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We propose a novel Markovian segmentation model which takes into account edge information. By construction, the model uses only pairwise interactions and its energy is sub modular. Thus the exact energy minima is obtained via a max-flow/min-cut algorithm. The method has been quantitatively evaluated on synthetic images as well as on fluorescence microscopic images of live cells.
This paper presents a novel computer vision system for automated identification of vesicle-plasma membrane fusion events in image sequences obtained from Total Internal Reflection Fluorescence (TIRF) microscopes. Identification of such events is important in order to better understand the process of exocytosis in cells. Manual analysis of thousands of images is painstakingly slow and subjective since...
Spatio-temporal dynamics within cells can now be recorded on film at appropriate resolutions thanks to advances made in fluorescence microscopy technologies. Even the single-particle tracking technique is now being applied to observations of biological molecules. Conversely, little is known about how reaction diffusion at the molecular level affects properties at the cellular level. Therefore, we...
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