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This study presents a novel algorithm for assembling cell pore structure to enhance the connectivity of porous medium used in the medical science. Firstly based on sample learning, the designed cell pore structure is assembled and thus the parametric pore model can be established. Then the model is optimized by using random decision forests as evaluator and KD tree as the nearest neighbor searching area in the high dimensional space. Finally the parametric model can be transformed to soliddoi:10.19026/ajfst.5.3165 fatcat:gfhozwu6r5bdvidpjzttw44iue