Graph Based Microscopic Images Semi and Unsupervised Classification and Segmentation

In this paper, we propose a general formulation of discrete functional regularization on weighted graphs. This framework can be used to on any multi-dimensional data living on graphs of arbitrary topologies. But, in this work, we focus on the microscopic image segmentation and classification with a semi and unsupervised schemes. Moreover, to provide a fast image segmentation we propose a graph based image simplification as a pre-processing step. Biological elements contained in images such as cells, cytoplasm and nuclei are segmented and classified with this image simplification and the label diffusion processes on weighted graphs. Keywords—Discrete regularization, weighted graphs, microscopical images, image simplification, semi-supervised, unsupervised, segmentation, classification.