disptools | Generate displacement fields with known volume changes
kandi X-RAY | disptools Summary
kandi X-RAY | disptools Summary
disptools is a C library. disptools has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
[Downloads] This library provides utilities to generate and manipulate displacement fields with known volume changes. It implements three search-based algorithms for the generation of deformation fields, along with a small collection of utility functions, and provides optional GPU acceleration through a CUDA implementation. The three algorithms implemented are referred as: + gradient: a gradient descent method (default). + greedy: a greedy search method proposed in [[1]] #1). + matching: a volume matching method proposed in [[2]] #2) and [[3]] #3). The implementation comes from the [PREDICT atrophysim tool] The library is built on top of SimpleITK, in order to provide a simple yet powerful set of functionalities for image analysis. Images stored as numpy arrays can be easily converted from and to [SimpleITK] and [ITK] image objects.
[Downloads] This library provides utilities to generate and manipulate displacement fields with known volume changes. It implements three search-based algorithms for the generation of deformation fields, along with a small collection of utility functions, and provides optional GPU acceleration through a CUDA implementation. The three algorithms implemented are referred as: + gradient: a gradient descent method (default). + greedy: a greedy search method proposed in [[1]] #1). + matching: a volume matching method proposed in [[2]] #2) and [[3]] #3). The implementation comes from the [PREDICT atrophysim tool] The library is built on top of SimpleITK, in order to provide a simple yet powerful set of functionalities for image analysis. Images stored as numpy arrays can be easily converted from and to [SimpleITK] and [ITK] image objects.
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Support
disptools has a low active ecosystem.
It has 16 star(s) with 2 fork(s). There are 2 watchers for this library.
It had no major release in the last 12 months.
There are 7 open issues and 2 have been closed. On average issues are closed in 17 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of disptools is 0.4.0
Quality
disptools has no bugs reported.
Security
disptools has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
disptools is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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disptools releases are available to install and integrate.
Installation instructions, examples and code snippets are available.
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disptools Key Features
No Key Features are available at this moment for disptools.
disptools Examples and Code Snippets
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Community Discussions
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Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install disptools
This package is available on [PyPI](https://pypi.org/project/disptools) both as source distribution and as a Windows pre-compiled binary wheel. You can install it with <tt>pip</tt>:. As always, it is recommended to use the package inside a [virtual environment](https://docs.python.org/3/tutorial/venv.html).
Requirements are specified by the <tt>requirements.txt</tt> file and can be installed with <tt>pip</tt>. The library is a cross-platform Python 3.5+ package, with a compiled C extension. The Python dependencies are: + [numpy](https://github.com/numpy/numpy) ([pypi package](https://pypi.python.org/pypi/numpy)) + [scipy](https://github.com/scipy/scipy) ([pypi package](https://pypi.org/pypi/scipy)) + [SimpleITK](https://github.com/SimpleITK/SimpleITK) ([pypi package](https://pypi.org/pypi/SimpleITK)). Build dependencies are a standard C compiler (tested with gcc 8.2 on Linux, mingw-w64 7.2 and MSVC 19 on Windows 10), [CMake](https://cmake.org/), the [numpy](https://pypi.python.org/pypi/numpy) and the [setuptools](https://pypi.python.org/pypi/setuptools) packages. [scikit-build](https://pypi.python.org/pypi/scikit-build) may be required to build the other Python dependencies. Some optional dependencies are required only for a limited set of features, and the package should build and run without them: + [itk](https://github.com/InsightSoftwareConsortium/ITK) ([pypi package](https://pypi.org/project/itk)): for <tt>disptools.drawing.sitk_to_itk</tt> + [vtk](https://github.com/Kitware/VTK) ([pypi package](https://pypi.org/project/vtk)): for <tt>disptools.io.write_vtk_points</tt> + [ply](https://github.com/dabeaz/ply) ([pypi package](https://pypi.org/project/ply)): for <tt>disptools.io.read_elastix_parameters</tt> + [scikit-image](https://github.com/scikit-image/scikit-image) ([pypi package](https://pypi.org/project/scikit-image)): for some features of <tt>disptools.drawing.extract_slice</tt>, and to run the unit tests. The following environment variables affect the <tt>setup.py</tt>: + <tt>DISPTOOLS_OPT=ON</tt>: enable non-portable optimisations. + <tt>DISPTOOLS_DEBUG=ON</tt>: disable optimisations, compile with debug symbols. + <tt>DISPTOOLS_CUDA_SUPPORT=ON</tt>: enable CUDA support.
First, be sure that [mingw](https://mingw-w64.org), CMake and Python are installed and their executables [are in your PATH](https://docs.python.org/3/using/windows.html#excursus-setting-environment-variables).
Ensure that <tt>gcc</tt> is working correctly:
Ensure that <tt>distutils</tt> correctly recognises your version of Visual Studio (even when using <tt>mingw</tt>). Open the file <tt>C:\Users\yourname\AppData\Local\Programs\Python\Python3x\Lib\distutils\cygwinccompiler.py</tt> (the exact location may vary according to your setup) and check that your version of Visual Studio is present in the function <tt>get_msvcr()</tt>; if not, adjust it according to the following:
Ensure that the library <tt>vcruntime140.dll</tt> is present in your library path. Otherwise, download it and place it in <tt>C:\Users\yourname\AppData\Local\Programs\Python\Python3x\libs</tt> (the exact path may vary according to your setup).
Clone the sources of this package with <tt>git</tt>, or download and extract them as a <tt>zip</tt> archive. Move to the root folder of the sources (<tt>C:\Users\yourname\disptools</tt> in this example), specify the right compiler, and launch the setup script to build and install the package.
Requirements are specified by the <tt>requirements.txt</tt> file and can be installed with <tt>pip</tt>. The library is a cross-platform Python 3.5+ package, with a compiled C extension. The Python dependencies are: + [numpy](https://github.com/numpy/numpy) ([pypi package](https://pypi.python.org/pypi/numpy)) + [scipy](https://github.com/scipy/scipy) ([pypi package](https://pypi.org/pypi/scipy)) + [SimpleITK](https://github.com/SimpleITK/SimpleITK) ([pypi package](https://pypi.org/pypi/SimpleITK)). Build dependencies are a standard C compiler (tested with gcc 8.2 on Linux, mingw-w64 7.2 and MSVC 19 on Windows 10), [CMake](https://cmake.org/), the [numpy](https://pypi.python.org/pypi/numpy) and the [setuptools](https://pypi.python.org/pypi/setuptools) packages. [scikit-build](https://pypi.python.org/pypi/scikit-build) may be required to build the other Python dependencies. Some optional dependencies are required only for a limited set of features, and the package should build and run without them: + [itk](https://github.com/InsightSoftwareConsortium/ITK) ([pypi package](https://pypi.org/project/itk)): for <tt>disptools.drawing.sitk_to_itk</tt> + [vtk](https://github.com/Kitware/VTK) ([pypi package](https://pypi.org/project/vtk)): for <tt>disptools.io.write_vtk_points</tt> + [ply](https://github.com/dabeaz/ply) ([pypi package](https://pypi.org/project/ply)): for <tt>disptools.io.read_elastix_parameters</tt> + [scikit-image](https://github.com/scikit-image/scikit-image) ([pypi package](https://pypi.org/project/scikit-image)): for some features of <tt>disptools.drawing.extract_slice</tt>, and to run the unit tests. The following environment variables affect the <tt>setup.py</tt>: + <tt>DISPTOOLS_OPT=ON</tt>: enable non-portable optimisations. + <tt>DISPTOOLS_DEBUG=ON</tt>: disable optimisations, compile with debug symbols. + <tt>DISPTOOLS_CUDA_SUPPORT=ON</tt>: enable CUDA support.
First, be sure that [mingw](https://mingw-w64.org), CMake and Python are installed and their executables [are in your PATH](https://docs.python.org/3/using/windows.html#excursus-setting-environment-variables).
Ensure that <tt>gcc</tt> is working correctly:
Ensure that <tt>distutils</tt> correctly recognises your version of Visual Studio (even when using <tt>mingw</tt>). Open the file <tt>C:\Users\yourname\AppData\Local\Programs\Python\Python3x\Lib\distutils\cygwinccompiler.py</tt> (the exact location may vary according to your setup) and check that your version of Visual Studio is present in the function <tt>get_msvcr()</tt>; if not, adjust it according to the following:
Ensure that the library <tt>vcruntime140.dll</tt> is present in your library path. Otherwise, download it and place it in <tt>C:\Users\yourname\AppData\Local\Programs\Python\Python3x\libs</tt> (the exact path may vary according to your setup).
Clone the sources of this package with <tt>git</tt>, or download and extract them as a <tt>zip</tt> archive. Move to the root folder of the sources (<tt>C:\Users\yourname\disptools</tt> in this example), specify the right compiler, and launch the setup script to build and install the package.
Support
The complete documentation for this package is available on https://martinopilia.com/disptools.
Find more information at:
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