Adaptive Segmentation of Cells and Particles in Fluorescent Microscope Images

Microscope imaging is an indispensable tool in modern systems biology. In combination with fully automatic image analysis it allows for valuable insights into biological processes on the sub-cellular level and fosters understanding of biological systems. In this paper we present two new techniques for automatic segmentation of cell areas and included sub-cellular particles. A new cascaded and intensity-adaptive segmentation scheme based on coupled active contours is used to segment cell areas. Structures on the sub-cellular level, i.e. stress granules and processing bodies, are detected applying a scale-adaptive wavelet-based detection technique. Combining these results allows for complementary analysis of biological processes. It yields new insights into interactions between different particles and distributions of particles among different cells. Our experimental evaluations based on ground-truth data prove the high-quality of our segmentation results regarding these aims and open perspectives towards deeper insights into biological systems on the sub-cellular level.