volumes are registered
from visvis import ssdf
# Create average volume from *all* volumes deformed to the "center"
N = len(reg._ims)
mean_vol = np.zeros(reg._ims[0].shape, 'float64')
for i in range(N):
vol, deform = reg._ims[i], reg.get_deform(i)
mean_vol += deform.as_backward().apply_deformation(vol)
mean_vol *= 1.0 / N
# Create struct
def __init__(self, ptcode, ctcode, basedir):
## Perform image registration
import os, time
import numpy as np
import visvis as vv
import pirt.reg # Python Image Registration Toolkit
from stentseg.utils.datahandling import select_dir, loadvol
import scipy
from scipy import ndimage
# Select dataset to register
cropname = 'prox'
what = 'phases'
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, what)
vols = []
phases = []
for key in dir(s):
if key.startswith('vol'):
print(key)
# create vol with zoom in z-direction
zscale = (s[key].sampling[0] / s[key].sampling[1]) # z / y
# resample vol using spline interpolation, 3rd order piecewise polynomial
vol_zoom = scipy.ndimage.interpolation.zoom(
s[key], [zscale, 1, 1], 'float32')
s[key].sampling = [
s[key].sampling[1], s[key].sampling[1], s[key].sampling[2]
]
# set scale and origin
vol_zoom_type = vv.Aarray(vol_zoom, s[key].sampling,
s[key].origin)
vol = vol_zoom_type
phases.append(key)
vols.append(vol)
t0 = time.time()
# Initialize registration object
reg = pirt.reg.GravityRegistration(*vols)
reg.params.mass_transforms = 2 # 2nd order (Laplacian) triggers more at lines
reg.params.speed_factor = 1.0
reg.params.deform_wise = 'groupwise' # groupwise!
reg.params.mapping = 'backward'
reg.params.deform_limit = 1.0
reg.params.final_scale = 1.0 # We might set this a wee bit lower than 1 (but slower!)
reg.params.scale_sampling = 16
reg.params.final_grid_sampling = 20
reg.params.grid_sampling_factor = 0.5
# Go!
reg.register(verbose=1)
t1 = time.time()
print('Registration completed, which took %1.2f min.' %
((t1 - t0) / 60))
# Store registration result
from visvis import ssdf
# Create struct
s2 = vv.ssdf.new()
N = len(vols)
for key in dir(s):
if key.startswith('meta'):
s2[key] = s[key]
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
# Obtain deform fields
for i in range(N):
fields = [field for field in reg.get_deform(i).as_backward()]
phase = phases[i][3:]
s2['deform%s' % phase] = fields
s2.sampling = s2['deform%s' %
phase][0].sampling # Sampling of deform is different!
s2.originDeforms = s2['deform%s' %
phase][0].origin # But origin is zero
s2.params = reg.params
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'deforms')
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print("deforms saved to disk.")
#============================================================================
# Store averaged volume, where the volumes are registered
#from visvis import ssdf
# Create average volume from *all* volumes deformed to the "center"
N = len(reg._ims)
mean_vol = np.zeros(reg._ims[0].shape, 'float64')
for i in range(N):
vol, deform = reg._ims[i], reg.get_deform(i)
mean_vol += deform.as_backward().apply_deformation(vol)
mean_vol *= 1.0 / N
# Create struct
s_avg = ssdf.new()
for key in dir(s):
if key.startswith('meta'):
s_avg[key] = s[key]
s_avg.sampling = s.vol0.sampling # z, y, x after interpolation
s_avg.origin = s.origin
s_avg.stenttype = s.stenttype
s_avg.croprange = s.croprange
s_avg.vol = mean_vol.astype('float32')
s_avg.params = s2.params
fig1 = vv.figure(1)
vv.clf()
fig1.position = 0, 22, 1366, 706
a1 = vv.subplot(111)
a1.daspect = 1, 1, -1
renderstyle = 'mip'
a1b = vv.volshow(s_avg.vol, clim=(0, 2000), renderStyle=renderstyle)
#a1b.isoThreshold = 600
vv.xlabel('x'), vv.ylabel('y'), vv.zlabel('z')
vv.title('Average volume of %s phases (%s) (resized data)' %
(len(phases), renderstyle))
# Save
avg = 'avgreg'
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, avg)
ssdf.save(os.path.join(basedir, ptcode, filename), s_avg)
print("avgreg saved to disk.")
t1 = time.time()
print('Registration completed, which took %1.2f min.' %
((t1 - t0) / 60))
def _Save(self):
ssdf.save(self._fname, self._s)
s = processFont(fontname)
ss.append(s)
# process to pack together
sr, sb, si = ss[0], ss[1], ss[2]
for fonttype in ['b', 'i']:
s = ss[{'b':1,'i':2}[fonttype]]
# cut interesting part of image in i or b
[Iy,Ix] = np.where(s.data>0); y1 = Iy.max()
data = s.data[0:y1+1,:]
# paste that part in image of regular
[Iy,Ix] = np.where(sr.data>0); y1 = Iy.max()
y2 = y1 + data.shape[0]
sr.data[y1:y2] = data
# correct origin of chars
for i in range(s.origin.shape[0]):
s.origin[i,1] += y1
# copy information to struct of sr
sr['charcodes_'+fonttype] = s.charcodes
sr['origin_'+fonttype] = s.origin
sr['size_'+fonttype] = s.size
sr['width_'+fonttype] = s.width
# store
base[font] = sr
ssdf.save(path+'fonts.ssdf', base)
ssdf.save(path+'../visvisResources/fonts.ssdf', base)
def __init__(self,ptcode,ctcode,basedir, threshold=300, show=True,
normalize=False, modelname='modelvessel'):
import os
import numpy as np
import visvis as vv
from visvis import ssdf
from stentseg.utils import PointSet, _utils_GUI
from stentseg.utils.datahandling import select_dir, loadvol, loadmodel
from stentseg.stentdirect.stentgraph import create_mesh
from stentseg.stentdirect import stentgraph, StentDirect, getDefaultParams
from stentseg.stentdirect import AnacondaDirect, EndurantDirect, NellixDirect
from stentseg.utils.visualization import show_ctvolume
from stentseg.utils.picker import pick3d, label2worldcoordinates, label2volindices
import scipy
from scipy import ndimage
import copy
from stentseg.utils.get_isosurface import get_isosurface3d, isosurface_to_graph, show_surface_and_vol
# Select dataset to register
cropname = 'prox'
#phase = 10
#what = 'phase'+str(phase)
what = 'avgreg'
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, what)
# sampling was not properly stored after registration for all cases: reset sampling
vol_org = copy.deepcopy(s.vol)
s.vol.sampling = [vol_org.sampling[1], vol_org.sampling[1], vol_org.sampling[2]] # z,y,x
s.sampling = s.vol.sampling
vol = s.vol
# Get isosurface
verts, faces, pp_vertices, mesh = get_isosurface3d(vol, threshold=threshold, showsurface=False)
if show:
self.label = show_surface_and_vol(vol, pp_vertices, showVol='MIP')
# Convert to graph
model = isosurface_to_graph(pp_vertices) # model with nodes
# Store segmentation to disk
p = threshold
stentType = 'isosurface'
# Build struct
s2 = vv.ssdf.new()
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = s.stenttype
s2.croprange = s.croprange
for key in dir(s):
if key.startswith('meta'):
suffix = key[4:]
s2['meta'+suffix] = s['meta'+suffix]
s2.what = what
s2.params = p
s2.stentType = stentType
# Store model (not also volume)
s2.model = model.pack()
# Save
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, modelname+ what)
ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk as {}.'.format(filename) )
def _Save(self):
try:
ssdf.save(self._fname, self._s)
except IOError:
pass # Maybe an installed frozen application (no write-rights)
def _Save(self):
ssdf.save(self._fname, self._s)
