itk-thickness3d

ITKThickness3D

An ITK module to compute 3D thickness

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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.