Improved marching cubes using novel adjacent lookup table and random sampling for medical object-specific 3D visualization

The marching cubes (MC) algorithm is a common  routine  to  extract  isosurfaces  from  volumetric  dataset.  This  method  suffers  from  the  exhaustive  accessingcubes sequentially and the failure of directly separating theisosurfaces.  To  address  this,  an  improved  MC  algorithmcalled AlutMC is proposed to track connected surfaces bycombining a new adjacent lookup table and random sam-pling technique. AlutMC has a natural ability to separatethe isosurfaces related to different components, which canefficiently segment 3D objects without extra expenditure andhelpful for visualizing medical objects. Experimental resultson  three  test  data  sets  show  the  computational  efficiencyin  identifying  isosurfaces.  Additionally,  it  is  simple  and efficient, not requiring complex data structure, and can beused as is into the MC and its improvements because it isquite cost-effective and self-contained.