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by Thierry P├ęcot

The C-CRAFT software enables to segment particles and estimate background in 2D or 3D image sequences.

We consider a statistical Bayesian approach in the framework of conditional random fields. Within this approach, we take advantage of a robust detection measure for fluorescence microscopy based on the distribution of neighbor patch similarity. We formulate the vesicle segmentation and background estimation as a global energy minimization problem. An iterative scheme to jointly segment vesicles and background is proposed for 2D-3D fluorescence image sequences.

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