# Registration with a Versor with Python and without SimpleITK

**URL:** https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806
**Category:** Beginner Questions
**Tags:** registration, python
**Created:** [February 15, 2022, 4:13am UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806 "2022-02-15T04:13:47Z")
**Posts on this page:** 13
**Page:** 1

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 15, 2022, 4:13am UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/1 "2022-02-15T04:13:48Z")

</div>

Continuing the discussion from [3D image registration with Python and without SimpleITK](https://discourse.itk.org/t/3d-image-registration-with-python-and-without-simpleitk/4773):

Hello!

Instead of the translation registration, I am now trying a registration with a versor. How can I do that? This is my code (MWE):

```python
# Copyright 2022 edgar
# License:
#
# This program is free software: you can redistribute it
# and/or modify it under the terms of the GNU General
# Public License as published by the Free Software
# Foundation, version 3 of the License.
#
# This program is distributed in the hope that it will be
# useful, but WITHOUT ANY WARRANTY; without even the
# implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE. See the GNU General Public License
# for more details.
#
# You should have received a copy of the GNU General
# Public License along with this program. If not, see
# <https://www.gnu.org/licenses/>.
#
# Copyright Insight Software Consortium
#
# Licensed under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0.txt
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on
# an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.

import sys
import itk
import numpy as np
from distutils.version import StrictVersion as VS
# from benchmark3d.primitives import displ_series_obj3d
from skimage.morphology import disk
from scipy.ndimage import shift

# Draw a 3D disk
side_size = 10
obj2d = disk(side_size / 2, dtype=np.uint8)
obj3d = np.asarray([disk(side_size / 2, dtype=np.uint8)
                    for idx in range(5)])
# Create 4 frames
series_length = 4
holder = np.asarray([obj3d for idx in range(series_length)])
# Move the last frame
holder[-1] = shift(holder[-1],
                   (series_length - 1, 0, 0))

# Set the right data type
pixel_type = itk.ctype("float")
dimension = 3
image_type = itk.Image[pixel_type, dimension]

# Load first and last frames as ITK data (images);
# swap axes ITK: i, j, k, Numpy: k, i, j
# (https://discourse.itk.org/t/
# importing-image-from-array-and-axis-reorder/1192/)
fixed_image_arr = holder[0].transpose((2, 1, 0))
moving_image_arr = holder[-1].transpose((2, 1, 0))
fixed_image = itk.image_from_array(
    fixed_image_arr.astype(np.float32))
moving_image = itk.image_from_array(
    moving_image_arr.astype(np.float32))

dimension = fixed_image.GetImageDimension()
# fixed_image_type = itk.Image[pixel_type, dimension]
# moving_image_type = itk.Image[pixel_type, dimension]
fixed_image_type = type(fixed_image)
moving_image_type = type(moving_image)

versor_transform = itk.VersorTransform[itk.D]
initial_transform = versor_transform.New()

versor_optimizer = itk.VersorTransformOptimizer.New(
    # # Not for this optimiser
    # LearningRate=4,
    MinimumStepLength=0.001,
    RelaxationFactor=0.5,
    NumberOfIterations=200)

mse_img2img_metric = itk.MeanSquaresImageToImageMetricv4
mse_metric = mse_img2img_metric[fixed_image_type,
                                moving_image_type].New()

registration_method = itk.ImageRegistrationMethodv4[
    fixed_image_type, moving_image_type]
registration = registration_method.New(
        FixedImage=fixed_image,
        MovingImage=moving_image,
        Metric=mse_metric,
        Optimizer=versor_optimizer,
        InitialTransform=initial_transform)

moving_initial_transform = versor_transform.New()
initial_parameters = moving_initial_transform.GetParameters()

```

, but I get this error:

```auto
  File "/usr/lib/python3.10/itk/itkImageRegistrationMethodv4Python.py", line 363, in New
    template_class.New(obj, *args, **kargs)
  File "/usr/lib/python3.10/itk/support/template_class.py", line 800, in New
    itk.set_inputs(self, args, kargs)
  File "/usr/lib/python3.10/itk/support/extras.py", line 1252, in set_inputs
    attrib(itk.output(value))
  TypeError: in method 'itkImageRegistrationMethodv4REGv4F3F3_SetOptimizer', argument 2 of type 'itkObjectToObjectOptimizerBaseTemplateD *'

```

If I try with `double`:

```python
  # Copyright 2022 edgar
  # License:
  #
  # This program is free software: you can redistribute it
  # and/or modify it under the terms of the GNU General
  # Public License as published by the Free Software
  # Foundation, version 3 of the License.
  #
  # This program is distributed in the hope that it will be
  # useful, but WITHOUT ANY WARRANTY; without even the
  # implied warranty of MERCHANTABILITY or FITNESS FOR A
  # PARTICULAR PURPOSE. See the GNU General Public License
  # for more details.
  #
  # You should have received a copy of the GNU General
  # Public License along with this program. If not, see
  # <https://www.gnu.org/licenses/>.
  #
  # Copyright Insight Software Consortium
  #
  # Licensed under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License. You may obtain a copy of the License at
  #
  # http://www.apache.org/licenses/LICENSE-2.0.txt
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on
  # an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied. See the License for the
  # specific language governing permissions and limitations
  # under the License.

  pixel_type = itk.ctype("double")
  dimension = 3
  image_type = itk.Image[pixel_type, dimension]

  # Load first and last frames as ITK data (images);
  # swap axes ITK: i, j, k, Numpy: k, i, j
  # (https://discourse.itk.org/t/
  # importing-image-from-array-and-axis-reorder/1192/)
  fixed_image_arr = holder[0].transpose((2, 1, 0))
  moving_image_arr = holder[-1].transpose((2, 1, 0))
  fixed_image = itk.image_from_array(
      fixed_image_arr.astype(np.double))
  moving_image = itk.image_from_array(
      moving_image_arr.astype(np.double))

  dimension = fixed_image.GetImageDimension()
  # fixed_image_type = itk.Image[pixel_type, dimension]
  # moving_image_type = itk.Image[pixel_type, dimension]
  fixed_image_type = type(fixed_image)
  moving_image_type = type(moving_image)

  versor_transform = itk.VersorTransform[itk.D]
  initial_transform = versor_transform.New()

  versor_optimizer = itk.VersorTransformOptimizer.New(
      # # Not for this optimiser
      # LearningRate=4,
      MinimumStepLength=0.001,
      RelaxationFactor=0.5,
      NumberOfIterations=200)

  mse_img2img_metric = itk.MeanSquaresImageToImageMetricv4
  mse_metric = mse_img2img_metric[fixed_image_type,
                                  moving_image_type].New()

  registration_method = itk.ImageRegistrationMethodv4[
      fixed_image_type, moving_image_type]
  registration = registration_method.New(
          FixedImage=fixed_image,
          MovingImage=moving_image,
          Metric=mse_metric,
          Optimizer=versor_optimizer,
          InitialTransform=initial_transform)

  moving_initial_transform = versor_transform.New()
  initial_parameters = moving_initial_transform.GetParameters()

```

I get this

```auto
Traceback (most recent call last):
  File "/usr/lib/python3.10/itk/support/template_class.py", line 525, in __getitem__
    this_item = self. __template__ [key]
KeyError: (<class 'itk.itkImagePython.itkImageD3'>, <class 'itk.itkImagePython.itkImageD3'>)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<string>", line 17, in __PYTHON_EL_eval
  File "<string>", line 1, in <module>
  File "/usr/lib/python3.10/itk/support/template_class.py", line 529, in __getitem__
    raise itk.TemplateTypeError(self, key)
itk.support.extras.TemplateTypeError: itk.MeanSquaresImageToImageMetricv4 is not wrapped for input type `itk.Image[itk.D,3], itk.Image[itk.D,3]`.

To limit the size of the package, only a limited number of
types are available in ITK Python. To print the supported
types, run the following command in your python environment:

    itk.MeanSquaresImageToImageMetricv4.GetTypes()

Possible solutions:
,* If you are an application user:
,** Convert your input image into a supported format (see below).
,** Contact developer to report the issue.
,* If you are an application developer, force input images to be
loaded in a supported pixel type.

    e.g.: instance = itk.MeanSquaresImageToImageMetricv4[itk.Image[itk.F,2], itk.Image[itk.F,2]].New(my_input)

,* (Advanced) If you are an application developer, build ITK Python yourself and
turned to `ON` the corresponding CMake option to wrap the pixel type or image
dimension you need. When configuring ITK with CMake, you can set
`ITK_WRAP_${type}` (replace ${type} with appropriate pixel type such as
`double`). If you need to support images with 4 or 5 dimensions, you can add
these dimensions to the list of dimensions in the CMake variable
`ITK_WRAP_IMAGE_DIMS`.

Supported input types:

itk.Image[itk.F,2]
itk.Image[itk.F,3]

```

I can compile again with `-DITK_WRAP_double:BOOL=ON`, but may be float32 is a bit less memory expensive. How can a registration be run with versors and `np.float32`? Thanks!

---

<div class="post-metadata">

### Author: ![dzenanz](https://discourse.itk.org/user_avatar/discourse.itk.org/dzenanz/32/1093_2.png) [@dzenanz](https://discourse.itk.org/u/dzenanz)
#### Post date: [February 15, 2022, 3:58pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/2 "2022-02-15T15:58:45Z")

</div>

> [@edgar](#):
>
> `versor_transform = itk.VersorTransform[itk.D]`

What happens if you use `versor_transform = itk.VersorTransform[itk.F]` (transform which uses floats internally)?

---

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 15, 2022, 6:44pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/3 "2022-02-15T18:44:37Z")

</div>

Hi! Thanks!

If everything stays as float (pixel\_type, fixed\_image, moving\_image), the error is similar, but now, at the end:

```auto
...
  File "/usr/lib/python3.10/itk/support/template_class.py", line 529, in __getitem__
    raise itk.TemplateTypeError(self, key)
itk.support.extras.TemplateTypeError: itk.VersorTransform is not wrapped for input type `itk.F`.
...
    e.g.: instance = itk.VersorTransform[itk.D].New(my_input)
...
Supported input types:

itk.D

```

I can see that my `CMakeCache.txt` has `ITK_WRAP_float:BOOL=ON` and `-DITK_WRAP_IMAGE_DIMS:STRING="2;3;4"`

---

<div class="post-metadata">

### Author: ![dzenanz](https://discourse.itk.org/user_avatar/discourse.itk.org/dzenanz/32/1093_2.png) [@dzenanz](https://discourse.itk.org/u/dzenanz)
#### Post date: [February 15, 2022, 7:01pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/4 "2022-02-15T19:01:28Z")

</div>

> [@edgar](#):
>
> `itk.VersorTransform is not wrapped for input type `itk.F``

Transforms are normally used with `double` parameters, so this is not strange. It was worth a shot.

@brad-t-moore, do you have any advice about `TypeError: in method 'itkImageRegistrationMethodv4REGv4F3F3_SetOptimizer', argument 2 of type 'itkObjectToObjectOptimizerBaseTemplateD *'`?

---

<div class="post-metadata">

### Author: ![Lee\_Newberg](https://discourse.itk.org/user_avatar/discourse.itk.org/lee_newberg/32/1461_2.png) [@Lee\_Newberg](https://discourse.itk.org/u/Lee_Newberg)
#### Post date: [February 15, 2022, 7:32pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/5 "2022-02-15T19:32:47Z")

</div>

As a side note, I think you do not want to transpose the dimensions when creating `fixed_image_arr` and `moving_image_arr`. Although ITK conventions have the indices in reverse order relative to numpy, that applies when using `itk::Index` values and `itk::Size` values. I suspect that `holder[0].shape` and `fixed_image.shape` do not match in the present code, but they should. (That `fixed_image.GetLargestPossibleRegion().GetSize()` returns the indices in reverse order to these shapes is okay.)

> [@edgar](#):
>
> ```auto
> # swap axes ITK: i, j, k, Numpy: k, i, j
> # (https://discourse.itk.org/t/
> # importing-image-from-array-and-axis-reorder/1192/)
> fixed_image_arr = holder[0].transpose((2, 1, 0))
> moving_image_arr = holder[-1].transpose((2, 1, 0))
> fixed_image = itk.image_from_array(
> fixed_image_arr.astype(np.double))
> moving_image = itk.image_from_array(
> moving_image_arr.astype(np.double))
> 
> ```

---

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 15, 2022, 8:49pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/6 "2022-02-15T20:49:03Z")

</div>

Yes, you may be right. I will check that. Thanks.

---

<div class="post-metadata">

### Author: ![brad-t-moore](https://discourse.itk.org/user_avatar/discourse.itk.org/brad-t-moore/32/1932_2.png) [@brad-t-moore](https://discourse.itk.org/u/brad-t-moore)
#### Post date: [February 16, 2022, 3:53pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/7 "2022-02-16T15:53:25Z")

</div>

The VersorTransformOptimizer is not a v4 optimizer is my guess.

---

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 16, 2022, 10:27pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/8 "2022-02-16T22:27:11Z")

</div>

Thanks.

1. What would be the appropriate way to run a registration with a versor? (what modifications are needed in the code that I posted?).
2. If a versor is not a feasible option, what other type of transform is available for rotation as a v4 transform?

---

<div class="post-metadata">

### Author: ![dzenanz](https://discourse.itk.org/user_avatar/discourse.itk.org/dzenanz/32/1093_2.png) [@dzenanz](https://discourse.itk.org/u/dzenanz)
#### Post date: [February 16, 2022, 10:42pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/9 "2022-02-16T22:42:49Z")

</div>

A complete list is [here](https://itk.org/Doxygen/html/group__ITKOptimizersv4.html). Try `RegularStepGradientDescentOptimizerv4`, `LBFGSOptimizerv4`, `PowellOptimizerv4` or `AmoebaOptimizerv4`.

---

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 17, 2022, 12:51am UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/10 "2022-02-17T00:51:47Z")

</div>

Thanks, I will try those 🙂 .

---

<div class="post-metadata">

### Author: ![brad-t-moore](https://discourse.itk.org/user_avatar/discourse.itk.org/brad-t-moore/32/1932_2.png) [@brad-t-moore](https://discourse.itk.org/u/brad-t-moore)
#### Post date: [February 17, 2022, 6:17pm UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/11 "2022-02-17T18:17:51Z")

</div>

So the VersorTransform can still be used but you need to use a v4 optimizer. The ITK software guide has a section that looks relevant. Pg. 223 of Book II (second half of the PDF)

> <https://github.com/InsightSoftwareConsortium/ITK/blob/master/Examples/RegistrationITKv4/ImageRegistration8.cxx>

[https://itk.org/ItkSoftwareGuide.pdf](https://itk.org/ItkSoftwareGuide.pdf)

---

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 18, 2022, 1:21am UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/12 "2022-02-18T01:21:10Z")

</div>

Thank you, I will look into that. I can already see that:

> [@](#):
>
> Fortunately in ITKv4, the  
> // \doxygen{RegularStepGradientDescentOptimizerv4} can be used for both  
> // vector and versor transform optimizations

---

<div class="post-metadata">

### Author: ![edgar](https://discourse.itk.org/letter_avatar_proxy/v4/letter/e/b487fb/32.png) [@edgar](https://discourse.itk.org/u/edgar)
#### Post date: [February 18, 2022, 2:07am UTC](https://discourse.itk.org/t/registration-with-a-versor-with-python-and-without-simpleitk/4806/13 "2022-02-18T02:07:56Z")

</div>

> [@brad-t-moore](#):
>
> The ITK software guide has a section that looks relevant. Pg. 223 of Book II (second half of the PDF)

For those interested, it can also be found here:  
[https://itk.org/ITKSoftwareGuide/html/Book2/ITKSoftwareGuide-Book2ch3.html#x26-1050003.6](https://itk.org/ITKSoftwareGuide/html/Book2/ITKSoftwareGuide-Book2ch3.html#x26-1050003.6)

> [@](#):
>
> We also set the ordinary parameters of the optimization method. In this case we are using a [itk::RegularStepGradientDescentOptimizerv4](https://www.itk.org/Doxygen/html/classitk_1_1RegularStepGradientDescentOptimizerv4.html)