This is an implementation of level set image segmentation using OpenCL.
The speed function is defined as -alpha*(epsilon-|T-intensity|)+(1-alpha)*curvature.
See http://www.eriksmistad.no/level-set-segmentation-on-gpus-using-opencl/ for more information on level sets and this implementation.
See LICENSE file for license information.
- OpenCL (You need an OpenCL implementation installed (AMD, NVIDIA, Intel, Apple...)
- Submodules SIPL and OpenCLUtilities (no need to install separately, however remember to initialize them "git submodule update" if you are cloning this repo)
- GTK2, which SIPL use for displaying the results (
sudo apt-get install libgtk2.0-dev)
Use CMake and the provided CMakeLists.txt file to compile this program. To compile on the run the example on Ubuntu, do the following:
cmake .
make
./levelSetSeg example_data/mr_brain.mhd result.mhd 100 100 100 10 2000 125 40 0.05 125 255The arguments for the program are:
./levelSetSeg inputFile.mhd outputFile.mhd seedX seedY seedZ seedRadius iterations threshold epsilon alpha [level window]
inputFile.mhd is the metadata file of the volume you want to process and outputFile.mhd the path to where the result should be stored.
seedX, seedY, seedZ defines a spherical seed point with a radius seedRadius.
Iterations is the total number of iterations and threshold, epsilon, alpha are parameters for the speed function -alpha*(epsilon-|T-intensity|)+(1-alpha)*curvature.
If the level and window arguments are set, the segmentation result will be displayed as an overlay to the input volume.
Run with provided example data: ./levelSetSeg example_data/mr_brain.mhd result.mhd 100 100 100 10 2000 125 40 0.05 125 255
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