Real-time nonlinear FEM with neural network for simulating soft organ model deformation.

Ken'ichi Morooka, Xian Chen, Ryo Kurazume, Seiichi Uchida, Kenji Hara, Yumi Iwashita, Makoto Hashizume

Research output: Contribution to journalArticle

Abstract

This paper presents a new method for simulating the deformation of organ models by using a neural network. The proposed method is based on the idea proposed by Chen et al. that a deformed model can be estimated from the superposition of basic deformation modes. The neural network finds a relationship between external forces and the models deformed by the forces. The experimental results show that the trained network can achieve a real-time simulation while keeping the acceptable accuracy compared with the nonlinear FEM computation.

Original languageEnglish
Pages (from-to)742-749
Number of pages8
JournalMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Volume11
Issue numberPt 2
Publication statusPublished - Jan 1 2008

All Science Journal Classification (ASJC) codes

  • Medicine(all)

Cite this

Real-time nonlinear FEM with neural network for simulating soft organ model deformation. / Morooka, Ken'ichi; Chen, Xian; Kurazume, Ryo; Uchida, Seiichi; Hara, Kenji; Iwashita, Yumi; Hashizume, Makoto.

In: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, Vol. 11, No. Pt 2, 01.01.2008, p. 742-749.

Research output: Contribution to journalArticle

Morooka, Ken'ichi ; Chen, Xian ; Kurazume, Ryo ; Uchida, Seiichi ; Hara, Kenji ; Iwashita, Yumi ; Hashizume, Makoto. / Real-time nonlinear FEM with neural network for simulating soft organ model deformation. In: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 2008 ; Vol. 11, No. Pt 2. pp. 742-749.
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