Graph-Cut Library for Biomedical Image Analysis
Pavel Matula · 2012
We have developed an open-source cross-platform library focusing on combinatorial optimization via graph cuts. It can be used in many digital image analysis tasks; especially for finding optimal solutions to energy minimization based discrete labeling problems such as image segmentation (e.g. Chan-Vese or Mumford-Shah segmentation model or geodesic active contour model). The library is being developed in C++ and places emphasis especially on speed and low memory usage as well as clean and extensible object-oriented design. It considers the aspects typical for biomedical image analysis, e.g. anisotropy, n-dimensionality, large images. MATLAB interface for all segmentation algorithms in the library is also available. We will present the library and examples of its usage in fluorescence microscopy image