def DrawModelAxes(vol,
graph=None,
ax=None,
axVis=False,
meshColor=None,
getLabel=False,
mc='b',
lc='g',
mw=7,
lw=0.6,
**kwargs):
""" Draw model with volume with axes set
ax = axes to draw (a1 or a2 or a3); graph = sd._nodes1 or 2 or 3
meshColor = None or faceColor e.g. 'g'
"""
#todo: prevent TypeError: draw() got an unexpected keyword argument mc/lc when not given as required variable
#todo: *args voor vol in drawModelAxes of **kwargs[key] in functies hieronder
if ax is None:
ax = vv.gca()
ax.MakeCurrent()
ax.daspect = 1, 1, -1
ax.axis.axisColor = 1, 1, 1
ax.bgcolor = 0, 0, 0
ax.axis.visible = axVis
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
if graph is None:
show_ctvolume(vol, graph, axis=ax, removeStent=False, **kwargs)
label = pick3d(vv.gca(), vol)
return label
if hasattr(graph, 'number_of_edges'):
if graph.number_of_edges(
) == 0: # get label from picked seeds sd._nodes1
show_ctvolume(vol, graph, axis=ax, **kwargs)
label = pick3d(vv.gca(), vol)
graph.Draw(mc=mc, lc=lc)
return label
if not meshColor is None:
bm = create_mesh(graph, 0.5) # (argument is strut tickness)
m = vv.mesh(bm)
m.faceColor = meshColor # 'g'
show_ctvolume(vol, graph, axis=ax, **kwargs)
graph.Draw(mc=mc, lc=lc)
if getLabel == True:
label = pick3d(vv.gca(), vol)
return label
else:
pick3d(vv.gca(), vol)
return
def nodeInteraction(model, vol, selected_nodes):
""" modify edges in dynamic model and make dynamic again
"""
f = vv.figure()
vv.clf()
f.position = 8.00, 30.00, 944.00, 1002.00
a = vv.gca()
a.axis.axisColor = 1, 1, 1
a.axis.visible = False
a.bgcolor = 0, 0, 0
a.daspect = 1, 1, -1
lim = (0, 2500)
t = vv.volshow(vol, clim=lim, renderStyle='mip')
pick3d(vv.gca(), vol)
model.Draw(mc='b', mw=10, lc='g')
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
vv.title('User interaction to modify model %s - %s' %
(ptcode[-3:], ctcode))
t3 = vv.Label(a, 'Edge length: ', fontSize=11, color='c')
t3.position = 0.1, 55, 0.5, 20
t3.bgcolor = None
t3.visible = False
# create clickable nodes
node_points = _utils_GUI.interactive_node_points(model, scale=0.6)
# bind event handlers
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [a]))
f.eventKeyDown.Bind(on_key)
for node_point in node_points:
node_point.eventDoubleClick.Bind(
lambda event: _utils_GUI.select_node(event, selected_nodes))
print('')
print('UP/DOWN = show/hide nodes')
print('DELETE = remove edge [select 2 nodes] or pop node [select 1 node]')
print('s = additional smooth')
print('e = smooth selected edge')
print('w = clear selected nodes')
print('q = activate "interactiveClusterRemoval"')
print('ALT = pop nodes')
print('ESCAPE = make model dynamic and save to disk')
print('')
return node_points, t3
def show_surface_and_vol(vol,
pp_isosurface,
showVol='MIP',
clim=(-200, 1000),
isoTh=300,
climEditor=True):
""" Show the generated isosurface in original volume
"""
f = vv.figure()
ax = vv.gca()
ax.daspect = 1, 1, -1
ax.axis.axisColor = 1, 1, 1
ax.bgcolor = 0, 0, 0
# show vol and iso vertices
show_ctvolume(vol,
showVol=showVol,
isoTh=isoTh,
clim=clim,
climEditor=climEditor)
label = pick3d(vv.gca(), vol)
vv.plot(pp_isosurface, ms='.', ls='', mc='r', alpha=0.2, mw=4)
a = vv.gca()
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [a]))
print('------------------------')
print('Use keys 1, 2, 3, 4 and 5 for preset anatomic views')
print('Use v for a default zoomed view')
print('Use x to show and hide axis')
print('------------------------')
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
return label
def showModel3d(basedir,ptcode, ctcode, cropname='ring', showVol='MIP',
showmodel=True, graphname='model', **kwargs):
""" show model and vol in 3d by mip iso or 2D
graphname 'all' draws all graph models stored in s, if multiple
"""
s = loadmodel(basedir, ptcode, ctcode, cropname, modelname='modelavgreg')
vol = loadvol(basedir, ptcode, ctcode, cropname, what='avgreg').vol
# figure
f = vv.figure(); vv.clf()
f.position = 0.00, 22.00, 1920.00, 1018.00
a = vv.gca()
a.axis.axisColor = 1,1,1
a.axis.visible = False
a.bgcolor = 0,0,0
a.daspect = 1, 1, -1
t = show_ctvolume(vol, axis=a, showVol=showVol, removeStent=False,
climEditor=True, **kwargs)
label = pick3d(a, vol)
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
if showmodel:
if graphname == 'all':
for key in dir(s):
if key.startswith('model'):
s[key].Draw(mc='b', mw = 5, lc='g', alpha = 0.5)
else:
s[graphname].Draw(mc='b', mw = 5, lc='g', alpha = 0.5)
vv.title('Model for LSPEAS %s - %s' % (ptcode[8:], ctcode))
# f.eventKeyDown.Bind(lambda event: _utils_GUI.RotateView(event, [a], axishandling=False ))
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [a]) )
return f, a, label, s
def drawmodelphasescycles(vol1,
model1,
modelori1,
showVol,
isoTh=300,
removeStent=False,
showmodelavgreg=False,
showvol=True,
phases=range(10),
colors='cgmrcgywmb',
meshWithColors=False,
stripSizeZ=None,
ax=None):
""" draw model and volume (show optional) at different phases cycle
"""
if ax is None:
ax = vv.gca()
ax.daspect = 1, 1, -1
ax.axis.axisColor = 0, 0, 0
ax.bgcolor = 1, 1, 1
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
# draw
t = show_ctvolume(vol1,
modelori1,
showVol=showVol,
removeStent=removeStent,
climEditor=True,
isoTh=isoTh,
clim=clim0,
stripSizeZ=stripSizeZ)
if showmodelavgreg:
# show model and CT mid cycle
mw = 5
for model in model1:
model.Draw(mc='b', mw=mw, lc='b', alpha=0.5)
label = pick3d(ax, vol1)
if not showvol:
t.visible = False
# get models in different phases
for model in model1:
for phasenr in phases:
model_phase = get_graph_in_phase(model, phasenr=phasenr)
if meshWithColors:
modelmesh1 = create_mesh_with_abs_displacement(model_phase,
radius=radius,
dim=dimensions)
m = vv.mesh(modelmesh1, colormap=vv.CM_JET, clim=clim2)
#todo: use colormap Viridis or Magma as JET is not linear (https://bids.github.io/colormap/)
else:
model_phase.Draw(mc=colors[phasenr], mw=10, lc=colors[phasenr])
# modelmesh1 = create_mesh(model_phase, radius = radius)
# m = vv.mesh(modelmesh1); m.faceColor = colors[phasenr]
if meshWithColors:
vv.colorbar()
return ax
def remove_nodes_by_selected_point(graph,
vol,
axes,
label,
clim,
location='posterior',
**kwargs):
""" removes nodes and edges in graph. Graph is separated by coord of selected point
use location to define what to remove, e.g. posterior to remove nodes in spine
Input : graph, axes, label of selected point,
dimension how to separate graph
Output: graph is modified locally and visualized in current view
"""
from stentseg.utils.picker import pick3d, label2worldcoordinates
from stentseg.utils.visualization import DrawModelAxes
if graph is None:
print('No nodes removed, graph is NoneType')
return
coord1 = np.asarray(label2worldcoordinates(label),
dtype=np.float32) # x,y,z
if location == 'posterior':
seeds = np.asarray(sorted(
graph.nodes(), key=lambda x: x[1])) # sort dim small to large
falseindices = np.where(
seeds[:, 1] > coord1[1]
) # tuple wih array of indices with values higher than coord y = 1
if location == 'anterior':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[1]))
falseindices = np.where(seeds[:, 1] < coord1[1])
elif location == 'proximal':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[2]))
falseindices = np.where(
seeds[:, 2] < coord1[2]) # dim z = 2; origin proximal
elif location == 'distal':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[2]))
falseindices = np.where(seeds[:, 2] > coord1[2]) # dim z = 2
elif location == 'left':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[0]))
falseindices = np.where(seeds[:, 0] > coord1[0])
elif location == 'right':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[0]))
falseindices = np.where(seeds[:, 0] < coord1[0])
# get seeds for removal by indices
falseseeds = seeds[falseindices[0]]
# remove from graph
graph.remove_nodes_from(tuple(map(
tuple, falseseeds))) # use map to convert to tuples
view = axes.GetView()
axes.Clear()
DrawModelAxes(vol, graph, ax=axes, clim=clim, **kwargs)
axes.SetView(view)
if graph.number_of_edges() == 0: # get label from picked seeds sd._nodes1
label = pick3d(vv.gca(), vol)
return label
def reDrawModel(vol, model, ax=None, selected_nodes=[]):
if ax is None:
ax = vv.gca()
view = ax.GetView()
ax.Clear()
lim = (0, 2500)
t = vv.volshow(vol, clim=lim, renderStyle='mip')
pick3d(vv.gca(), vol)
model.Draw(mc='g', mw=10, lc='g')
node_points = _utils_GUI.interactive_node_points(model, scale=0.6)
_utils_GUI.node_points_callbacks(node_points, selected_nodes, pick=False)
# see if node_points are still selected to color them red
for node_point in node_points:
node_point.visible = True
for i, node in enumerate(selected_nodes):
if node_point.node == node.node:
selected_nodes[i] = node_point
node_point.faceColor = (1, 0, 0)
ax.SetView(view)
return node_points
## Load all rings of the limb
for i in nrs:
ring = 'ringR%s' %(i)
filename = '%s_%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'model'+what,ring)
s["ringR" + str(i)] = ssdf.load(os.path.join(basedir1, filename))
## Visualize centerlines rings
s2 = loadmodel(targetdir2, ptcode, ctcode, cropname, modelname='stentseedsavgreg')
pmodel = points_from_nodes_in_graph(s2.model)
if FIG1 == True:
f = vv.figure(1); vv.clf()
f.position = 709.00, 30.00, 1203.00, 1008.00
a1 = vv.subplot(121)
show_ctvolume(s.vol, None, showVol=showVol, clim=clim0, isoTh=isoTh, removeStent=False)
label = pick3d(vv.gca(), s.vol)
a1.axis.visible = showAxis
a1.daspect = 1,1,-1
a2 = vv.subplot(122)
vv.plot(pmodel, ms='.', ls='', alpha=0.2, mw = 2) # stent seed points
for i in nrs:
pp = s["ringR" + str(i)].ringpoints
vv.plot(pp[0],pp[1],pp[2], ms='.', ls='', mw=3, mc='c')
a2.axis.visible = showAxis
a2.daspect = 1,1,-1
# a1.camera = a2.camera
## Distances
# Obtain minimal distances from all points on ring to a point on ring below
fig = vv.figure()
vv.clf()
fig.position = 0.00, 22.00, 1920.00, 1018.00
clim = (0, 2500)
# Show volume
a1 = vv.subplot(111)
a1.daspect = 1, 1, -1
t = show_ctvolume(vol,
axis=a1,
showVol='ISO',
clim=clim,
isoTh=250,
removeStent=False,
climEditor=True)
label = pick3d(vv.gca(), vol)
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
## Show 3D movie, by alternating the 10 volumes
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, 'phases')
vols = []
for key in dir(s):
if key.startswith('vol'):
zscale = (s[key].sampling[0] / s[key].sampling[1]) # z / y
# resample vol using spline interpolation, 3rd order polynomial
vol_zoom = scipy.ndimage.interpolation.zoom(s[key], [zscale, 1, 1],
'float32')
def identify_peaks_valleys(midpoints_peaks_valleys, model, vol, vis=True):
""" Given a cloud of points containing 2 peak and 2 valley points for R1
and R2, identify and return these locations. Uses clustering and x,y,z
"""
# detect clusters to further label locations
kmeans = KMeans(n_clusters=4)
kmeans.fit(midpoints_peaks_valleys)
centroids = kmeans.cluster_centers_ # x,y,z
labels = kmeans.labels_
# identify left, right, ant, post centroid (assumes origin is prox right anterior)
left = list(centroids[:, 0]).index(max(centroids[:, 0])) # max x value
right = list(centroids[:, 0]).index(min(centroids[:, 0]))
anterior = list(centroids[:, 1]).index(min(centroids[:, 1])) # min y value
posterior = list(centroids[:, 1]).index(max(centroids[:, 1]))
# get points into grouped arrays
cLeft, cRight, cAnterior, cPosterior = [], [], [], []
for i, p in enumerate(midpoints_peaks_valleys):
if labels[i] == left:
cLeft.append(tuple(p.flat))
elif labels[i] == right:
cRight.append(tuple(p.flat))
elif labels[i] == anterior:
cAnterior.append(tuple(p.flat))
elif labels[i] == posterior:
cPosterior.append(tuple(p.flat))
cLeft = np.asarray(cLeft)
cRight = np.asarray(cRight)
cAnterior = np.asarray(cAnterior)
cPosterior = np.asarray(cPosterior)
# divide into R1 R2
R1_left = cLeft[list(cLeft[:, 2]).index(min(
cLeft[:, 2]))] # min z for R1; valley
R2_left = cLeft[list(cLeft[:, 2]).index(max(cLeft[:, 2]))] # valley
R1_right = cRight[list(cRight[:, 2]).index(min(
cRight[:, 2]))] # min z for R1; valley
R2_right = cRight[list(cRight[:, 2]).index(max(cRight[:, 2]))] # valley
R1_ant = cAnterior[list(cAnterior[:, 2]).index(min(
cAnterior[:, 2]))] # min z for R1; peak
R2_ant = cAnterior[list(cAnterior[:, 2]).index(max(cAnterior[:,
2]))] # peak
R1_post = cPosterior[list(cPosterior[:, 2]).index(min(
cPosterior[:, 2]))] # min z for R1; peak
R2_post = cPosterior[list(cPosterior[:,
2]).index(max(cPosterior[:,
2]))] # peak
if vis == True:
# visualize identified locations
f = vv.figure(1)
vv.clf()
f.position = 968.00, 30.00, 944.00, 1002.00
a = vv.gca()
colors = ['r', 'g', 'b', 'm', 'c', 'y', 'w', 'k']
for i, p in enumerate([
R1_left, R2_left, R1_right, R2_right, R1_ant, R2_ant, R1_post,
R2_post
]):
vv.plot(p[0], p[1], p[2], ms='.', ls='', mc=colors[i], mw=14)
vv.legend('R1 left', 'R2 left', 'R1 right', 'R2 right', 'R1 ant',
'R2 ant', 'R1 post', 'R2 post')
show_ctvolume(vol, model, showVol='MIP', clim=(0, 2500))
pick3d(vv.gca(), vol)
model.Draw(mc='b', mw=10, lc='g')
for i in range(len(midpoints_peaks_valleys)):
vv.plot(midpoints_peaks_valleys[i],
ms='.',
ls='',
mc=colors[labels[i]],
mw=6)
a.axis.axisColor = 1, 1, 1
a.bgcolor = 0, 0, 0
a.daspect = 1, 1, -1 # z-axis flipped
a.axis.visible = True
return R1_left, R2_left, R1_right, R2_right, R1_ant, R2_ant, R1_post, R2_post
def identifyCenterlines(s,
ptcode,
ctcode,
basedir,
modelname,
showVol='MIP',
**kwargs):
""" s is struct with models
"""
from stentseg.utils.datahandling import select_dir, loadvol, loadmodel
from stentseg.utils.picker import pick3d
from stentseg.utils.visualization import show_ctvolume
from stentseg.utils import _utils_GUI
showAxis = False
# showVol = 'MIP' # MIP or ISO or 2D or None
clim = (0, 2500)
# clim = -200,500 # 2D
isoTh = 250
cropname = 'prox'
# init fig
f = vv.figure()
vv.clf()
f.position = 0.00, 22.00, 1920.00, 1018.00
# load vol
svol = loadvol(basedir, ptcode, ctcode, cropname, what='avgreg')
# set sampling for cases where this was not stored correctly
svol.vol.sampling = [svol.sampling[1], svol.sampling[1], svol.sampling[2]]
vol = svol.vol
s.sampling = [svol.sampling[1], svol.sampling[1],
svol.sampling[2]] # for model
# show vol
t = show_ctvolume(vol, showVol=showVol, clim=clim, isoTh=isoTh, **kwargs)
label = pick3d(vv.gca(), vol)
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
if showVol == 'MIP':
c = vv.ClimEditor(vv.gca())
c.position = (10, 50)
f.eventKeyDown.Bind(lambda event: _utils_GUI.ShowHideSlider(event, c))
print('Use "s" to show/hide slider')
if showVol == 'ISO':
c = _utils_GUI.IsoThEditor(vv.gca())
c.position = (10, 50)
f.eventKeyDown.Bind(lambda event: _utils_GUI.ShowHideSlider(event, c))
print('Use "s" to show/hide slider')
f.eventKeyDown.Bind(
lambda event: _utils_GUI.ViewPresets(event, [vv.gca()]))
print('------------------------')
print('Use keys 1, 2, 3, 4 and 5 for preset anatomic views')
print('Use v for a default zoomed view')
print('Use x to show and hide axis')
print('------------------------')
ax, s2 = interactiveCenterlineID(s, ptcode, ctcode, basedir, cropname,
modelname)
return ax, s2
ax.axis.axisColor = 0, 0, 0
ax.bgcolor = 1, 1, 1
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
# draw
showVol = 'ISO'
t = show_ctvolume(vol,
showVol=showVol,
removeStent=False,
climEditor=True,
isoTh=300)
if showmodelavgreg:
# show model and CT mid cycle
mw = 5
modelcll.Draw(mc='b', mw=mw, lc='b', alpha=0.5)
label = pick3d(ax, vol)
if not showvol:
t.visible = False
# get centerline models in different phases
for phasenr in phases:
model_phase = get_graph_in_phase(modelcll, phasenr=phasenr)
model_phase.Draw(mc=color[phasenr], mw=10, lc=color[phasenr])
#bind view control
f.eventKeyDown.Bind(
lambda event: _utils_GUI.RotateView(event, [ax], axishandling=False))
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [ax]))
def showModelsStatic(ptcode,codes, vols, ss, mm, vs, showVol, clim, isoTh, clim2,
clim2D, drawMesh=True, meshDisplacement=True, drawModelLines=True,
showvol2D=False, showAxis=False, drawVessel=False, vesselType=1,
meshColor=None, **kwargs):
""" show one to four models in multipanel figure.
Input: arrays of codes, vols, ssdfs; params from show_models_static
Output: axes, colorbars
"""
# init fig
f = vv.figure(1); vv.clf()
# f.position = 0.00, 22.00, 1920.00, 1018.00
mw = 5
if drawMesh == True:
lc = 'w'
meshColor = meshColor
else:
lc = 'g'
# create subplots
if isinstance(codes, str): # if 1 ctcode, otherwise tuple of strings
a1 = vv.subplot(111)
axes = [a1]
elif codes == (codes[0],codes[1]):
a1 = vv.subplot(121)
a2 = vv.subplot(122)
axes = [a1,a2]
elif codes == (codes[0],codes[1], codes[2]):
a1 = vv.subplot(131)
a2 = vv.subplot(132)
a3 = vv.subplot(133)
axes = [a1,a2,a3]
elif codes == (codes[0],codes[1], codes[2], codes[3]):
a1 = vv.subplot(141)
a2 = vv.subplot(142)
a3 = vv.subplot(143)
a4 = vv.subplot(144)
axes = [a1,a2,a3,a4]
elif codes == (codes[0],codes[1], codes[2], codes[3], codes[4]):
a1 = vv.subplot(151)
a2 = vv.subplot(152)
a3 = vv.subplot(153)
a4 = vv.subplot(154)
a5 = vv.subplot(155)
axes = [a1,a2,a3,a4,a5]
else:
a1 = vv.subplot(111)
axes = [a1]
for i, ax in enumerate(axes):
ax.MakeCurrent()
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Model for LSPEAS %s - %s' % (ptcode[7:], codes[i]))
t = show_ctvolume(vols[i], ss[i].model, axis=ax, showVol=showVol, clim=clim, isoTh=isoTh, **kwargs)
label = pick3d(ax, vols[i])
if drawModelLines == True:
ss[i].model.Draw(mc='b', mw = mw, lc=lc)
if showvol2D:
for i, ax in enumerate(axes):
t2 = vv.volshow2(vols[i], clim=clim2D, axes=ax)
cbars = [] # colorbars
if drawMesh:
for i, ax in enumerate(axes):
m = vv.mesh(mm[i], axes=ax)
if meshDisplacement:
m.clim = clim2
m.colormap = vv.CM_JET #todo: use colormap Viridis or Magma as JET is not linear (https://bids.github.io/colormap/)
cb = vv.colorbar(ax)
cbars.append(cb)
elif meshColor is not None:
if len(meshColor) == 1:
m.faceColor = meshColor[0] # (0,1,0,1)
else:
m.faceColor = meshColor[i]
else:
m.faceColor = 'g'
if drawVessel:
for i, ax in enumerate(axes):
v = showVesselMesh(vs[i], ax, type=vesselType)
for ax in axes:
ax.axis.axisColor = 1,1,1
ax.bgcolor = 25/255,25/255,112/255 # midnightblue
# http://cloford.com/resources/colours/500col.htm
ax.daspect = 1, 1, -1 # z-axis flipped
ax.axis.visible = showAxis
# set colorbar position
for cbar in cbars:
p1 = cbar.position
cbar.position = (p1[0], 20, p1[2], 0.98) # x,y,w,h
# bind rotate view and view presets [1,2,3,4,5]
f = vv.gcf()
f.eventKeyDown.Bind(lambda event: _utils_GUI.RotateView(event,axes,axishandling=False) )
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event,axes) )
return axes, cbars
def __init__(self,ptcode,ctcode,allcenterlines,basedir):
"""
Script to show the stent plus centerline model and select points on
centerlines for motion analysis
"""
import os, time
import pirt
import visvis as vv
import numpy as np
import math
import itertools
import xlsxwriter
from datetime import datetime
from stentseg.utils.datahandling import select_dir, loadvol, loadmodel
from stentseg.utils.new_pointset import PointSet
from stentseg.stentdirect.stentgraph import create_mesh
from stentseg.motion.vis import create_mesh_with_abs_displacement
from stentseg.utils.visualization import show_ctvolume
from pirt.utils.deformvis import DeformableTexture3D, DeformableMesh
from stentseg.utils import PointSet
from stentseg.stentdirect import stentgraph
from visvis import Pointset # for meshes
from stentseg.stentdirect.stentgraph import create_mesh
from visvis.processing import lineToMesh, combineMeshes
from visvis import ssdf
from stentseg.utils.picker import pick3d
try:
from PyQt4 import QtCore, QtGui # PyQt5
except ImportError:
from PySide import QtCore, QtGui # PySide2
from stentseg.apps.ui_dialog import MyDialog
from stentseg.utils.centerline import dist_over_centerline # added for Mirthe
import copy
cropname = 'prox'
exceldir = os.path.join(basedir,ptcode)
# Load deformations and avg ct (forward for mesh)
# centerlines combined in 1 model
m = loadmodel(basedir, ptcode, ctcode, cropname, modelname = 'centerline_total_modelavgreg_deforms')
model = m.model
# centerlines separated in a model for each centerline
# m_sep = loadmodel(basedir, ptcode, ctcode, cropname, modelname = 'centerline_modelavgreg_deforms')
s = loadvol(basedir, ptcode, ctcode, cropname, what='avgreg')
vol_org = copy.deepcopy(s.vol)
s.vol.sampling = [vol_org.sampling[1], vol_org.sampling[1], vol_org.sampling[2]]
s.sampling = s.vol.sampling
vol = s.vol
# Start visualization and GUI
fig = vv.figure(30); vv.clf()
fig.position = 0.00, 30.00, 944.00, 1002.00
a = vv.gca()
a.axis.axisColor = 1,1,1
a.axis.visible = True
a.bgcolor = 0,0,0
a.daspect = 1, 1, -1
lim = 2500
t = vv.volshow(vol, clim=(0, lim), renderStyle='mip')
pick3d(vv.gca(), vol)
b = model.Draw(mc='b', mw = 0, lc='g', alpha = 0.5)
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Model for LSPEAS %s - %s' % (ptcode[7:], ctcode))
# Add clickable nodes
t0 = time.time()
node_points = []
for i, node in enumerate(sorted(model.nodes())):
node_point = vv.solidSphere(translation = (node), scaling = (0.6,0.6,0.6))
node_point.faceColor = 'b'
node_point.alpha = 0.5
node_point.visible = True
node_point.node = node
node_point.nr = i
node_points.append(node_point)
t1 = time.time()
print('Clickable nodes created, which took %1.2f min.' % ((t1-t0)/60))
# list of correctly clicked nodes
selected_nodes_sum = set()
# Initialize labels
t0 = vv.Label(a, '\b{Node nr|location}: ', fontSize=11, color='w')
t0.position = 0.1, 25, 0.5, 20 # x (frac w), y, w (frac), h
t0.bgcolor = None
t0.visible = True
t1 = vv.Label(a, '\b{Nodepair}: ', fontSize=11, color='w')
t1.position = 0.1, 45, 0.5, 20
t1.bgcolor = None
t1.visible = True
# Initialize output variable to store pulsatility analysis
storeOutput = list()
def on_key(event):
if event.key == vv.KEY_ENTER:
# mogenlijkheden aantal nodes
# 1 voor relative beweging vanuit avg punt
# 2 voor onderlinge beweging tussen twee punten
# 3 voor hoek in punt 2 van punt 1 naar punt 3
if len(selected_nodes) == 1:
selectn1 = selected_nodes[0].node
n1index = selected_nodes[0].nr
n1Deforms = model.node[selectn1]['deforms']
output = point_pulsatility(selectn1, n1Deforms)
output['NodesIndex'] = [n1index]
# Store output with name
dialog_output = get_index_name()
output['Name'] = dialog_output
storeOutput.append(output)
# update labels
t1.text = '\b{Node}: %i' % (n1index)
t1.visible = True
print('selection of 1 node stored')
if len(selected_nodes) == 2:
# get nodes
selectn1 = selected_nodes[0].node
selectn2 = selected_nodes[1].node
# get index of nodes which are in fixed order
n1index = selected_nodes[0].nr
n2index = selected_nodes[1].nr
nindex = [n1index, n2index]
# get deforms of nodes
n1Deforms = model.node[selectn1]['deforms']
n2Deforms = model.node[selectn2]['deforms']
# get pulsatility
cl_merged = append_centerlines(allcenterlines)
output = point_to_point_pulsatility(cl_merged, selectn1,
n1Deforms, selectn2, n2Deforms, type='euclidian')
output['NodesIndex'] = nindex
# get distance_centerline
#dist_cl = dist_over_centerline(cl_merged, selectn1, selectn2, type='euclidian') # toegevoegd Mirthe
#dist_cl = dist_centerline_total(cl_merged, selectn1,
# n1Deforms, selectn2, n2Deforms, type='euclidian')
# Store output with name
dialog_output = get_index_name()
output['Name'] = dialog_output
storeOutput.append(output)
# update labels
t1.text = '\b{Node pair}: %i - %i' % (nindex[0], nindex[1])
t1.visible = True
print('selection of 2 nodes stored')
if len(selected_nodes) == 3:
# get nodes
selectn1 = selected_nodes[0].node
selectn2 = selected_nodes[1].node
selectn3 = selected_nodes[2].node
# get index of nodes which are in fixed order
n1index = selected_nodes[0].nr
n2index = selected_nodes[1].nr
n3index = selected_nodes[2].nr
nindex = [n1index, n2index, n3index]
# get deforms of nodes
n1Deforms = model.node[selectn1]['deforms']
n2Deforms = model.node[selectn2]['deforms']
n3Deforms = model.node[selectn3]['deforms']
# get angulation
output = line_line_angulation(selectn1,
n1Deforms, selectn2, n2Deforms, selectn3, n3Deforms)
output['NodesIndex'] = nindex
# Store output with name
dialog_output = get_index_name()
output['Name'] = dialog_output
storeOutput.append(output)
# update labels
t1.text = '\b{Nodes}: %i - %i - %i' % (nindex[0], nindex[1], nindex[2])
t1.visible = True
print('selection of 3 nodes stored')
if len(selected_nodes) > 3:
for node in selected_nodes:
node.faceColor = 'b'
selected_nodes.clear()
print('to many nodes selected, select 1,2 or 3 nodes')
if len(selected_nodes) < 1:
for node in selected_nodes:
node.faceColor = 'b'
selected_nodes.clear()
print('to few nodes selected, select 1,2 or 3 nodes')
# Visualize analyzed nodes and deselect
for node in selected_nodes:
selected_nodes_sum.add(node)
for node in selected_nodes_sum:
node.faceColor = 'g' # make green when analyzed
selected_nodes.clear()
if event.key == vv.KEY_ESCAPE:
# FINISH MODEL, STORE TO EXCEL
# Store to EXCEL
storeOutputToExcel(storeOutput, exceldir)
vv.close(fig)
print('output stored to excel')
selected_nodes = list()
def select_node(event):
""" select and deselect nodes by Double Click
"""
if event.owner not in selected_nodes:
event.owner.faceColor = 'r'
selected_nodes.append(event.owner)
elif event.owner in selected_nodes:
event.owner.faceColor = 'b'
selected_nodes.remove(event.owner)
def pick_node(event):
nodenr = event.owner.nr
node = event.owner.node
t0.text = '\b{Node nr|location}: %i | x=%1.3f y=%1.3f z=%1.3f' % (nodenr,node[0],node[1],node[2])
def unpick_node(event):
t0.text = '\b{Node nr|location}: '
def point_pulsatility(point1, point1Deforms):
n1Indices = point1 + point1Deforms
pos_combinations = list(itertools.combinations(range(len(point1Deforms)),2))
distances = []
for i in pos_combinations:
v = point1Deforms[i[0]] - point1Deforms[i[1]]
distances.append(((v[0]**2 + v[1]**2 + v[2]**2)**0.5 ))
distances = np.array(distances)
# get max distance between phases
point_phase_max = distances.max()
point_phase_max = [point_phase_max, [x*10 for x in (pos_combinations[list(distances).index(point_phase_max)])]]
# get min distance between phases
point_phase_min = distances.min()
point_phase_min = [point_phase_min, [x*10 for x in (pos_combinations[list(distances).index(point_phase_min)])]]
return {'point_phase_min':point_phase_min,'point_phase_max': point_phase_max, 'Node1': [point1, point1Deforms]}
def point_to_point_pulsatility(cl, point1, point1Deforms,
point2, point2Deforms,type='euclidian'):
import numpy as np
n1Indices = point1 + point1Deforms
n2Indices = point2 + point2Deforms
# define vector between nodes
v = n1Indices - n2Indices
distances = ( (v[:,0]**2 + v[:,1]**2 + v[:,2]**2)**0.5 ).reshape(-1,1)
# get min and max distance
point_to_pointMax = distances.max()
point_to_pointMin = distances.min()
# add phase in cardiac cycle where min and max where found (5th = 50%)
point_to_pointMax = [point_to_pointMax, (list(distances).index(point_to_pointMax) )*10]
point_to_pointMin = [point_to_pointMin, (list(distances).index(point_to_pointMin) )*10]
# get median of distances
point_to_pointMedian = np.percentile(distances, 50) # Q2
# median of the lower half, Q1 and upper half, Q3
point_to_pointQ1 = np.percentile(distances, 25)
point_to_pointQ3 = np.percentile(distances, 75)
# Pulsatility min max distance point to point
point_to_pointP = point_to_pointMax[0] - point_to_pointMin[0]
# add % change to pulsatility
point_to_pointP = [point_to_pointP, (point_to_pointP/point_to_pointMin[0])*100 ]
# find index of point on cll and calculate length change cll ???
if isinstance(cl, PointSet):
cl = np.asarray(cl).reshape((len(cl),3))
indpoint1 = np.where( np.all(cl == point1, axis=-1) )[0] # -1 counts from last to the first axis
indpoint2 = np.where( np.all(cl == point2, axis=-1) )[0] # renal point
n1Indices = point1 + point1Deforms
n2Indices = point2 + point2Deforms
clDeforms = []
clpart_deformed = []
vectors = []
clpart = []
d = []
dist_cl = []
clpartDeforms = []
clpart_deformed_test = []
for i in range(len(cl)):
clDeforms1 = model.node[cl[i,0], cl[i,1], cl[i,2]]['deforms']
clDeforms.append(clDeforms1)
clpart_deformed1 = cl[i] + clDeforms1
clpart_deformed.append(clpart_deformed1)
# clpart = cl[min(indpoint1[0], indpoint2[0]):max(indpoint1[0], indpoint2[0])+1]
clpart = clpart_deformed[min(indpoint1[0], indpoint2[0]):max(indpoint1[0], indpoint2[0])+1]
# for i in range(len(clpart)):
# clpartDeforms1 = model.node[clpart[i,0], clpart[i,1], clpart[i,2]]['deforms']
# clpartDeforms.append(clpartDeforms1)
# clpart_deformed1_test = cl[i] + clpartDeforms1
# clpart_deformed_test.append(clpart_deformed1_test)
# for k in range(len(n1Indices)):
# vectors_phases = np.vstack([clpart_deformed_test[i+1][k]-clpart_deformed_test[i][k] for i in range(len(clpart)-1)])
# vectors.append(vectors_phases)
for k in range(len(n1Indices)):
vectors_phases = np.vstack([clpart[i+1][k]-clpart[i][k] for i in range(len(clpart)-1)])
vectors.append(vectors_phases)
for i in range(len(vectors)):
if type == 'euclidian':
d1 = (vectors[i][:,0]**2 + vectors[i][:,1]**2 + vectors[i][:,2]**2)**0.5 # 3Dvector length in mm
d.append(d1)
elif type == 'z':
d = abs(vectors[i][:,2]) # x,y,z ; 1Dvector length in mm
for i in range(len(d)):
dist = d[i].sum()
dist_cl.append(dist)
#if indpoint2 > indpoint1: # stent point proximal to renal on centerline: positive
#dist_cl*=-1
cl_min_index1 = np.argmin(dist_cl)
cl_min_index = cl_min_index1*10
cl_min = min(dist_cl)
cl_max_index1 = np.argmax(dist_cl)
cl_max_index = cl_max_index1*10
cl_max = max(dist_cl)
print ([dist_cl])
print ([point1, point2])
return {'point_to_pointMin': point_to_pointMin,
'point_to_pointQ1': point_to_pointQ1,
'point_to_pointMedian': point_to_pointMedian,
'point_to_pointQ3': point_to_pointQ3,
'point_to_pointMax': point_to_pointMax,
'point_to_pointP': point_to_pointP,
'Node1': [point1, point1Deforms],
'Node2': [point2, point2Deforms], 'distances': distances,
'dist_cl': dist_cl, 'cl_min_index': cl_min_index,
'cl_max_index': cl_max_index, 'cl_min': cl_min, 'cl_max': cl_max}
def line_line_angulation(point1, point1Deforms, point2, point2Deforms, point3, point3Deforms):
n1Indices = point1 + point1Deforms
n2Indices = point2 + point2Deforms
n3Indices = point3 + point3Deforms
# get vectors
v1 = n1Indices - n2Indices
v2 = n3Indices - n2Indices
# get angles
angles = []
for i in range(len(v1)):
angles.append(math.degrees(math.acos((np.dot(v1[i],v2[i]))/
(np.linalg.norm(v1[i])*np.linalg.norm(v2[i])))))
angles = np.array(angles)
# get all angle differences of all phases
pos_combinations = list(itertools.combinations(range(len(v1)),2))
angle_diff = []
for i in pos_combinations:
v = point1Deforms[i[0]] - point1Deforms[i[1]]
angle_diff.append(abs(angles[i[0]] - angles[i[1]]))
angle_diff = np.array(angle_diff)
# get max angle differences
point_angle_diff_max = angle_diff.max()
point_angle_diff_max = [point_angle_diff_max, [x*10 for x in
(pos_combinations[list(angle_diff).index(point_angle_diff_max)])]]
# get min angle differences
point_angle_diff_min = angle_diff.min()
point_angle_diff_min = [point_angle_diff_min, [x*10 for x in
(pos_combinations[list(angle_diff).index(point_angle_diff_min)])]]
return {'point_angle_diff_min':point_angle_diff_min,
'point_angle_diff_max': point_angle_diff_max, 'angles': angles,
'Node1': [point1, point1Deforms], 'Node2': [point2, point2Deforms],
'Node3': [point3, point1Deforms]}
def append_centerlines(allcenterlines):
""" Merge seperated PointSet centerlines into one PointSet
"""
# cl_merged = allcenterlines[0]
cl_merged = PointSet(3)
for i in range(0,len(allcenterlines)):
for point in allcenterlines[i]:
cl_merged.append(point)
return cl_merged
def get_index_name():
# Gui for input name
app = QtGui.QApplication([])
m = MyDialog()
m.show()
m.exec_()
dialog_output = m.edit.text()
return dialog_output
def storeOutputToExcel(storeOutput, exceldir):
"""Create file and add a worksheet or overwrite existing
"""
# https://pypi.python.org/pypi/XlsxWriter
workbook = xlsxwriter.Workbook(os.path.join(exceldir,'storeOutput.xlsx'))
worksheet = workbook.add_worksheet('General')
# set column width
worksheet.set_column('A:A', 35)
worksheet.set_column('B:B', 30)
# add a bold format to highlight cells
bold = workbook.add_format({'bold': True})
# write title and general tab
worksheet.write('A1', 'Output ChEVAS dynamic CT, 10 Phases', bold)
analysisID = '%s_%s_%s' % (ptcode, ctcode, cropname)
worksheet.write('A2', 'Filename:', bold)
worksheet.write('B2', analysisID)
worksheet.write('A3', 'Date and Time:', bold)
date_time = datetime.now() #strftime("%d-%m-%Y %H:%M")
date_format_str = 'dd-mm-yyyy hh:mm'
date_format = workbook.add_format({'num_format': date_format_str,
'align': 'left'})
worksheet.write_datetime('B3', date_time, date_format)
# write 'storeOutput'
sort_index = []
for i in range(len(storeOutput)):
type = len(storeOutput[i]['NodesIndex'])
sort_index.append([i, type])
sort_index = np.array(sort_index)
sort_index = sort_index[sort_index[:,1].argsort()]
for i, n in sort_index:
worksheet = workbook.add_worksheet(storeOutput[i]['Name'])
worksheet.set_column('A:A', 35)
worksheet.set_column('B:B', 20)
worksheet.write('A1', 'Name:', bold)
worksheet.write('B1', storeOutput[i]['Name'])
if n == 1:
worksheet.write('A2', 'Type:', bold)
worksheet.write('B2', '1 Node')
worksheet.write('A3', 'Minimum translation (mm, Phases)',bold)
worksheet.write('B3', storeOutput[i]['point_phase_min'][0])
worksheet.write_row('C3', list(storeOutput[i]['point_phase_min'][1]))
worksheet.write('A4', 'Maximum translation (mm, Phases)',bold)
worksheet.write('B4', storeOutput[i]['point_phase_max'][0])
worksheet.write_row('C4', list(storeOutput[i]['point_phase_max'][1]))
worksheet.write('A5', 'Avg node position and deformations', bold)
worksheet.write('B5', str(list(storeOutput[i]['Node1'][0])))
worksheet.write_row('C5', [str(x)for x in list(storeOutput[i]['Node1'][1])])
worksheet.write('A6', 'Node Index Number', bold)
worksheet.write_row('B6', list(storeOutput[i]['NodesIndex']))
elif n == 2:
worksheet.write('A2', 'Type:', bold)
worksheet.write('B2', '2 Nodes')
worksheet.write('A3', 'Minimum distance (mm, Phases)',bold)
worksheet.write('B3', storeOutput[i]['point_to_pointMin'][0])
worksheet.write('C3', storeOutput[i]['point_to_pointMin'][1])
worksheet.write('A4', 'Q1 distance (mm)',bold)
worksheet.write('B4', storeOutput[i]['point_to_pointQ1'])
worksheet.write('A5', 'Median distance (mm)',bold)
worksheet.write('B5', storeOutput[i]['point_to_pointMedian'])
worksheet.write('A6', 'Q3 distance (mm)',bold)
worksheet.write('B6', storeOutput[i]['point_to_pointQ3'])
worksheet.write('A7', 'Maximum distance (mm, phases)',bold)
worksheet.write('B7', storeOutput[i]['point_to_pointMax'][0])
worksheet.write('C7', storeOutput[i]['point_to_pointMax'][1])
worksheet.write('A8', 'Maximum distance difference (mm)', bold)
worksheet.write('B8', storeOutput[i]['point_to_pointP'][0])
worksheet.write('A9', 'Distances for each phase', bold)
worksheet.write_row('B9', [str(x) for x in list(storeOutput[i]['distances'])])
worksheet.write('A10', 'Avg node1 position and deformations', bold)
worksheet.write('B10', str(list(storeOutput[i]['Node1'][0])))
worksheet.write_row('C10', [str(x) for x in list(storeOutput[i]['Node1'][1])])
worksheet.write('A11', 'Avg node2 position and deformations', bold)
worksheet.write('B11', str(list(storeOutput[i]['Node2'][0])))
worksheet.write_row('C11', [str(x) for x in list(storeOutput[i]['Node2'][1])])
worksheet.write('A12', 'Node Index Number', bold)
worksheet.write_row('B12', list(storeOutput[i]['NodesIndex']))
worksheet.write('A13', 'Length centerline', bold)
worksheet.write('B13', str(list(storeOutput[i]['dist_cl'])))
worksheet.write('A14', 'Minimum length centerline', bold)
worksheet.write('B14', storeOutput[i]['cl_min'])
worksheet.write('C14', storeOutput[i]['cl_min_index'])
worksheet.write('A15', 'Maximum length centerline', bold)
worksheet.write('B15', storeOutput[i]['cl_max'])
worksheet.write('C15', storeOutput[i]['cl_max_index'])
elif n == 3:
worksheet.write('A2', 'Type:', bold)
worksheet.write('B2', '3 Nodes')
worksheet.write('A3', 'Minimum angle difference (degrees, Phases)',bold)
worksheet.write('B3', storeOutput[i]['point_angle_diff_min'][0])
worksheet.write_row('C3', list(storeOutput[i]['point_angle_diff_min'][1]))
worksheet.write('A4', 'Maximum angle difference (degrees, Phases)',bold)
worksheet.write('B4', storeOutput[i]['point_angle_diff_max'][0])
worksheet.write_row('C4', list(storeOutput[i]['point_angle_diff_max'][1]))
worksheet.write('A5', 'Angles for each phase (degrees)',bold)
worksheet.write_row('B5', list(storeOutput[i]['angles']))
worksheet.write('A6', 'Avg node1 position and deformations', bold)
worksheet.write('B6', str(list(storeOutput[i]['Node1'][0])))
worksheet.write_row('C6', [str(x) for x in list(storeOutput[i]['Node1'][1])])
worksheet.write('A7', 'Avg node2 position and deformations', bold)
worksheet.write('B7', str(list(storeOutput[i]['Node2'][0])))
worksheet.write_row('C7', [str(x) for x in list(storeOutput[i]['Node2'][1])])
worksheet.write('A8', 'Avg node2 position and deformations', bold)
worksheet.write('B8', str(list(storeOutput[i]['Node3'][0])))
worksheet.write_row('C8', [str(x) for x in list(storeOutput[i]['Node3'][1])])
worksheet.write('A9', 'Node Index Number', bold)
worksheet.write_row('B9', list(storeOutput[i]['NodesIndex']))
workbook.close()
# Bind event handlers
fig.eventKeyDown.Bind(on_key)
for node_point in node_points:
node_point.eventDoubleClick.Bind(select_node)
node_point.eventEnter.Bind(pick_node)
node_point.eventLeave.Bind(unpick_node)
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 __init__(self,
ptcode,
ctcode,
StartPoints,
EndPoints,
basedir,
modelname='modelavgreg'):
""" with start and endpoints provided, calculate centerline and save as
ssdf in basedir as model and dynamic model
"""
#todo: name of dynamic model is now deforms, unclear, should be dynamic
#import numpy as np
import visvis as vv
import numpy as np
import os
import copy
from stentseg.utils import PointSet, _utils_GUI
from stentseg.utils.centerline import (find_centerline,
points_from_nodes_in_graph,
points_from_mesh,
smooth_centerline)
from stentseg.utils.datahandling import loadmodel, loadvol
from stentseg.utils.visualization import show_ctvolume
from stentseg.utils.picker import pick3d
stentnr = len(StartPoints)
cropname = 'prox'
what = modelname
what_vol = 'avgreg'
vismids = True
m = loadmodel(basedir, ptcode, ctcode, cropname, what)
s = loadvol(basedir, ptcode, ctcode, cropname, what_vol)
s.vol.sampling = [s.sampling[1], s.sampling[1], s.sampling[2]]
s.sampling = s.vol.sampling
start1 = StartPoints.copy()
ends = EndPoints.copy()
from stentseg.stentdirect import stentgraph
ppp = points_from_nodes_in_graph(m.model)
allcenterlines = [] # for pp
allcenterlines_nosmooth = [] # for pp
centerlines = [] # for stentgraph
nodes_total = stentgraph.StentGraph()
for j in range(stentnr):
if j == 0 or not start1[j] == ends[j - 1]:
# if first stent or when stent did not continue with this start point
nodes = stentgraph.StentGraph()
centerline = PointSet(3) # empty
# Find main centerline
# if j > 3: # for stent with midpoints
# centerline1 = find_centerline(ppp, start1[j], ends[j], step= 1,
# ndist=10, regfactor=0.5, regsteps=10, verbose=False)
#else:
centerline1 = find_centerline(ppp,
start1[j],
ends[j],
step=1,
ndist=10,
regfactor=0.5,
regsteps=1,
verbose=False)
# centerline1 is a PointSet
print('Centerline calculation completed')
# ========= Maaike =======
smoothfactor = 15 # Mirthe used 2 or 4
# check if cll continued here from last end point
if not j == 0 and start1[j] == ends[j - 1]:
# yes we continued
ppart = centerline1[:
-1] # cut last but do not cut first point as this is midpoint
else:
# do not use first points, as they are influenced by user selected points
ppart = centerline1[1:-1]
for p in ppart:
centerline.append(p)
# if last stent or stent does not continue with next start-endpoint
if j == stentnr - 1 or not ends[j] == start1[j + 1]:
# store non-smoothed for vis
allcenterlines_nosmooth.append(centerline)
pp = smooth_centerline(centerline, n=smoothfactor)
# add pp to list
allcenterlines.append(pp) # list with PointSet per centerline
self.allcenterlines = allcenterlines
# add pp as nodes
for i, p in enumerate(pp):
p_as_tuple = tuple(p.flat)
nodes.add_node(p_as_tuple)
nodes_total.add_node(p_as_tuple)
# add pp as one edge so that pathpoints are in fixed order
pstart = tuple(pp[0].flat)
pend = tuple(pp[-1].flat)
nodes.add_edge(pstart, pend, path=pp)
nodes_total.add_edge(pstart, pend, path=pp)
# add final centerline nodes model to list
centerlines.append(nodes)
# ========= Maaike =======
## Store segmentation to disk
# Build struct
s2 = vv.ssdf.new()
s2.sampling = s.sampling
s2.origin = s.origin
s2.stenttype = m.stenttype
s2.croprange = m.croprange
for key in dir(m):
if key.startswith('meta'):
suffix = key[4:]
s2['meta' + suffix] = m['meta' + suffix]
s2.what = what
s2.params = s.params #reg
s2.paramsseeds = m.params
s2.stentType = 'nellix'
s2.StartPoints = StartPoints
s2.EndPoints = EndPoints
# keep centerlines as pp also [Maaike]
s2.ppallCenterlines = allcenterlines
for k in range(len(allcenterlines)):
suffix = str(k)
pp = allcenterlines[k]
s2['ppCenterline' + suffix] = pp
s3 = copy.deepcopy(s2)
s3['model'] = nodes_total.pack()
# Store model for each centerline
for j in range(len(centerlines)):
suffix = str(j)
model = centerlines[j]
s2['model' + suffix] = model.pack()
# Save model with seperate centerlines.
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'centerline_' + what)
vv.ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk as {}.'.format(filename))
# Save model with combined centerlines
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'centerline_total_' + what)
vv.ssdf.save(os.path.join(basedir, ptcode, filename), s3)
print('saved to disk as {}.'.format(filename))
# remove intermediate centerline points
# start1 = map(tuple, start1)
# ends = map(tuple, ends)
startpoints_clean = copy.deepcopy(start1)
endpoints_clean = copy.deepcopy(ends)
duplicates = list(set(start1) & set(ends))
for i in range(len(duplicates)):
startpoints_clean.remove(duplicates[i])
endpoints_clean.remove(duplicates[i])
#Visualize
f = vv.figure(10)
vv.clf()
a1 = vv.subplot(121)
a1.daspect = 1, 1, -1
vv.plot(ppp, ms='.', ls='', alpha=0.6, mw=2)
for j in range(len(startpoints_clean)):
vv.plot(PointSet(list(startpoints_clean[j])),
ms='.',
ls='',
mc='g',
mw=20) # startpoint green
vv.plot(PointSet(list(endpoints_clean[j])),
ms='.',
ls='',
mc='r',
mw=20) # endpoint red
for j in range(len(allcenterlines)):
vv.plot(allcenterlines[j], ms='.', ls='', mw=10, mc='y')
vv.title('Centerlines and seed points')
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
# for j in range(len(allcenterlines_nosmooth)):
# vv.plot(allcenterlines_nosmooth[j], ms='o', ls='', mw=10, mc='c', alpha=0.6)
a2 = vv.subplot(122)
a2.daspect = 1, 1, -1
vv.plot(ppp, ms='.', ls='', alpha=0.6, mw=2)
# vv.volshow(s.vol, clim=clim, renderStyle = 'mip')
t = show_ctvolume(s.vol,
axis=a2,
showVol='ISO',
clim=(0, 2500),
isoTh=250,
removeStent=False,
climEditor=True)
label = pick3d(vv.gca(), s.vol)
for j in range(len(startpoints_clean)):
vv.plot(PointSet(list(startpoints_clean[j])),
ms='.',
ls='',
mc='g',
mw=20,
alpha=0.6) # startpoint green
vv.plot(PointSet(list(endpoints_clean[j])),
ms='.',
ls='',
mc='r',
mw=20,
alpha=0.6) # endpoint red
for j in range(len(allcenterlines)):
vv.plot(allcenterlines[j], ms='o', ls='', mw=10, mc='y', alpha=0.6)
# show midpoints (e.g. duplicates)
if vismids:
for p in duplicates:
vv.plot(p[0], p[1], p[2], mc='m', ms='o', mw=10, alpha=0.6)
a2.axis.visible = False
vv.title('Centerlines and seed points')
a1.camera = a2.camera
f.eventKeyDown.Bind(
lambda event: _utils_GUI.RotateView(event, [a1, a2]))
f.eventKeyDown.Bind(
lambda event: _utils_GUI.ViewPresets(event, [a1, a2]))
# Pick node for midpoint to redo get_centerline
self.pickedCLLpoint = _utils_GUI.Event_pick_graph_point(
nodes_total, s.vol, label, nodesOnly=True) # x,y,z
# use key p to select point
#===============================================================================
vv.figure(11)
vv.gca().daspect = 1, 1, -1
t = show_ctvolume(s.vol,
showVol='ISO',
clim=(0, 2500),
isoTh=250,
removeStent=False,
climEditor=True)
label2 = pick3d(vv.gca(), s.vol)
for j in range(len(startpoints_clean)):
vv.plot(PointSet(list(startpoints_clean[j])),
ms='.',
ls='',
mc='g',
mw=20,
alpha=0.6) # startpoint green
vv.plot(PointSet(list(endpoints_clean[j])),
ms='.',
ls='',
mc='r',
mw=20,
alpha=0.6) # endpoint red
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
#===============================================================================
## Make model dynamic (and store/overwrite to disk)
import pirt
from stentseg.motion.dynamic import incorporate_motion_nodes, incorporate_motion_edges
# Load deforms
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'deforms')
s1 = vv.ssdf.load(os.path.join(basedir, ptcode, filename))
deformkeys = []
for key in dir(s1):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s1[key] for key in deformkeys]
deforms = [
pirt.DeformationFieldBackward(*fields) for fields in deforms
]
for i in range(len(deforms)):
deforms[i]._field_sampling = tuple(s1.sampling)
paramsreg = s1.params
# Load model
s2 = loadmodel(basedir, ptcode, ctcode, cropname, 'centerline_' + what)
s3 = loadmodel(basedir, ptcode, ctcode, cropname,
'centerline_total_' + what)
# Combine ...
for key in dir(s2):
if key.startswith('model'):
incorporate_motion_nodes(s2[key], deforms, s.origin)
incorporate_motion_edges(s2[key], deforms, s.origin)
model = s2[key]
s2[key] = model.pack()
# Combine ...
for key in dir(s3):
if key.startswith('model'):
incorporate_motion_nodes(s3[key], deforms, s.origin)
incorporate_motion_edges(s3[key], deforms, s.origin)
model = s3[key]
s3[key] = model.pack()
# Save
s2.paramsreg = paramsreg
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname,
'centerline_' + what + '_deforms')
vv.ssdf.save(os.path.join(basedir, ptcode, filename), s2)
print('saved to disk as {}.'.format(filename))
# Save
s3.paramsreg = paramsreg
filename = '%s_%s_%s_%s.ssdf' % (
ptcode, ctcode, cropname, 'centerline_total_' + what + '_deforms')
vv.ssdf.save(os.path.join(basedir, ptcode, filename), s3)
print('saved to disk as {}.'.format(filename))
renal1_and_cl_point[0])
# Main outcome 1: distance 2nd ring valleys to renal
# Main outcome 2: migration 2nd ring valleys from discharge to 1, 6, 12 months
## Visualize
f = vv.figure(2)
vv.clf()
f.position = 0.00, 22.00, 1920.00, 1018.00
alpha = 0.5
if ctcode2:
a1 = vv.subplot(121)
else:
a1 = vv.gca()
show_ctvolume(vol1, model1, showVol=showVol, clim=clim0, isoTh=isoTh)
pick3d(vv.gca(), vol1)
model1.Draw(mc='b', mw=10, lc='g')
vm = vv.mesh(modelmesh1)
vm.faceColor = 'g'
# m = vv.mesh(vessel1)
# m.faceColor = (1,0,0, alpha) # red
# vis vessel, centerline, renal origo, peaks valleys R1
vv.plot(ppvessel1, ms='.', ls='', mc='r', alpha=0.2, mw=7, axes=a1) # vessel
vv.plot(PointSet(list(c1_start1)), ms='.', ls='', mc='g', mw=18,
axes=a1) # start1
vv.plot([e[0] for e in c1_ends], [e[1] for e in c1_ends],
[e[2] for e in c1_ends],
ms='.',
ls='',
mc='b',
model = s.model
model2 = model.copy()
# Load static CT image to add as reference
s2 = loadvol(basedir, ptcode, ctcode, cropname, 'avgreg')
vol = s2.vol
f = vv.figure(1)
vv.clf()
a = vv.subplot(1, 2, 1)
a.axis.axisColor = 1, 1, 1
a.axis.visible = False
a.bgcolor = 0, 0, 0
a.daspect = 1, 1, -1
t = vv.volshow(vol, clim=(0, 2500), renderStyle='mip')
label = pick3d(a, vol)
# model.Draw(mc='b', mw = 10, lc='g')
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
vv.title('Model for LSPEAS %s - %s' % (ptcode[7:], ctcode))
# get hooks and struts
model_struts, model_hooks, model_R1R2, model_h_s, model_noHooks = get_model_struts(
model, nstruts=8)
model_R1R2.Draw(mc='r', mw=10, lc='r')
model_noHooks.Draw(mc='b', mw=10, lc='b')
model_struts.Draw(mc='y', mw=10, lc='y')
a2 = vv.subplot(1, 2, 2)
a2.axis.axisColor = 1, 1, 1