/NiftySeg

Primary LanguageC++BSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

NIFTYSEG PACKAGE

1 - WHAT DOES THE PACKAGE CONTAIN?

This project, lead by Jorge Cardoso at King's College London, contains programs to perform EM based segmentation of images in nifti or analyse format. NiftySeg is an open-source toolkit licensed under the BSD license. It also contains a package of label fusion algorithms (MV, STAPLE, SBA) with different types of ranking strategies. Features: LoAd: Locally Adaptive Brain Segmentation General Purpose EM segmentation Single and Multi-label Fusion package To download the latest version, please check out the code by copying the following line to the termini;:

git clone git@github.com:KCL-BMEIS/NiftySeg.git niftyseg

A packaged stable release is also available in the files menu above. This release in only updated once in a while, thus, it does not have the latest developments. See below for installation instructions.

2 - HOW TO BUILD THE CODE

Download The code can be easily build using cmake (http://www.cmake.org/). The latest version can be downloaded from http://www.cmake.org/cmake/resources/software.html

To download the latest version, please check out the code by copying the following line to the terminal:

git clone git@github.com:KCL-BMEIS/NiftySeg.git niftyseg

A packaged stable release is also available at this website.

Linux & OSX

  • Build

Assuming that the code source are in the source path folder, you will have to first create a new folder, i.e. build path (step 1) and then to change directory to move into that folder (step 2).

mkdir build_path

cd build_path

There you will need to call ccmake (step 3a) in order to fill in the build options. If you don’t want to specify options, we could just use cmake (step 3b) and the default build values will be used.

ccmake source_path
cmake source_path

The main option in the ccmake gui are defined bellow:

> CMAKE BUILD INSTALL options are Release, RelWithDebInfo or Debug 
> INSTALL_PRIORS Will install the population atlas for the segmentation pipeline
> INSTALL_PRIORS_DIRECTORY Directory where the population atlas is going to be installed
> INSTALL_NIFTYREG Will fetch and automatically configure and install the niftireg package.

Once all the flags are properly filled in, just press the ”c” to configure the Make- file and then the ”g” key to generate them.

  • Install

In the prompt, you just have to make (step 4) first and then make install (step 5).

make 
make install

Windows

  • Build

The building process is the following:

  1. Get the source
  2. Create a new directory for the build: "niftyseg-build"
  3. Launch CMake-Gui, set the source path to "niftyseg" and the build path to "niftyseg-build" then hit configure
  4. Cmake will prompt you to select the generator, which means you'll need to select the Visual Studio version you have installed earlier
  5. Make sure the Use OpenMP option is enabled.
  6. Set the CMAKE_INSTALL_PREFIX to the folder where you want to install NiftySeg.
  7. Note, that if you want to install NiftySeg under Program Files, you'll need to create the folder yourself and explicitly apply full write permissions.
  8. Once the flags are set, hit configure and generate. This will generate the Visual Studio project files.
  • Install
  1. Go to "niftyseg-build", and launch NiftySeg.sln. This will start Visual Studio.
  2. In Visual Studio select build type, for generic use select Release and build the project (hit F7).
  3. Once the build finished Select and run the Install task (Right Click on Install > Project Only > Build only Install). This will install NiftySeg to the folder you selected earlier.
  4. Probably you'll want to add the install folder to your system path.

3 - LICENSE

Copyright (c) 2018, NiftySeg Development Team, United-Kingdom All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither the name of the University College London nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

4 - CONTACT

For any comments, please, feel free to contact M. Jorge Cardoso (manuel.cardoso@kcl.ac.uk).