Hexahedron Model Generation of Human Organ by Self-Organizing Deformable Model

Ken'ichi Morooka, Shoko Miyauchi, Xian Chen, Ryo Kurazume

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper presents a new method for generating object mesh models composed of hexahedra. The proposed method is based on a self-organizing deformable model (SDM) which is a deformable surface model guided by competitive learning and an energy minimization approach. Extending the SDM, the proposed method generates a hexahedral mesh model of a target object by fitting a cuboid composed of rectangular voxels to the object. Moreover, the shape of each hexahedron in the model is corrected by dividing the hexahedron into sub-hexahedra and moving the nodes of the hexahedron. From our experimental results, the proposed method obtains the hexahedral mesh model which consists of many regular hexahedra while recovering the shape of the object.

Original languageEnglish
Title of host publication2018 World Automation Congress, WAC 2018
PublisherIEEE Computer Society
Number of pages5
ISBN (Print)9781532377914
Publication statusPublished - Aug 8 2018
Event2018 World Automation Congress, WAC 2018 - Stevenson, United States
Duration: Jun 3 2018Jun 6 2018

Publication series

NameWorld Automation Congress Proceedings
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832


Conference2018 World Automation Congress, WAC 2018
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering


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