算法是规则体数据等值面抽取的经典算法。
The Marching Cube algorithm is the classical iso-surface extracting algorithm in regular volume data.
根据插值得到的矿床规则体数据的品位空间分布，将体数据分为若干段。
According to the grade spatial distribution of regular volume data from interpolation, the deposit volume data was divided into several sections.
移动立方体(MC)算法是基于规则体数据抽取等值面的经典算法，本文最后设计开发了一个基于MC算法的医学图像三维重建系统。
Marching cubes (MC) algorithm is a classical algorithm to extract iso-surface from regular volume data. At last, a medical images reconstruction system based on MC algorithm is developed.
然后，根据心电及角度信号提取正确原始切片图像，进行预处理，并利用三维直接匹配插值方法对旋转扫描超声心动图像进行插值，获得规则体数据。
After pre processing, the technique of direct 3d interpolation for rotational scanning images was used to convert the original rotary scanning images into regular volume data.
通过品位与储量等矿石属性计算的实现，为矿床的三维可视化仿真提供体素处理手段。首先对原始采样数据进行预处理，以构造满足需要的规则体数据；
Through the process of grade and reserve calculation, a method of dealing with voxel for visualization technology and its applications in an integrated simulation system were provided for deposits.
实际算例表明，此系统可较好实现历史故障数据的管理和故障诊断规则获取的一体化。
The calculation of a real case shows that this system can well implement the integration of management of historical fault data and fault. Diagnosis rule acquisition.
这些数据模型包括全要素的结构化不规则三角网(TIN)与GIS一体化的数据模型以及网状模型。
These data models include the unified model of all essential factor's structuralized triangulated irregular network (TIN) model and GIS as well as network model.
系统实现“四库一体化”结构，提出全新的方法库概念和适合于大体量知识库的产生式规则法、框架法、关系数据库法结合的知识表达体系。
A new concept of method base and knowledge expressing system by combination of production rule method, frame method and data base method appropriate to big knowledge base was proposed.
介绍了在数据立方体上对于不同可信度的数据进行分块的方法，阐述了基于数据立方体分块的多维关联规则挖掘的算法。
This paper introduces partition method in data cube with different confidence, expatiates on multidimensional association rule data mining algorithm based on data cube partition.
非规则数据场的体绘制是可视化的一个热点和难点。
Volume rendering of irregular data field is a hot but knotty field in VISC recently.
为了改善在大数据量时体素化效率不高的缺点，针对三角形不规则网(TIN)模型的三角网特性，提出了一种快速简单的体素化算法。
IN order to improve the voxelization efficiency of large data, a fast and simple voxelization algorithm was proposed for the Triangulated Irregular Network (TIN) model.
为了改善在大数据量时体素化效率不高的缺点，针对三角形不规则网(TIN)模型的三角网特性，提出了一种快速简单的体素化算法。
IN order to improve the voxelization efficiency of large data, a fast and simple voxelization algorithm was proposed for the Triangulated Irregular Network (TIN) model.
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