我需要使用相同的轉換矩陣轉換(旋轉現在)的itk圖像和vtk polydata,但我遇到了麻煩。如何匹配vtk polydata和itk轉換
所有的代碼和測試數據是在這裏:https://github.com/jmerkow/vtk_itk_rotate
下面是relavent部分:
import SimpleITK as sitk
import vtk
import numpy as np
def rotate_img(img, rotation_center=None, theta_x=0,theta_y=0, theta_z=0, translation=(0,0,0), interp=sitk.sitkLinear, pixel_type=None, default_value=None):
if not rotation_center:
rotation_center = np.array(img.GetOrigin())+np.array(img.GetSpacing())*np.array(img.GetSize())/2
if default_value is None:
default_value = img.GetPixel(0,0,0)
pixel_type = img.GetPixelIDValue()
rigid_euler = sitk.Euler3DTransform(rotation_center, theta_x, theta_y, theta_z, translation)
return sitk.Resample(img, img, rigid_euler, interp, default_value, pixel_type)
def rotate_polydata(pd, rotation_center, theta_x=0,theta_y=0, theta_z=0, translation=(0,0,0)):
rigid_euler = sitk.Euler3DTransform(rotation_center, -theta_x, -theta_y, -theta_z, translation)
matrix = np.zeros([4,4])
old_matrix=np.array(rigid_euler.GetMatrix()).reshape(3,3)
matrix[:3,:3] = old_matrix
matrix[-1,-1] = 1
# to rotate about a center we first need to translate
transform_t = vtk.vtkTransform()
transform_t.Translate(-rotation_center)
transformer_t = vtk.vtkTransformPolyDataFilter()
transformer_t.SetTransform(transform_t)
transformer_t.SetInputData(pd)
transformer_t.Update()
transform = vtk.vtkTransform()
transform.SetMatrix(matrix.ravel())
transformer = vtk.vtkTransformPolyDataFilter()
transformer.SetTransform(transform)
transformer.SetInputConnection(transformer_t.GetOutputPort())
transformer.Update()
# translate back
transform_t2 = vtk.vtkTransform()
transform_t2.Translate(rotation_center)
transformer_t2 = vtk.vtkTransformPolyDataFilter()
transformer_t2.SetTransform(transform_t2)
transformer_t2.SetInputConnection(transformer.GetOutputPort())
transformer_t2.Update()
return transformer_t2.GetOutputDataObject(0)
datafn = 'test.mha'
polydata_file = 'test.vtp'
reader = vtk.vtkXMLPolyDataReader()
reader.SetFileName(polydata_file)
reader.Update()
pd = reader.GetOutput()
img = sitk.ReadImage(datafn)
seg = pd_to_itk_image(pd, img)
rotation_center = np.array(img.GetOrigin())+np.array(img.GetSpacing())*np.array(img.GetSize())/2
thetas = [0, 50]
thetas = [0, 50]
for theta_x in thetas:
for theta_y in thetas:
for theta_z in thetas:
theta_xr = theta_x/180.*np.pi
theta_yr = theta_y/180.*np.pi
theta_zr = theta_z/180.*np.pi
img_rot=rotate_img(img, theta_z=theta_zr, theta_y=theta_yr, theta_x=theta_xr)
seg_rot=rotate_img(seg, theta_z=theta_zr, theta_y=theta_yr, theta_x=theta_xr, interp=sitk.sitkNearestNeighbor, default_value=0)
pd_rot = rotate_polydata(pd, rotation_center, theta_z=theta_zr, theta_y=theta_yr, theta_x=theta_xr)
seg_pd_rot = pd_to_itk_image(pd_rot, img_rot)
mse = ((sitk.GetArrayFromImage(seg_pd_rot)-sitk.GetArrayFromImage(seg_rot))**2.).mean()
print theta_x, theta_y, theta_z, mse
#this outputs for this particular volume:
#0 0 0 mse: 0.0
#0 0 50 mse: 50.133369863 visually about the same
#0 50 0 mse: 25.2197787166 visually about the same
#0 50 50 mse: 863.588476181 visually totally different
#50 0 0 mse: 20.4021692276 visually about the same
#50 0 50 mse: 546.699844301 visually totally different
#50 50 0 mse: 662.337975204 visually totally different
#50 50 50 mse: 339.220945537 visually totally different
此代碼旋轉從POLYDATA產生的二進制體積,並在執行相同的旋轉操作polydata然後從那裏生成一個二進制卷。我期望這兩個結果是(大致)相同,但是,如果我圍繞多個軸旋轉,我所得到的是兩個完全不同的旋轉。 這是令我費解的,因爲我正在從一個變換矩陣並直接應用到另一個。
如何設置這些轉換,使兩個操作執行相同的轉換?爲什麼我們會得到不同的結果?
這個例子可能會有所幫助:https://itk.org/Wiki/ITK/Examples/WishList/IO/itkVtkImageConvertDICOM –