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.
第四章介绍了我们实现的利用VRML进行医学体数据三维重建的工作；
The chapter 4 introduced the work of using VRML in medical body data 3D reconstruction which realized by us.
医学体数据三维可视化技术有着广泛的应用前景。
The 3-d Visualization technique on medical volume data has extensive application and broad prospects.
而图像的配准、图像分割、体数据集的构建、三维空间插值则是医学图像三维可视化实现过程中的关键技术环节。
The image registering, image segmentation, pixel data set construction and 3d special interpolation are the key technologies in medical images 3d reconstruction.
其中的体绘制方法直接对所有的体数据进行处理，有利于保留三维医学图像的细节信息，具有较好的绘制效果。
The volume rendering method does shading processes to all of the volume data directly, maintains the details of the medical images, and achieves better render results.
为提高三维医学数据场的分割效率和准确率，本文利用特征聚类技术，提出了一种新的基于改进K - means聚类的三维医学数据场的体分割算法。
A clustering segmentation algorithm based on an improved K-means clustering method is used to improve the efficiency and accuracy of 3d medical image segmentation.
为提高三维医学数据场的分割效率和准确率，本文利用特征聚类技术，提出了一种新的基于改进K - means聚类的三维医学数据场的体分割算法。
A clustering segmentation algorithm based on an improved K-means clustering method is used to improve the efficiency and accuracy of 3d medical image segmentation.
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