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 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 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 loadvolmodel(basedir,
ptcode,
ctcode1,
cropname,
modelname,
nstruts=8,
ringpart=False):
""" load vol and model
"""
s1 = loadmodel(basedir, ptcode, ctcode1, cropname, modelname)
model = s1.model
models1 = []
for ringname in ringnames:
model1 = s1[ringname]
if ringpart:
models = get_model_struts(model1, nstruts=nstruts)
modelRs = get_model_rings(models[2]) # model_R1R2
model1 = modelRs[ringpart - 1] # R1 or R2
models1.append(model1)
vol1 = loadvol(basedir, ptcode, ctcode1, cropname, 'avgreg').vol
return vol1, models1, model
def __init__(self, ptcode, ctcode, basedir, clim=None):
""" select start and endpoints to be used for centerline generation
"""
from stentseg.apps._3DPointSelector import select3dpoints
# from stentseg.apps.ui_dialog import MyDialog
# from PyQt4 import QtGui
import imageio
import os
from stentseg.utils.datahandling import select_dir, loadvol
import copy
# Select dataset to register
cropname = 'prox'
what = 'avgreg'
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, what)
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
# # Select nr of stents
# app = QtGui.QApplication([])
# m = MyDialog()
# m.show()
# m.exec_()
# nr_of_stents = int(m.combo.currentText())
# Endpoint selection
points = select3dpoints(s.vol, nr_of_stents=6, clim=clim)
self.StartPoints = points[0]
self.EndPoints = points[1]
print('StartPoints are: ' + str(self.StartPoints))
print('EndPoints are: ' + str(self.EndPoints))
drawVessel = True
clim = (0, 2500)
clim2D = -200, 500 # MPR
clim2 = (0, 2)
isoTh = 180 # 250
## Load data
# Load CT image data for reference, and deform data to measure motion
try:
# If we run this script without restart, we can re-use volume and deforms
vol1
deforms
except NameError:
vol1 = loadvol(basedir, ptcode, ctcode1, cropvol, 'avgreg').vol
s_deforms = loadvol(basedir, ptcode, ctcode1, cropvol, 'deforms')
deforms = [
s_deforms[key] for key in dir(s_deforms) if key.startswith('deform')
]
deforms = [pirt.DeformationFieldBackward(*fields) for fields in deforms]
# Load vessel mesh (mimics)
# We make sure that it is a mesh without faces, which makes our sampling easier
try:
ppvessel
except NameError:
# Load mesh with visvis, then put in our meshlib.Mesh() and let it ensure that
# the mesh is closed, check the winding, etc. so that we can cut it with planes,
# and reliably calculate volume.
filename = '{}_{}_neck.stl'.format(ptcode, ctcode1)
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)
from stentseg.utils.visualization import DrawModelAxes
import visvis as vv
from stentseg.utils import _utils_GUI
# Select the ssdf basedir
basedir = select_dir(os.getenv('LSPEAS_BASEDIR', ''), r'D:\LSPEAS\LSPEAS_ssdf',
r'F:\LSPEAS_ssdf_backup', r'G:\LSPEAS_ssdf_backup')
# Select dataset to register
ptcode = 'LSPEAS_008'
ctcode = '1month'
cropname = 'stent'
what = 'phases' # avgreg
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, what)
vol = s.vol80
clim = (0, 2500)
# clim = (-100,300)
showVol = '2D'
fig = vv.figure(2)
vv.clf()
fig.position = 0.00, 22.00, 1920.00, 1018.00
label = DrawModelAxes(vol, clim=clim, showVol=showVol) # lc, mc
a = vv.gca()
# bind rotate view [a,d rotate; z,x axes]
fig.eventKeyDown.Bind(lambda event: _utils_GUI.RotateView(event, [a]))
for i, vol in enumerate(vols2):
print(vol.meta.sampling)
phase = int(vol.meta.SeriesDescription[:1])
vols[phase] = vol
for j, vol in enumerate(vols):
print(vol.meta.SeriesDescription)
assert vol.shape == vols[0].shape
assert str(j * 10) in vol.meta.SeriesDescription # 0% , 10% etc.
## Step B: Crop and Save SSDF
for cropname in cropnames:
savecropvols(vols, basedir, ptcode, ctcode, cropname, stenttype)
## Visualize result
s1 = loadvol(basedir, ptcode, ctcode, cropnames[0], what='10phases')
vol1 = s1.vol40
vol2 = s1.vol90
# Visualize and compare
colormap = {
'r': [(0.0, 0.0), (0.17727272, 1.0)],
'g': [(0.0, 0.0), (0.27272728, 1.0)],
'b': [(0.0, 0.0), (0.34545454, 1.0)],
'a': [(0.0, 1.0), (1.0, 1.0)]
}
import visvis as vv
fig = vv.figure(1)
vv.clf()
fig.position = 0, 22, 1366, 706
# Select the ssdf basedir
basedir = select_dir(r'D:\LSPEAS\LSPEAS_ssdf', r'F:\LSPEAS_ssdf_backup',
r'G:\LSPEAS_ssdf_backup')
basedirstl = select_dir(
r'D:\Profiles\koenradesma\SURFdrive\UTdrive\LSPEAS\Analysis\Leg angulation',
r'C:\Users\Maaike\SURFdrive\UTdrive\LSPEAS\Analysis\Leg angulation')
# Select dataset
ptcode = 'LSPEAS_008'
ctcode = 'discharge'
cropname = 'stent'
what = 'centerline'
# 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 centerline mat
matName = '%s_%s_%s_%s.mat' % (ptcode, ctcode, cropname, what)
centerlineMat = scipy.io.loadmat(os.path.join(basedirstl, ptcode, matName))
# Load model
s = loadmodel(basedirstl, ptcode, ctcode, cropname, what)
for key in dir(s):
def __init__(self, dicom_basedir, ptcode, ctcode, basedir):
import imageio
#import easygui
from stentseg.utils.datahandling import loadvol
from stentseg.utils.datahandling import savecropvols, saveaveraged
## Select base directory for LOADING DICOM data
#dicom_basedir = easygui.diropenbox()
print('DICOM Path = ', dicom_basedir)
#ctcode = '12months' # 'pre', 'post_x', '12months'
stenttype = 'nellix'
## Select base directory to SAVE SSDF
#basedir = easygui.diropenbox()
print('Base Path = ', basedir)
# Set which crops to save
cropnames = ['prox'] #,'stent'] # ['ring'] or ['ring','stent'] or ..
#===============================================================================
## Step A: read single volumes to get vols:
# folder1 = '10%'
# folder2 = '60%'
# vol1 = imageio.volread(os.path.join(dicom_basedir, folder1), 'dicom')
# vol2 = imageio.volread(os.path.join(dicom_basedir, folder2), 'dicom')
# print( )
#
# if vol1.meta.SeriesDescription[:2] < vol2.meta.SeriesDescription[:2]:
# vols4078 = [vol1,vol2]
# else:
# vols4078 = [vol2,vol1]
#
# vols = vols4078.copy()
#
# for vol in vols:
# vol.meta.PatientName = ptcode # anonimyze
# vol.meta.PatientID = 'anonymous'
# print(vol.meta.SeriesDescription,'-', vol.meta.sampling)
#===============================================================================
##Orginele code
#===============================================================================
#
# folder1 = '40% iDose'
# folder2 = '78 iDose'
# vol1 = imageio.volread(os.path.join(dicom_basedir, folder1), 'dicom')
# vol2 = imageio.volread(os.path.join(dicom_basedir, folder2), 'dicom')
# print( )
#
# if vol1.meta.SeriesDescription[:2] < vol2.meta.SeriesDescription[:2]:
# vols4078 = [vol1,vol2]
# else:
# vols4078 = [vol2,vol1]
#
# vols = vols4078.copy()
#
# for vol in vols:
# vol.meta.PatientName = ptcode # anonimyze
# vol.meta.PatientID = 'anonymous'
# print(vol.meta.SeriesDescription,'-', vol.meta.sampling)
#===============================================================================
## Step A: read 10 volumes to get vols
# Deze zoekt alle mappen en dat zijn er dus 10 maar niet in de goede volgorde
vols2 = [
vol2 for vol2 in imageio.get_reader(dicom_basedir, 'DICOM', 'V')
]
vols = [None] * len(vols2)
for i, vol in enumerate(vols2):
# print(vol.meta.sampling)
print(vol.meta.SeriesDescription)
phase = int(vol.meta.SeriesDescription[:1])
# use phase to fix order of phases
vols[phase] = vol
#vols[phase].meta.ImagePositionPatient = (0.0,0.0,0.0)
for i, vol in enumerate(
vols): #wat ik heb veranderd is i, en enumerate()
print(vol.meta.SeriesDescription)
assert vol.shape == vols[0].shape
assert str(i * 10) in vol.meta.SeriesDescription # 0% , 10% etc.
## Step B: Crop and Save SSDF
# 1 of 2 cropnames opgeven voor opslaan 1 of 2 crpos.
# Het eerste volume wordt geladen in MIP, crop met marges van minimaal 30 mm
for cropname in cropnames:
savecropvols(vols, basedir, ptcode, ctcode, cropname, stenttype)
# saveaveraged(basedir, ptcode, ctcode, cropname, range(0,100,10))
## Visualize result
#s1 = loadvol(basedir, ptcode, ctcode, cropnames[0], what ='10avgreg')
#s2 = loadvol(basedir, ptcode, ctcode, cropnames[0], what ='10phases')
s1 = loadvol(basedir, ptcode, ctcode, cropnames[0], what='phases')
#s2 = loadvol(basedir, ptcode, ctcode, cropnames[0], what = 'avg010')
#vol1 = s1.vol
vol1 = s1.vol40
# Visualize and compare
colormap = {
'r': [(0.0, 0.0), (0.17727272, 1.0)],
'g': [(0.0, 0.0), (0.27272728, 1.0)],
'b': [(0.0, 0.0), (0.34545454, 1.0)],
'a': [(0.0, 1.0), (1.0, 1.0)]
}
import visvis as vv
fig = vv.figure(1)
vv.clf()
fig.position = 0, 22, 1366, 706
a1 = vv.subplot(111)
a1.daspect = 1, 1, -1
# t1 = vv.volshow(vol1, clim=(0, 3000), renderStyle='iso') # iso or mip
# t1.isoThreshold = 600 # stond op 400 maar je moet hoger zetten als je alleen stent wil
# t1.colormap = colormap
a1 = vv.volshow2(vol1, clim=(-500, 1500), renderStyle='mip')
vv.xlabel('x'), vv.ylabel('y'), vv.zlabel('z')
# vv.title('One volume at %i procent of cardiac cycle' % phase )
vv.title('Vol40')
from stentseg.utils.visualization import DrawModelAxes, show_ctvolume
from stentseg.utils.utils_graphs_pointsets import get_graph_in_phase
from stentseg.utils.picker import pick3d
basedir = select_dir(r'E:\Nellix_chevas\CT_SSDF\SSDF_automated',
r'D:\Nellix_chevas_BACKUP\CT_SSDF\SSDF_automated')
ptcode = 'chevas_09_thin'
ctcode = '12months'
phases = range(10) # all 10 phases
showmodelavgreg = True
showvol = True
# get vol for reference
s = loadvol(basedir, ptcode, ctcode, 'prox', what='avgreg')
# set sampling for cases where this was not stored correctly
s.vol.sampling = [s.sampling[1], s.sampling[1], s.sampling[2]]
vol = s.vol
s_modelcll = loadmodel(basedir,
ptcode,
ctcode,
'prox',
modelname='centerline_total_modelavgreg_deforms')
# get graph
modelcll = s_modelcll.model
s_modelcll_vessel = loadmodel(basedir,
ptcode,
ctcode,
else:
vol = imageio.volread(os.path.join(dicom_basedir, ptcode, ctcode), 'dicom')
print ()
print(vol.meta.SeriesDescription)
print(vol.meta.sampling)
print()
# Step B: Crop and Save SSDF
vols = [vol]
for cropname in cropnames:
savecropvols(vols, ssdf_basedir, ptcode, ctcode, cropname, stenttype)
## Visualize result
s1 = loadvol(ssdf_basedir, ptcode, ctcode, cropnames[0], what ='phase')
vol = s1.vol
# Visualize and compare
colormap = {'r': [(0.0, 0.0), (0.17727272, 1.0)],
'g': [(0.0, 0.0), (0.27272728, 1.0)],
'b': [(0.0, 0.0), (0.34545454, 1.0)],
'a': [(0.0, 1.0), (1.0, 1.0)]}
import visvis as vv
fig = vv.figure(1); vv.clf()
fig.position = 0, 22, 1366, 706
a = vv.gca()
a.daspect = 1,1,-1
t1 = vv.volshow(vol, clim=(0, 2500), renderStyle='iso') # iso or mip
t1.isoThreshold = 400
def showVolPhases(basedir, vols=None, ptcode=None, ctcode=None, cropname=None,
showVol='iso', mipIsocolor=False, isoTh=310,
slider=False, clim=(0,3000), clim2D=(-550, 500), fname=None):
""" Show vol phases in motion container
showVol= mip or iso or 2D; Provide either vols or location
"""
if vols is None:
# Load volumes
s = loadvol(basedir, ptcode, ctcode, cropname, 'phases', fname=fname)
vols = []
for key in dir(s):
if key.startswith('vol'):
vols.append(s[key])
# Start vis
f = vv.figure(1); vv.clf()
f.position = 9.00, 38.00, 992.00, 944.00
a = vv.gca()
a.daspect = 1, 1, -1
a.axis.axisColor = 1,1,1
a.axis.visible = False
a.bgcolor = 0,0,0
if showVol=='mip':
if not ptcode is None and not ctcode is None:
vv.title('Maximum intensity projection cine-loop of the original ECG-gated CT volumes of patient %s at %s ' % (ptcode[8:], ctcode))
else:
vv.title('Maximum intensity projection cine-loop of the original ECG-gated CT volumes ')
else:
if not ptcode is None and not ctcode is None:
vv.title('ECG-gated CT scan cine-loop of the original ECG-gated CT volumes of patient %s at %s ' % (ptcode[8:], ctcode))
else:
vv.title('ECG-gated CT scan cine-loop of the original ECG-gated CT volumes ')
# Setup data container
container = vv.MotionDataContainer(a)
for vol in vols:
if showVol == '2D':
t = vv.volshow2(vol, clim=clim2D) # -750, 1000
t.parent = container
else:
t = vv.volshow(vol, clim=clim, renderStyle = showVol)
t.parent = container
if showVol == 'iso':
t.isoThreshold = isoTh # iso or mip work well
t.colormap = {'r': [(0.0, 0.0), (0.17727272, 1.0)],
'g': [(0.0, 0.0), (0.27272728, 1.0)],
'b': [(0.0, 0.0), (0.34545454, 1.0)],
'a': [(0.0, 1.0), (1.0, 1.0)]}
if mipIsocolor:
t.colormap = {'r': [(0.0, 0.0), (0.17727272, 1.0)],
'g': [(0.0, 0.0), (0.27272728, 1.0)],
'b': [(0.0, 0.0), (0.34545454, 1.0)],
'a': [(0.0, 1.0), (1.0, 1.0)]}
# bind ClimEditor to figure
if slider:
if showVol=='mip':
c = vv.ClimEditor(vv.gcf())
c.position = (10, 50)
f.eventKeyDown.Bind(lambda event: _utils_GUI.ShowHideSlider(event, c) )
if showVol=='iso':
c = IsoThEditor(vv.gcf())
c.position = (10, 50)
f.eventKeyDown.Bind(lambda event: _utils_GUI.ShowHideSlider(event, c) )
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('------------------------')
return t
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) )
from stentseg.utils import PointSet, _utils_GUI, visualization
basedir = select_dir(os.getenv('LSPEAS_BASEDIR',
''), r'D:\LSPEAS\LSPEAS_ssdf',
r'F:\LSPEAS_ssdf_BACKUP', r'G:\LSPEAS_ssdf_BACKUP')
ptcode = 'LSPEAS_025'
ctcode = '1month'
cropname = 'ring'
modelname = 'modelavgreg'
s = loadmodel(basedir, ptcode, ctcode, cropname, modelname)
model = s.model.copy()
# Load volume
s_vol = loadvol(basedir, ptcode, ctcode, cropname, 'avgreg')
vol = s_vol.vol
# Load deforms
s_deforms = loadvol(basedir, ptcode, ctcode, cropname, 'deforms')
deformkeys = []
for key in dir(s_deforms):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s_deforms[key] for key in deformkeys]
deforms = [pirt.DeformationFieldBackward(*fields) for fields in deforms]
selected_nodes = list()
node_points, t3 = nodeInteraction(model, vol, selected_nodes)
print(s.origin) # for same crop the origins should be the same
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
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))
print("avgreg saved to disk.")
t1 = time.time()
t_in_min = (t1 - t0) / 60
print('Registration completed for %s - %s, which took %1.2f min.' %
(ptcode, ctcode, t_in_min))
## Load deforms and apply deform to registered phases/vols
if visualize:
#load avgreg
avg = 'avgreg'
filename = '%s_%s.ssdf' % (fileTr, avg)
savg = loadvol(dirsaveinsilico,
ptcode,
ctcode,
None,
'avgreg',
fname=filename)
# loadvol sets savg.sampling and savg.origin
vol = savg.vol
# show
#f = vv.figure(2); vv.clf()
#f.position = 968.00, 30.00, 944.00, 1002.00
#a = vv.subplot(111)
#a.daspect = 1, 1, -1
if reg2d:
t = vv.imshow(vol, clim=clim, axes=a4)
else:
t = vv.volshow(vol, clim=clim, renderStyle='mip', axes=a4)
#t.isoThreshold = 600
vv.xlabel('x'), vv.ylabel('y'), vv.zlabel('z')
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,
basedir,
showVol='mip',
meshWithColors=False,
motion='amplitude',
clim2=(0, 2)):
"""
Script to show the stent model. [ nellix]
"""
import os
import pirt
import visvis as vv
from stentseg.utils.datahandling import select_dir, loadvol, loadmodel
from pirt.utils.deformvis import DeformableTexture3D, DeformableMesh
from stentseg.stentdirect.stentgraph import create_mesh
from stentseg.stentdirect import stentgraph
from stentseg.utils.visualization import show_ctvolume
from stentseg.motion.vis import create_mesh_with_abs_displacement
import copy
from stentseg.motion.dynamic import incorporate_motion_nodes, incorporate_motion_edges
from lspeas.utils.ecgslider import runEcgSlider
from stentseg.utils import _utils_GUI
import numpy as np
cropname = 'prox'
# params
nr = 1
# motion = 'amplitude' # amplitude or sum
dimension = 'xyz'
showVol = showVol # MIP or ISO or 2D or None
clim0 = (0, 2000)
# clim2 = (0,2)
motionPlay = 9, 1 # each x ms, a step of x %
s = loadvol(basedir, ptcode, ctcode, cropname, what='deforms')
m = loadmodel(basedir, ptcode, ctcode, cropname,
'centerline_total_modelavgreg_deforms')
v = loadmodel(basedir,
ptcode,
ctcode,
cropname,
modelname='centerline_total_modelvesselavgreg_deforms')
s2 = loadvol(basedir, ptcode, ctcode, cropname, what='avgreg')
vol_org = copy.deepcopy(s2.vol)
s2.vol.sampling = [
vol_org.sampling[1], vol_org.sampling[1], vol_org.sampling[2]
]
s2.sampling = s2.vol.sampling
vol = s2.vol
# merge models into one for dynamic visualization
model_total = stentgraph.StentGraph()
for key in dir(m):
if key.startswith('model'):
model_total.add_nodes_from(
m[key].nodes(data=True)) # also attributes
model_total.add_edges_from(m[key].edges(data=True))
for key in dir(v):
if key.startswith('model'):
model_total.add_nodes_from(
v[key].nodes(data=True)) # also attributes
model_total.add_edges_from(v[key].edges(data=True))
# Load deformations (forward for mesh)
deformkeys = []
for key in dir(s):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s[key] for key in deformkeys]
deforms = [[field[::2, ::2, ::2] for field in fields]
for fields in deforms]
# These deforms are forward mapping. Turn into DeformationFields.
# Also get the backwards mapping variants (i.e. the inverse deforms).
# The forward mapping deforms should be used to deform meshes (since
# the information is used to displace vertices). The backward mapping
# deforms should be used to deform textures (since they are used in
# interpolating the texture data).
deforms_f = [pirt.DeformationFieldForward(*f) for f in deforms]
deforms_b = [f.as_backward() for f in deforms_f]
# Create mesh
if meshWithColors:
try:
modelmesh = create_mesh_with_abs_displacement(model_total,
radius=0.7,
dim=dimension,
motion=motion)
except KeyError:
print('Centerline model has no pathdeforms so we create them')
# use unsampled deforms
deforms2 = [s[key] for key in deformkeys]
# deforms as backward for model
deformsB = [
pirt.DeformationFieldBackward(*fields)
for fields in deforms2
]
# set sampling to original
# for i in range(len(deformsB)):
# deformsB[i]._field_sampling = tuple(s.sampling)
# not needed because we use unsampled deforms
# Combine ...
incorporate_motion_nodes(model_total, deformsB, s2.origin)
convert_paths_to_PointSet(model_total)
incorporate_motion_edges(model_total, deformsB, s2.origin)
convert_paths_to_ndarray(model_total)
modelmesh = create_mesh_with_abs_displacement(model_total,
radius=0.7,
dim=dimension,
motion=motion)
else:
modelmesh = create_mesh(model_total, 0.7, fullPaths=True)
## Start vis
f = vv.figure(nr)
vv.clf()
if nr == 1:
f.position = 8.00, 30.00, 944.00, 1002.00
else:
f.position = 968.00, 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
t = vv.volshow(vol, clim=clim0, renderStyle=showVol, axes=a)
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
if meshWithColors:
if dimension == 'xyz':
dim = '3D'
vv.title(
'Model for chEVAS %s (color-coded %s of movement in %s in mm)'
% (ptcode[8:], motion, dim))
else:
vv.title('Model for chEVAS %s' % (ptcode[8:]))
colorbar = True
# Create deformable mesh
dm = DeformableMesh(a, modelmesh) # in x,y,z
dm.SetDeforms(*[list(reversed(deform))
for deform in deforms_f]) # from z,y,x to x,y,z
if meshWithColors:
dm.clim = clim2
dm.colormap = vv.CM_JET #todo: use colormap Viridis or Magma as JET is not linear (https://bids.github.io/colormap/)
if colorbar:
vv.colorbar()
colorbar = False
else:
dm.faceColor = 'g'
# Run mesh
a.SetLimits()
# a.SetView(viewringcrop)
dm.MotionPlay(motionPlay[0],
motionPlay[1]) # (10, 0.2) = each 10 ms do a step of 20%
dm.motionSplineType = 'B-spline'
dm.motionAmplitude = 0.5
## run ecgslider
ecg = runEcgSlider(dm, f, a, motionPlay)
# basedir = select_dir(r'D:\LSPEAS_F\LSPEASF_ssdf')
# Select dataset to register
# ptcode = 'QRM_FANTOOM_20160121'
# ctcode = '12months'
cropnames = ['stent']
ptcodes = ['LSPEAS_018', 'LSPEAS_025', 'LSPEAS_023', 'LSPEAS_024']
ctcodes = ['24months']
for ptcode in ptcodes:
for ctcode in ctcodes:
for cropname in cropnames:
# Load volumes
try:
s = loadvol(basedir, ptcode, ctcode, cropname, 'phases')
except FileNotFoundError:
continue
vols = [s['vol%i' % (i * 10)] for i in range(10)]
#todo: resample to isotropic?
# for vol in vols:
# see function in datahandling
#todo: normalize data!! comparable histograms, comparable mass image forces
t0 = time.time()
# Initialize registration object
reg = pirt.reg.GravityRegistration(*vols)
# Set params
reg.params.mass_transforms = 2 # 2nd order (Laplacian) triggers more at lines
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))
## Renal origin coordinates: input by user/read excel
# coordinates, left and right most caudal renal
# ctcode1
xrenal1, yrenal1, zrenal1 = 132.7, 89.2, 85.5
renal1 = PointSet(list((xrenal1, yrenal1, zrenal1)))
# ctcode2
if ctcode2:
xrenal2, yrenal2, zrenal2 = 171, 165.1, 39.5
renal2 = PointSet(list((xrenal2, yrenal2, zrenal2)))
# renal_left, renal_right = foo.readRenalsExcel(sheet_renals_obs, ptcode, ctcode1)
# renal1 = renal_left
## Load (dynamic) stent models, vessel, ct
# Load static CT image to add as reference
s = loadvol(basedir, ptcode, ctcode1, cropname, 'avgreg')
vol1 = s.vol
if ctcode2:
s = loadvol(basedir, ptcode, ctcode2, cropname, 'avgreg')
vol2 = s.vol
# load stent model
s2 = loadmodel(basedir, ptcode, ctcode1, cropname, modelname)
model1 = s2.model
modelmesh1 = create_mesh(model1, meshradius)
if ctcode2:
s2 = loadmodel(basedir, ptcode, ctcode2, cropname, modelname)
model2 = s2.model
modelmesh2 = create_mesh(model2, meshradius)
# Load vessel mesh (output Mimics)
from stentseg.utils import _utils_GUI
import copy
from stentseg.utils.picker import pick3d
from stentseg.apps.record_movie import recordMovie
# Select the ssdf basedir
basedir = select_dir(r'F:\Nellix_chevas\CT_SSDF\SSDF_automated',
r'D:\Nellix_chevas_BACKUP\CT_SSDF\SSDF_automated')
# Select dataset to register
ptcode = 'chevas_02'
ctcode, nr = '12months', 1
cropname = 'prox'
## Show single vol
s0 = loadvol(basedir, ptcode, ctcode, cropname, 'phases')
# vol = s0.vol
vol = s0.vol20
key = 'vol20'
zscale = (s0[key].sampling[0] / s0[key].sampling[1]) # z / y
# resample vol using spline interpolation, 3rd order polynomial
vol_zoom = scipy.ndimage.interpolation.zoom(s0[key], [zscale, 1, 1], 'float32')
s0[key].sampling = [
s0[key].sampling[1], s0[key].sampling[1], s0[key].sampling[2]
]
# 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()
# ptcode = 'QRM_FANTOOM_20160121'
# ctcode, nr = 'ZA3-75-1.2', 1
cropname = 'ring'
modelname = 'modelavgreg'
motion = 'amplitude' # amplitude or sum
dimension = 'xyz'
showVol = 'ISO' # MIP or ISO or 2D or None
clim0 = (-10, 2500)
clim2 = (0, 3)
isoTh = 250
motionPlay = 9, 1 # each x ms, a step of perc of T
staticref = 'avgreg' # 'avg7020'
meshWithColors = True
# Load deformations (forward for mesh)
s = loadvol(basedir, ptcode, ctcode, cropname, 'deforms')
# deforms = [s['deform%i'%(i*10)] for i in range(10)]
deformkeys = []
for key in dir(s):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s[key] for key in deformkeys]
# deforms = [[field[::2,::2,::2] for field in fields] for fields in deforms]
try:
s2 = loadvol(basedir, ptcode, ctcode, 'ring', staticref)
except FileNotFoundError:
s2 = loadvol(basedir, ptcode, ctcode, 'ring', staticref)
vol = s2.vol
s3 = loadvol(basedir, ptcode, ctcode, cropname, 'phases')
basedir = select_dir(os.getenv('LSPEAS_BASEDIR', ''),
r'D:\LSPEAS\LSPEAS_ssdf', r'F:\LSPEAS_ssdf_backup')
# Select dataset to register
ptcode = 'LSPEAS_025'
ctcode = '24months'
cropname = 'ring'
modelname = 'modelavgreg'
# Load the stent model and mesh
s = loadmodel(basedir, ptcode, ctcode, cropname, modelname)
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)')
