融合构型查找表与邻接查找子表的改进MC方法
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国家自然科学基金资助项目(60903142, 61190122);重庆市自然科学基金资助项目(CSTC2009BB3192,CSTC2011jjA40024);重庆市科技攻关项目(CSTC2009AB5196);中央高校基本科研业务费资助项目(CDJZR10120003, CDJXS10120010);中国博士后基金资助项目(2012M521677)


Improved marching cubes by combining case lookup table and adjacency lookup sub-table
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    摘要:

    针对医学图像三维可视化中移动立方体面绘制算法(marching cubes,MC)执行速度慢、效率不高的问题,提出了融合构型查找表与邻接查找子表的改进MC方法。该方法通过显性构建邻接查找子表约束体元搜索路径,使面绘制时只处理有效体元,根据邻接查找子表特点设计堆栈结构实现搜索算法,不仅提高了算法访问效率,而且减少了临时存储空间。在可视化工具包(VTK)下用改进MC方法对人体脚、胸腔、头部的CT数据集进行三维重建实验,结果表明在不损失重建质量的前提下,重建过程中遍历立方体数目缩短95%左右,重建时间缩短20%左右,提高了MC方法的执行速度和重建效率。

    Abstract:

    The marching cubes (MC) is an effective surface rendering method in three-dimensional visualization for medical image sequence. However, most existing MC algorithms are slow and inefficient because they have to process all the cubes for isosurface extraction. An efficient MC algorithm is proposed by combing the case lookup table and a novel adjacent lookup sub-table to exclude unrelated empty cubes. By explicitly building the fix-length adjacent lookup sub-table that is independent on image sequences, the volumes elements are constrained to those only intersect with the isosurface. Both execution time and temporary storage space are further reduced by incorporating the heap data structure in algorithmic implementation. Experimental results on human head, chest foot CT data sets by using the visualization toolkit package show that the traversal cubes decreases by 95%, and the reconstruction time decreases by 20% without any loss of reconstruction quality. Therefore, the proposed method can remarkably speed up the rendering time and be easily integrated into 3D visualization for clinical application.

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王旭初,王赞,牛彦敏,张绍祥,谭立文,晋军.融合构型查找表与邻接查找子表的改进MC方法[J].重庆大学学报,2012,35(12):68-77.

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  • 在线发布日期: 2013-01-10
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