def point_based_registration(I_path, Im_path, X, Xm):
#read/load the images I and Im
imageI = plt.imread(I_path)
imageIm = plt.imread(Im_path)
#convert to homogenous coordinates using c2h
X_h = util.c2h(X)
Xm_h = util.c2h(Xm)
#compute affine transformation and make a homogenous transformation matrix
Th = reg.ls_affine(X_h, Xm_h)
#transfrom the moving image using the transformation matrix
It, Xt = reg.image_transform(imageIm, Th)
#plotting the results
fig = plt.figure(figsize=(20, 30))
ax1 = fig.add_subplot(131)
im1 = ax1.imshow(imageI) #plot first image (fixed or T1) image
ax2 = fig.add_subplot(132)
im2 = ax2.imshow(imageIm) #plot second image (moving or T2) image
ax3 = fig.add_subplot(133)
im3 = ax3.imshow(It) #plot (T1 moving or T2) transformed image
ax1.set_title('T1 (fixed)')
ax2.set_title('T1 moving or T2')
ax3.set_title('Transformed (T1 moving or T2) image')
return Th
def ls_affine_test():
X = util.test_object(1)
# convert to homogeneous coordinates
Xh = util.c2h(X)
T_rot = reg.rotate(np.pi / 4)
T_scale = reg.scale(1.2, 0.9)
T_shear = reg.shear(0.2, 0.1)
T = util.t2h(T_rot.dot(T_scale).dot(T_shear), [10, 20])
Xm = T.dot(Xh)
Te = reg.ls_affine(Xh, Xm)
Xmt = Te.dot(Xm)
fig = plt.figure(figsize=(12, 5))
ax1 = fig.add_subplot(131)
ax2 = fig.add_subplot(132)
ax3 = fig.add_subplot(133)
util.plot_object(ax1, Xh)
util.plot_object(ax2, Xm)
util.plot_object(ax3, Xmt)
ax1.set_title('Test shape')
ax2.set_title('Arbitrary transformation')
ax3.set_title('Retrieved test shape')
ax1.grid()
ax2.grid()
ax3.grid()
def pbr(I_path, Im_path):
I = plt.imread(I_path)
Im = plt.imread(Im_path)
X, Xm = util.my_cpselect(I_path, Im_path)
if len(X[1]) == 1:
print('x must be larger than 1')
return
X = util.c2h(X)
Xm = util.c2h(Xm)
T = reg.ls_affine(X, Xm)
It, Xt = reg.image_transform(Im, T)
fig = plt.figure(figsize=(30, 30))
ax1 = fig.add_subplot(121)
ax1.set_title('Overlay of original images', fontsize=35)
ax1.axis('off')
im11 = ax1.imshow(I)
im12 = ax1.imshow(Im, alpha=0.7)
ax2 = fig.add_subplot(122)
ax2.set_title('Overlay transformed image over the fixed image',
fontsize=35)
ax2.axis('off')
im21 = ax2.imshow(I)
im22 = ax2.imshow(It, alpha=0.7)
return I, Im, It
def point_based_affine_registration(I, Im):
# let the user selecte points
X, Xm = util.my_cpselect(I, Im)
# find affine transformation matrix
T, reg_error = reg.ls_affine(util.c2h(X), util.c2h(Xm))
# transform the moving image according to T
Im = plt.imread(Im)
It, _ = reg.image_transform(Im, T)
return It, reg_error
def point_based_registration_demo():
# ---------------------------------
# Append the following code in jupiter to run:
# %matplotlib inline
# import sys
# sys.path.append("C:/Users/s163666/Documents/2019-2020/Medical Image Analysis/Mini_project_mia")
# from project_fout import point_based_registration_demo
# point_based_registration_demo()
# ---------------------------------
# read the fixed and moving images, 2x T1 or T1&T2
# change these in order to read different images
I_path = './data/image_data/3_1_t1.tif'
Im_path = './data/image_data/3_1_t2.tif'
#Select set of corresponding points using my_cpselect
X0, Xm0 = util.my_cpselect(I_path, Im_path)
#Compute the affine transformation between the pair of images
Xm = np.ones((3, Xm0.shape[1]))
Xm[0, :] = Xm0[0, :]
Xm[1, :] = Xm0[1, :]
X = np.ones((3, X0.shape[1]))
X[0, :] = X0[0, :]
X[1, :] = X0[1, :]
T, Etrain = reg.ls_affine(X, Xm)
Etest = reg.point_based_error(I_path, Im_path, T)
#read image
Im = plt.imread(Im_path)
#Apply the affine transformation to the moving image
It, Xt = reg.image_transform(Im, T)
#plot figure
fig = plt.figure(figsize=(12, 5))
#fig, ax = plt.subplots()
ax = fig.add_subplot(121)
im = ax.imshow(It)
ax.set_title("Transformed image")
ax.set_xlabel('x')
ax.set_ylabel('y')
print(Etrain)
print(Etest)
display(fig)
fig.savefig('./data/image_results/3_1_t1 + 3_1_t2.png')
def my_point_based_registration():
I = '../data/image_data/3_2_t1.tif'
I_d = '../data/image_data/3_2_t1_d.tif'
I_plt = plt.imread('../data/image_data/3_2_t1.tif')
I_d_plt = plt.imread('../data/image_data/3_2_t1_d.tif')
X, Xm = util.my_cpselect(I, I_d)
affine_transformation = reg.ls_affine(X, Xm)
transformed_moving_image, transformed_vector = reg.image_transform(
I_d_plt, affine_transformation)
fig = plt.figure(figsize=(12, 5))
ax1 = fig.add_subplot(131)
Im1 = ax1.imshow(I_plt) # Fixed image or Transformed image
Im2 = ax1.imshow(transformed_moving_image,
alpha=0.7) # Transformed image or Fixed image
def my_point_based_registration_2():
I2 = '../data/image_data/3_2_t1.tif' # Tweede opdracht T1 slide
I_d_2 = '../data/image_data/3_2_t2.tif' # T2 slice
I_plt_2 = plt.imread('../data/image_data/3_2_t1.tif')
I_d_plt_2 = plt.imread('../data/image_data/3_2_t1_d.tif')
X2, Xm2 = util.my_cpselect(I2, I_d_2)
affine_transformation_2 = reg.ls_affine(X2, Xm2)
transformed_moving_image_2, transformed_vector_2 = reg.image_transform(
I_d_plt_2, affine_transformation_2)
fig = plt.figure(figsize=(12, 5))
ax1 = fig.add_subplot(131)
Im1 = ax1.imshow(
I_plt_2) # Fixed image or Transformed image, Je mag wisselen
Im2 = ax1.imshow(
transformed_moving_image_2,
alpha=0.7) # Transformed image or Fixed image Mag wisselen
