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

Abstract

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
Pages188-192
Number of pages5
ISBN (Print)9781532377914
DOIs
Publication statusPublished - Aug 8 2018
Externally publishedYes
Event2018 World Automation Congress, WAC 2018 - Stevenson, United States
Duration: Jun 3 2018Jun 6 2018

Publication series

NameWorld Automation Congress Proceedings
Volume2018-June
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832

Other

Other2018 World Automation Congress, WAC 2018
CountryUnited States
CityStevenson
Period6/3/186/6/18

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Morooka, K., Miyauchi, S., Chen, X., & Kurazume, R. (2018). Hexahedron Model Generation of Human Organ by Self-Organizing Deformable Model. In 2018 World Automation Congress, WAC 2018 (pp. 188-192). [8430386] (World Automation Congress Proceedings; Vol. 2018-June). IEEE Computer Society. https://doi.org/10.23919/WAC.2018.8430386