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Real-time simulation for multi-component biomechanical analysis using localized tissue constraint progressive transfer learning.
Jiang, Jiaxi; Fu, Tianyu; Liu, Jiaqi; Wang, Yuanyuan; Fan, Jingfan; Song, Hong; Xiao, Deqiang; Wang, Yongtian; Yang, Jian.
Afiliación
  • Jiang J; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
  • Fu T; School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China. Electronic address: fty0718@bit.edu.cn.
  • Liu J; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
  • Wang Y; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
  • Fan J; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
  • Song H; School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China.
  • Xiao D; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.
  • Wang Y; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China. Electronic address: wyt@bit.edu.cn.
  • Yang J; School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China. Electronic address: jyang@bit.edu.cn.
J Mech Behav Biomed Mater ; 158: 106682, 2024 Oct.
Article en En | MEDLINE | ID: mdl-39142234
ABSTRACT
In virtual surgical training, it is crucial to achieve real-time, high-fidelity simulation of the tissue deformation. The anisotropic and nonlinear characteristics of the organ with multi-component make accurate real-time deformation simulation difficult. A localized tissue constraint progressive transfer learning method is proposed in this paper, where the base-compensated dual-output transfer learning strategy and the localized tissue constraint progressive learning architecture are developed. The proposed strategy enriches the multi-component biomechanical dataset to fully represent complex force-displacement with minimal high-quality data. Meanwhile, the proposed architecture adopts focused and progressive model to accurately describe tissues with varied biomechanical properties rather than singular homogeneous model. We made comparison with 4 state-of-the-art (SOTA) methods in simulating multi-component biomechanical deformations of organs with 100 pairs of testing data. Results show that the accuracy of our method is 50% higher than other methods in different validation matrix. And our method can stably simulate the deformations in 0.005 s per frame, which largely improves the computing efficiency.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fenómenos Mecánicos Límite: Humans Idioma: En Revista: J Mech Behav Biomed Mater Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fenómenos Mecánicos Límite: Humans Idioma: En Revista: J Mech Behav Biomed Mater Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos