Brain volume mapping for constructing volumetric statistical shape model

Shoko Miyauchi, Ken'ichi Morooka, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume

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

1 Citation (Scopus)


We propose a new method for mapping onto a brain volume model including inner organs with complicated shapes such as lateral ventricles. The proposed method is based on a volumetric Self-organizing Deformable Model (vSDM) which allows to control the mapping positions of inner organs while preserving geometrical features before and after the mapping. The control sometimes causes the self-intersection of the volume model. The solution for the self-intersection in vSDM is to move vertices of the volume model. However, when the inner organ has complicated shape, the vertex movement cannot always correct the self-intersection. To solve this problem, we extend vSDM by introducing a new process of editing the mesh structure of the volume model. Moreover, by applying the proposed method to six brain volume models, a volumetric Statistical Shape Model (SSM) is constructed which represents the shape variations of not only brain surface but also brain inner organs. From experimental results, we confirmed the volumetric SSM has an acceptable performance compared with general surface SSMs generated by organ surface models.

Original languageEnglish
Title of host publicationInternational Forum on Medical Imaging in Asia 2019
EditorsHiroshi Fujita, Jong Hyo Kim, Feng Lin
ISBN (Electronic)9781510627758
Publication statusPublished - Jan 1 2019
EventInternational Forum on Medical Imaging in Asia 2019 - Singapore, Singapore
Duration: Jan 7 2019Jan 9 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceInternational Forum on Medical Imaging in Asia 2019

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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