Optimization of retraction in neurosurgery to avoid damage caused by deformation of brain tissues

Akira Fukuhara, Teppei Tsujita, Kazuya Sase, Atsushi Konno, Xin Jiang, Satoko Abiko, Masaru Uchiyama

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

2 Citations (Scopus)

Abstract

In neurosurgery, effects of deformation should be considered to avoid damaging brain tissues. The goal of this study is to develop an automatic path planner considering the deformation of brain tissues. This paper shows a scheme which combines FEM (Finite Element Method) and an optimization method for optimization of retraction in order to approach a deep part of a brain. Also, evaluations of two optimization results are discussed. One optimization is for retraction of a simple shape model for comparing two solvers, Pattern Search and Genetic Algorithm. Pattern Search Algorithm obtained maximum view size for the simple model when the principal stress of the tissue is not more than the threshold 500 (Pa). The other optimization is for retraction of a brain fissure model. Based on the result of the simple shape model, Pattern Search Algorithm is used for this optimization. It successfully generated optimal position and posture of a spatula for opening the fissure model which has same mechanical property with the human brain. These results show the effectiveness of the proposed scheme.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages588-594
Number of pages7
ISBN (Electronic)9781479973965
DOIs
Publication statusPublished - 2014 Apr 20
Externally publishedYes
Event2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014 - Bali, Indonesia
Duration: 2014 Dec 52014 Dec 10

Other

Other2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
Country/TerritoryIndonesia
CityBali
Period14/12/514/12/10

ASJC Scopus subject areas

  • Biotechnology
  • Artificial Intelligence
  • Human-Computer Interaction

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