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。
The image registering, image segmentation, pixel data set construction and 3d special interpolation are the key technologies in medical images 3d reconstruction.
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。
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