# embeded

**Repository Path**: balonga/embeded

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- **Project Name**: embeded
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- **License**: Apache-2.0
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- **Created**: 2022-01-19
- **Last Updated**: 2023-12-19

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## README

ITKThickness3D
==============

**An ITK module to compute 3D thickness**

.. image:: https://github.com/InsightSoftwareConsortium/ITKThickness3D/workflows/Build,%20test,%20package/badge.svg
    :alt:    Build Status

.. image:: https://img.shields.io/pypi/v/itk-thickness3d.svg
    :target: https://pypi.python.org/pypi/itk-thickness3d
    :alt: PyPI Version

.. image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg
    :target: https://github.com/InsightSoftwareConsortium/ITKThickness3D/blob/master/LICENSE
    :alt: License

Overview
--------

This is a module for the `Insight Toolkit (ITK) <https://itk.org>`_ that
provides filters that compute the skeleton and thickness transforms of a 3D
image.

ITK currently comes without a hands-on solution for 3D thickness evaluation.
This contribution implements several filters based on the Euclidean distance
transform and binary skeleton to fill this blank.

Binary thinning
```````````````
Provides a 1 pixel-thin wire skeleton using an efficient `curve thinning <https://doi.org/10.1016/j.patrec.2014.01.012>`_ algorithm. 

The thinning algorithm used in this module comes from the
`Insight Journal article <https://hdl.handle.net/1926/1292)>`_::

  Homann H.
  Implementation of a 3D thinning algorithm
  The Insight Journal - 2007 July - December.
  https://hdl.handle.net/1926/1292
  https://insight-journal.org/browse/publication/181

Medial thickness
````````````````

The idea behind the **medial thickness** as implemented in this module is
**twice the shortest distance to the outter shell along the medial axis**
of the object *(i.e. diameter of the local maximal fitting sphere)*.

This definition provides an *unbiased* method for thickness evaluation compared
to the *local thickness transform* since this last one will result in a higher
number of points for thick parts. The skeletonization insure a *minimal* set of
measurements to *fully* describe the object.


Filters
-------

- `itk::BinaryThinningImageFilter3D<TInputImage, TOutputImage> 
  <include/itkBinaryThinningImageFilter3D.h>`_: Compute the 3D `skeleton <https://hdl.handle.net/1926/1292>`_ 
  of the input image.
- `itk::MedialThicknessImageFilter3D<TInputImage, TOutputImage>
  </include/itkMedialThicknessImageFilter3D.h>`_: 2x the
  `distance <https://itk.org/Doxygen/html/classitk_1_1SignedMaurerDistanceMapImageFilter.html>`_
  to the outside along the `medial axis <include/itkBinaryThinningImageFilter3D.hxx>`_.


Installation
------------

Python
``````

Binary `Python packages <https://pypi.python.org/pypi/itk-thickness3d>`_ are
available for Linux, macOS, and Windows. They can be installed with::

  python -m pip install --upgrade pip
  python -m pip install itk-thickness3d


C++
```

You need to `build ITK <https://itk.org/Wiki/ITK/Configuring_and_Building>`_
from source to use this module.

In the newer versions of ITK, this module is available as a
`Remote <https://blog.kitware.com/advance-itk-with-modules/>`_ module in the
ITK source code. Build it with the `CMake` option: `Module_Thickness3D`, this
can be switched on with a `CMake` graphical interface `ccmake` or directly
from the command line with: `-DModule_Thickness3D:BOOL=ON`

For older ITK versions, add it manually as an *External* or *Remote* module to
the ITK source code:

*External*::

  cd ${itk_src}/Modules/External
  git clone https://github.com/InsightSoftwareConsortium/ITKThickness3D


*Remote*:

Create a file in ``${itk_src}/Modules/Remote`` called
``Thickness3D.remote.cmake`` (see
`this GitHub gist <https://gist.github.com/T4mmi/20449a97dce99f71eec8a9bb6e8853d4>`_)
with the the following contents::

  itk_fetch_module(Thickness3D
    "Tools for 3D thickness measurement"
    GIT_REPOSITORY ${git_protocol}://github.com/InsightSoftwareConsortium/ITKThickness3D.git
    GIT_TAG <replace with the latest stable commit tag>
  )


Usage
-----

Python
``````

Once ITK imported, you can use the ``itk.MedialThicknessImageFilter3D`` just as
any other `ITK methods <https://itkpythonpackage.readthedocs.io/en/latest/Quick_start_guide.html>`_::

  skeleton = itk.BinaryThinningImageFilter3D.New(image)


Here is a simple python script that reads an image, applies the medial
thickness filter and writes the resulting image in a file::

  import itk

  input_filename = sys.argv[1]
  output_filename = sys.argv[2]

  image = itk.imread(input_filename)
  thickness_map = itk.MedialThicknessImageFilter3D.New(image)

  itk.imwrite(thickness_map, output_filename)


License
-------

This software is distributed under the Apache 2.0 license. Please see the
*LICENSE* file for details.