The parallel strategy that can effectively improve the rendering speed and the algorithm efficiency is proposed on the basis of lntranet and common-configuration computers. Several kernel techniques are introduced respectively, including the basic concepts of parallel volume rendering and visualization, Master-Slave-Collector mode, load balance, pool-of task and pool-of result. The Master-Slave-Collector computation mode presented can decrease computing time, attain load balance,and improve the rending speed effectively without reducing image quality. Experimental results demonstrate that this method provides promising and real-time results to play great role in clinic and research field, which balances the computational speed and memory requirements.%以内部网络和普通配置计算机为实验平台,研究大规模数据集的并行体绘制的实现方法,以提高绘制速度和算法效率.分别介绍并行可视化、Master-Slave-Collector模式、负载平衡、任务池和结果池等关键技术.在传统的Master-Slave模式基础上的改进模式Master-Slave-Collector,具有减少计算时间.实现负载平衡、提高绘制效率等优点.实验结果表明,该方法较好地解决了运算速度和内存空间这两大难题,效果良好,实时性强,在临床诊断和科学研究中发挥重要作用.
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