3D Distance Transformations with Feature Subtraction

  • Mike Janzen
  • Sudhanshu Kumar SemwalEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1069)


This paper presents a technique to implement three-dimensional distance transformation based on the city-block algorithm and selective removal of cells of interest using both serial and parallel techniques. We call this feature subtraction. One of the main benefits of feature subtraction is that the volume data could be representing as union of these subtracted features (e.g. spheres), replacing the cells in the volume data by a set of these disjointed spheres. The algorithm is implemented in the specialized graphics programming language called Processing Language.


3D distance transformation Sphere packing Medical applications 



We want to acknowledge the role Slicer3D Community has played in our research directions. Although we have implemented the code using Processing Language, we want to implement the Distance Transformations algorithms using 3D Slicer platform in future. The second author of this paper is also grateful to Dr. Arcady Godin who introduced Dr. Leonid Perlovsky, and Dr. Perlovsky’s work on Dynamic Logic, although not discussed in paper, was the motivation to start our work in 3D medical data visualization.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of ColoradoColorado SpringsUSA

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