This paper presents CIS, a biomedical simulation framework based on the markov random field (MRF). CIS is a discrete domain 2-D simulation framework emphasizing on the spatial interactions of biomedical entities. The probability model within the MRF framework facilitates the construction of more realistic models than deterministic differential equation approaches and cellular automata. The global phenomenon in CIS are dictated by the local conditional probabilities. In addition, multiscale MRF is potentially useful for the modelling of complex biomedical phenomenon in multiple spatial and time scales. The methodology and procedure of CIS for a biomedical simulation is presented using the scenario of tumor-induced hypoxia and angiogenesis as an example. The goal of this research is to unveil the complex appearances of biomedical phenomenon using mathematical models, thus enhancing our understanding on the secrets of life.
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