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Research on the System of the Segmentation and Tracking of the Time Lapse of Neural Stem Cells

Adult neuron stem cells are a sort of cells hidden in some positions of adult nerve system. They have so good plasticity that can be artificially built by means of gene engineering or cell engineering and some other modern techniques in order to make them directional differentiation and to build up a kind of replacement of impairment in nerve, especially impairment in nerve center. How to find the law of the natural cleavage and prolification of neuron stem cells so that we can apply the certain progenitor cells of neuron stem cells then to culture them to become a sort of nerve organ which has ceratin function being used to cure the patients of neural disease by organ transplantation method. This project becomes harder and more popular in the world. Aided by the imaging analysis technique of digital image in computing science and the technique of high speed processing in signal and information, the tracking of neuron stem cells is studied. This project is still on an initial stage so far.The original images analysised in this dissertation are based on the time lapse image sequences of neuron stem cells acquired by Karin Althoff and Johan Degerman of Chalmers University of technology in Sweden. The first level segmentation called watershed segmentation is adopted by the automatic region-based seeded watershed segmentation implemented by the group of Center of Image Analysis in Uppsala University. A segmentation and tracking system has been set up on the base of the conditions above mentioned. The main characteristic of this system is the tracking algorithm combined with many kinds of segmentation algorithms in order to ensure the accuracy of tracking results. The main research and innovation contents are stated as following:1. As the outcome of watershed segmentation are not satifiying when imaging focus is changed in automatic images capturing, after the Hamilton-Jacobi equation based on level set method combined with geometric snake algorithm is

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