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A New Clustering Segmentation Algorithm of 3D Medical Data Field Based on Density-isoline

机译:基于密度 - isoline的3D医学数据字段的新聚类分割算法

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摘要

Direct 3D volume segmentation is one of the difficult and hot research fields in 3D medical data field processing. Using the clustering and analyzing techniques of data mining, a new clustering and segmentation algorithm is presented Firstly, According to the physical means of the medical data, the data field is preprocessed to speed up succeed processing. Secondly, the paper deduces and analyzes the clustering and segmentation algorithm and presents some methods to increase the process speed Finally, the experimental results show that the algorithm has high accuracy when used to segment complicated medical tissue and can improve process speed greatly.
机译:直接3D卷分割是3D医疗数据现场处理中的困难和热门研究领域之一。使用数据挖掘的聚类和分析技术,首先根据医疗数据的物理手段来呈现新的聚类和分段算法,数据字段被预处理以加速成功处理。其次,纸张推断并分析了聚类和分割算法,并提出了一些方法来最终提高过程速度,实验结果表明,当算法用于分割复杂的医疗组织并大大提高过程速度时,该算法具有高精度。

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