def query_extract_region(fixed_image: sitk.Image, moving_image: sitk.Image,
transform: sitk.Transform,
registration_method: sitk.ImageRegistrationMethod):
do_extract = util.query_yes_no(
'Do you wish to extract a sub-region to register based on? [y/n] >> ')
if do_extract:
itkplt.plot_overlay(fixed_image, moving_image, transform=transform)
size = util.query_int('Enter the region size >> ')
origin = []
for dim in range(len(fixed_image.GetSpacing())):
origin_in_dim = util.query_float(
'Enter the origin in dimension {0} >> '.format(dim))
origin.append(origin_in_dim)
origin = np.array(origin)
fixed_region = extract_region(fixed_image, size, origin)
moving_region = extract_region(moving_image, size * 1.1,
origin - 0.05 * size, transform)
query_registration_sampling_change(registration_method)
return fixed_region, moving_region, do_extract
else:
return fixed_image, moving_image, do_extract
def supervised_register_images(fixed_image: sitk.Image,
moving_image: sitk.Image,
initial_transform: sitk.Transform = None,
moving_path=None,
registration_parameters: dict = None):
"""Register two images
:param fixed_image: image that is being registered to
:param moving_image: image that is being transformed and registered
:param initial_transform: the type of registration/transform, e.g. affine or euler
:param registration_parameters: dictionary of registration key/value arguments
:return: Registered image, corresponding transform, metric, and stop
"""
# todo: Re-enable registering for RGB images
while True:
registration_method = define_registration_method(
registration_parameters)
fixed_final, moving_final, region_extracted = query_for_changes(
fixed_image, moving_image, initial_transform, registration_method,
moving_path)
reg_plot = RegistrationPlot(fixed_final,
moving_final,
transform=initial_transform)
(transform, metric,
stop) = register(fixed_final,
moving_final,
reg_plot,
registration_method=registration_method,
initial_transform=initial_transform)
if region_extracted:
itkplt.plot_overlay(fixed_image,
moving_image,
transform,
downsample=False)
if query_good_registration(transform, metric, stop):
break
# todo: change registration method query here
registered_image = sitk.Resample(moving_image, fixed_image, transform,
sitk.sitkLinear, 0.0,
moving_image.GetPixelID())
meta.copy_relevant_metadata(registered_image, moving_image)
plt.close('all')
return registered_image, transform, metric, stop
def plot_overlay_from_czi_timepoints(path_file, timepoint_one, timepoint_two):
"""
Plot two timepoints from a czi image in a red/green overlay. Warning: requires a running javabridge
:param path_file: Path to the czi file
:param timepoint_one: First timepoint
:param timepoint_two: Second timepoint
:return:
"""
array_one = bf.load_image(str(path_file), t=timepoint_one)
array_two = bf.load_image(str(path_file), t=timepoint_two)
image_one = sitk.GetImageFromArray(array_one)
image_two = sitk.GetImageFromArray(array_two)
itkplot.plot_overlay(image_one, image_two, sitk.Transform(2, sitk.sitkIdentity), continuous_update=True,
downsample=False)
def query_rotation_change(fixed_image: sitk.Image, moving_image: sitk.Image,
initial_transform: sitk.Transform):
"""Ask if the user wants a new 2D ITK origin based on image overlay"""
itkplt.plot_overlay(fixed_image, moving_image, initial_transform)
change_rotation = util.query_yes_no(
'Do you want to change the rotation? [y/n] >> ')
if change_rotation:
while True:
rotation = util.query_float('Enter new rotation (degrees): ')
tran.set_transform_rotation(initial_transform, rotation)
itkplt.plot_overlay(fixed_image, moving_image, initial_transform,
rotation)
# bug: The image does not show up till after the question
if util.query_yes_no('Is this rotation good? [y/n] >> '): break
def query_translation_change(fixed_image: sitk.Image, moving_image: sitk.Image,
transform: sitk.Transform):
"""Ask if the user wants a new 2D ITK translation based on image overlay"""
change_origin = util.query_yes_no(
'Do you want to change the initial translation? [y/n] >> ')
translation = tran.get_translation(transform)
if change_origin:
while True:
print('Current physical shift: ' + str(-1 * np.array(translation)))
new_translation = []
for dim in range(len(translation)):
new_dim_translation = -1 * util.query_float(
'Enter the new shift in dimension {0} >> '.format(
str(dim)))
new_translation.append(new_dim_translation)
tran.set_translation(transform, new_translation)
itkplt.plot_overlay(fixed_image, moving_image, transform)
# bug: The image does not show up till after the question
if util.query_yes_no('Is this translation good? [y/n] >>> '): break