def TPSMatch(self):
mx1 = []
my1 = []
mx2 = []
my2 = []
for i in range(len(self.vMatchX)):
mx1.append(self.X1[self.vMatchX[i]])
my1.append(self.Y1[self.vMatchX[i]])
mx2.append(self.X2[self.vMatchY[i]])
my2.append(self.Y2[self.vMatchY[i]])
tp = TPS()
tp.drawimg = 0
self.vTPS = tp.GetTransform(mx1, my1, mx2, my2)
if self.bDraw:
self.DrawImg(mx1, my1, mx2, my2)
return self.vTPS
def TPSMatch(self):
mx1 = []
my1 = []
mx2 = []
my2 = []
for i in range(len(self.vMatchX)):
mx1.append(self.X1[self.vMatchX[i]])
my1.append(self.Y1[self.vMatchX[i]])
mx2.append(self.X2[self.vMatchY[i]])
my2.append(self.Y2[self.vMatchY[i]])
tp = TPS()
tp.drawimg = 0
self.vTPS = tp.GetTransform(mx1, my1, mx2, my2)
if self.bDraw:
self.DrawImg(mx1, my1, mx2, my2)
return self.vTPS
def getSectorMap(filename,
sector,
roi_list,
visualize=False,
patID=-1,
saveToMat=False):
"""
Get an atlas point cloud registered to a patient with a transformed sector delineation
:param filename: the filename of the catlas
:param sector: a point cloud representing the sector in atlas coordinate frame
:param roi_list: a list of the regions of interest for the patient
:param visualize: if True, the method will plot the before and after transformations
:param patID: patient ID, if left empty, a random patient will be chosen using the roi_list
:param saveToMat: by default, false, but if true, will save to a .mat file called sectors.mat
:type filename: str
:type sector: numpy.array N x 3
:type roi_list: list[str]
:type visualize: bool
:type patID: int
:type saveToMat: bool
:return: A point cloud of the atlas and the sector together and as separate objects
:rtype: numpy.array N x 3
"""
atlas = get_atlas(filename)
atlas = atlas.iterations[-1]
print atlas.shape
length = sector.shape[0]
if patID == -1:
patID = query_test_patient(roi_list)[0]
fixed_atlas = atlas
print('Starting Registration...')
transformed, g, wc, errors, patient = register_atlas_to_patient(
fixed_atlas, patID, roi_list)
print('Registration finished.')
wobject = TPS.register(fixed_atlas, transformed, sector)
print('TPS finished.')
atlas_after = np.append(transformed, wobject, 0)
if visualize:
print('Visualizing')
atlas_before = np.append(atlas, sector, 0)
vs.visualizePointCloud(atlas_before,
'Atlas with delineated sector',
alpha=0.3,
num_points=length,
state=1)
vs.visualizePointCloud(atlas_after,
'Atlas with sector in patient coordinate frame',
alpha=0.3,
num_points=length,
state=1)
if saveToMat:
sio.savemat(
'sectors.mat', {
'atlas': atlas,
'transformed': transformed,
'sector': sector,
'ptsector': wobject
})
return atlas_after, wobject, transformed
def Chamfer(self):
if (len(self.vMatchX) < 10):
return [100000, 100000, 100000, 100000]
PX1 = []
PY1 = []
PX2 = []
PY2 = []
for i in self.vMatchX:
t = i % len(self.X1)
PX1.append(self.X1[t])
PY1.append(self.Y1[t])
for i in self.vMatchY:
PX2.append(self.X2[i])
PY2.append(self.Y2[i])
#print len(self.X1), len(self.X2)
tp = TPS()
tp.drawimg = self.bDraw
bendingcost = tp.GetTransform(PX1, PY1, PX2, PY2)
#DrawMatch(PX1, PY1, PX2, PY2)
#print Afft
chamfer = 0
resultx = []
resulty = []
for i in range(len(self.X1)):
ts = tp.Transform(self.X1[i], self.Y1[i])
resultx.append(ts[0])
resulty.append(ts[1])
mindist = 1e10
for j in range(len(self.X2)):
dist = math.sqrt((ts[0] - self.X2[j]) * (ts[0] - self.X2[j]) +
(ts[1] - self.Y2[j]) * (ts[1] - self.Y2[j]))
if (dist < mindist):
mindist = dist
chamfer += mindist
#DrawMatch(self.X2, self.Y2, resultx, resulty)
if (self.DrawImg):
DrawIndexMatch(self.X1, self.Y1, self.X2, self.Y2, self.vMatchX,
self.vMatchY)
return bendingcost + [chamfer]
def Chamfer(self):
if (len(self.vMatchX) < 10):
return [100000, 100000, 100000, 100000]
PX1 =[]
PY1 =[]
PX2 =[]
PY2 =[]
for i in self.vMatchX:
t = i % len(self.X1)
PX1.append(self.X1[t])
PY1.append(self.Y1[t])
for i in self.vMatchY:
PX2.append(self.X2[i])
PY2.append(self.Y2[i])
#print len(self.X1), len(self.X2)
tp = TPS()
tp.drawimg = self.bDraw
bendingcost = tp.GetTransform(PX1, PY1, PX2, PY2)
#DrawMatch(PX1, PY1, PX2, PY2)
#print Afft
chamfer = 0
resultx = []
resulty = []
for i in range(len(self.X1)):
ts = tp.Transform(self.X1[i], self.Y1[i])
resultx.append(ts[0])
resulty.append(ts[1])
mindist = 1e10
for j in range(len(self.X2)):
dist = math.sqrt((ts[0] - self.X2[j]) * (ts[0] - self.X2[j]) + (ts[1] - self.Y2[j]) * ( ts[1] - self.Y2[j]))
if (dist < mindist):
mindist = dist
chamfer += mindist
#DrawMatch(self.X2, self.Y2, resultx, resulty)
if (self.DrawImg):
DrawIndexMatch(self.X1, self.Y1, self.X2, self.Y2, self.vMatchX, self.vMatchY)
return bendingcost + [chamfer]
