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首先，本文提出一种微机小动脉自动向心分级技术；其次，本文推广、改进了ＷｏｌｆｇａｎｇＳｃｈｒｎｉｎｅｒ的小动脉空间优化生长模型，提出信号灯追踪、阻力平衡和双准则求新增血管段末端点的新算法，并用这种模型和算法成功地在微机上模拟了猫缝痘肌（Ｓａｒｔｏｒｉｕｓ）小动脉的生长。最后，用自动向心分级技术对优化生长网络进行了自动分级，并将网络的各级直径的统计平均值，与Ａ．Ｋｏｌｌｅｒ的实验结果进行了比较［９］．
First of all, this paper proposes an automatic centripetal grading technique of arterioles. Secondly, this paper extends and improves Wolfgang Schrniner’s optimal growth model of small arteries, and proposes a new algorithm of signal tracking, resistance balance and double criteria for finding new end points of vascular segments , And using this model and algorithm to successfully simulate the growth of the small artery of Sartorius fossa on a microcomputer. Finally, the auto-centripetal grading technique is used to automatically classify the optimal growth network, and the statistical average of the diameters at all levels of the network, Koller’s experimental results were compared [9].