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 journalArticlepeer-review

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)

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