¹Key Laboratory of Optoelectronic Technology and Systems of Ministry of Education, College of Optoelectronic Engineering, Chongqing University,Chongqing 400044, P.R.China
²College of Computer and Information Science, Chongqing Normal University, Chongqing 400050, P.R.China
³Department of Anatomy, College of Basic Medical Science, Third Military Medical University, Chongqing 400038, China

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Abstract—The marching cubes (MC) algorithm is a widely used routine to extract isosurfaces from volumetric data set. This method suffers from the exhaustive accessing cubes sequentially and the failure of directly separating the isosurfaces. To address this, an improved MC algorithm called AlutMC is proposed to track connected surfaces by combining a new adjacent lookup table and random sampling technique. AlutMC has a natural ability to separate the isosurfaces related to different components, which can efficiently segment 3D objects without extra expenditure and helpful for visualizing medical objects. Experimental results on three test data sets show the computational efficiency in identifying isosurfaces. Additionally, it is simple and efficient, not requiring complex data structure, and can be used as is into the MC and its improvements because it is quite cost-effective and self-contained.

Index Terms—Surface rendering, Isosurface extraction, Marching cubes, Lookup table, Isosurface separation, 3D object segmentation

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Cite: Xuchu Wang, Yanmin Niub, Li-wen Tan, Shao-Xiang Zhang, "Improved marching cubes using novel adjacent lookup table and random sampling for medical object-specific 3D visualization," Journal of Software vol. 9, no. 10, pp. 2528-2537, 2014.