def figparts():
""" Visualize ring parts
"""
fig = vv.figure(4);
fig.position = 8.00, 30.00, 944.00, 1002.00
vv.clf()
a0 = vv.subplot(121)
show_ctvolume(vol, model, showVol=showVol, clim=clim0, isoTh=isoTh)
modelR1, modelR2 = modelsR1R2[0][0], modelsR1R2[0][1]
modelR1.Draw(mc='g', mw = 10, lc='g') # R1 = green
modelR2.Draw(mc='c', mw = 10, lc='c') # R2 = cyan
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Analysis for model LSPEAS %s - %s' % (ptcode[7:], ctcode))
a0.axis.axisColor= 1,1,1
a0.bgcolor= 0,0,0
a0.daspect= 1, 1, -1 # z-axis flipped
a0.axis.visible = showAxis
a1 = vv.subplot(122)
show_ctvolume(vol, model, showVol=showVol, clim=clim0, isoTh=isoTh)
models[0][0].Draw(mc='y', mw = 10, lc='y') # struts = yellow
models[0][1].Draw(mc='r', mw = 10, lc='r') # hooks = red
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Analysis for model LSPEAS %s - %s' % (ptcode[7:], ctcode))
a1.axis.axisColor= 1,1,1
a1.bgcolor= 0,0,0
a1.daspect= 1, 1, -1 # z-axis flipped
a1.axis.visible = showAxis
a0.camera = a1.camera
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 vis3Dfit(fitted, vol, model, ptcode, ctcode, showAxis, **kwargs):
"""Visualize ellipse fit in 3D with CT volume in current axis
input: fitted = _fit3D output = (pp3, plane, pp3_2, e3)
"""
from stentseg.utils import fitting
import numpy as np
pp3,plane,pp3_2,e3 = fitted[0],fitted[1],fitted[2],fitted[3]
a = vv.gca()
# show_ctvolume(vol, model, showVol=showVol, clim=clim0, isoTh=isoTh)
show_ctvolume(vol, model, **kwargs)
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Ellipse fit for model %s - %s' % (ptcode[7:], ctcode))
a.axis.axisColor= 1,1,1
a.bgcolor= 0,0,0
a.daspect= 1, 1, -1 # z-axis flipped
a.axis.visible = showAxis
# For visualization, calculate 4 points on rectangle that lies on the plane
x1, x2 = pp3.min(0)[0]-0.3, pp3.max(0)[0]+0.3
y1, y2 = pp3.min(0)[1]-0.3, pp3.max(0)[1]+0.3
p1 = x1, y1, -(x1*plane[0] + y1*plane[1] + plane[3]) / plane[2]
p2 = x2, y1, -(x2*plane[0] + y1*plane[1] + plane[3]) / plane[2]
p3 = x2, y2, -(x2*plane[0] + y2*plane[1] + plane[3]) / plane[2]
p4 = x1, y2, -(x1*plane[0] + y2*plane[1] + plane[3]) / plane[2]
vv.plot(pp3, ls='', ms='.', mc='y', mw = 10)
vv.plot(fitting.project_from_plane(pp3_2, plane), lc='r', ls='', ms='.', mc='r', mw=9)
# vv.plot(fitting.project_from_plane(fitting.sample_circle(c3), plane), lc='r', lw=2)
vv.plot(fitting.project_from_plane(fitting.sample_ellipse(e3), plane), lc='b', lw=2)
vv.plot(np.array([p1, p2, p3, p4, p1]), lc='g', lw=2)
# vv.legend('3D points', 'Projected points', 'Circle fit', 'Ellipse fit', 'Plane fit')
vv.legend('3D points', 'Projected points', 'Ellipse fit', 'Plane fit')
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
dist_for_R1_post = dist_over_centerline(centerline1, R1_post_and_cl_point[0],
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='',
showAxis = True # True or False
showVol = 'MIP' # MIP or ISO or 2D or None
ringpart = True # True; False
nstruts = 8
clim0 = (0,3000)
# clim0 = -550,500
clim2 = (0,4)
radius = 0.07
dimensions = 'xyz'
isoTh = 250
## Visualize with GUI
f = vv.figure(3); vv.clf()
f.position = 968.00, 30.00, 944.00, 1002.00
a = vv.gca()
show_ctvolume(vol, model, showVol=showVol, clim=clim0, isoTh=isoTh)
model.Draw(mc='b', mw = 10, lc='g')
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Analysis for model LSPEAS %s - %s' % (ptcode[7:], ctcode))
a.axis.axisColor= 1,1,1
a.bgcolor= 0,0,0
a.daspect= 1, 1, -1 # z-axis flipped
a.axis.visible = showAxis
# Initialize labels GUI
from visvis import Pointset
from stentseg.stentdirect import stentgraph
t1 = vv.Label(a, 'Edge ctvalue: ', fontSize=11, color='c')
t1.position = 0.1, 5, 0.5, 20 # x (frac w), y, w (frac), h
t1.bgcolor = None
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) )
#===============================================================================
## 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
]
# aanpassingen voor scale en origin
vol_zoom_type = vv.Aarray(vol_zoom, s0[key].sampling, s0[key].origin)
vol = vol_zoom_type
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'):
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))
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
f = vv.figure()
vv.clf()
f.position = 0.00, 22.00, 1920.00, 1018.00
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
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])
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 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
