Boundary Constraint-free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction

Fuente: arXiv
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Main Authors: Yang, Zixin, Simon, Richard, Merrell, Kelly, Linte, Cristian. A.
Format: Preprint
Published: 2024
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author Yang, Zixin
Simon, Richard
Merrell, Kelly
Linte, Cristian. A.
author_facet Yang, Zixin
Simon, Richard
Merrell, Kelly
Linte, Cristian. A.
contents In image-guided liver surgery, 3D-3D non-rigid registration methods play a crucial role in estimating the mapping between the preoperative model and the intraoperative surface represented as point clouds, addressing the challenge of tissue deformation. Typically, these methods incorporate a biomechanical model, represented as a finite element model (FEM), into the strain energy term to regularize a surface matching term. We propose a 3D-3D non-rigid registration method that incorporates a modified FEM into the surface matching term. The modified FEM alleviates the need to specify boundary conditions, which is achieved by modifying the stiffness matrix of a FEM and using diagonal loading for stabilization. As a result, the modified surface matching term does not require the specification of boundary conditions or an additional strain energy term to regularize the surface matching term. Optimization is achieved through an accelerated gradient algorithm, further enhanced by our proposed method for determining the optimal step size. We evaluated our method and compared it to several state-of-the-art methods across various datasets. Our straightforward and effective approach consistently outperformed or achieved comparable performance to the state-of-the-art methods. Our code and datasets are available at https://github.com/zixinyang9109/BCF-FEM.
format Preprint
id arxiv_https___arxiv_org_abs_2403_09964
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Boundary Constraint-free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction
Yang, Zixin
Simon, Richard
Merrell, Kelly
Linte, Cristian. A.
Image and Video Processing
Computer Vision and Pattern Recognition
In image-guided liver surgery, 3D-3D non-rigid registration methods play a crucial role in estimating the mapping between the preoperative model and the intraoperative surface represented as point clouds, addressing the challenge of tissue deformation. Typically, these methods incorporate a biomechanical model, represented as a finite element model (FEM), into the strain energy term to regularize a surface matching term. We propose a 3D-3D non-rigid registration method that incorporates a modified FEM into the surface matching term. The modified FEM alleviates the need to specify boundary conditions, which is achieved by modifying the stiffness matrix of a FEM and using diagonal loading for stabilization. As a result, the modified surface matching term does not require the specification of boundary conditions or an additional strain energy term to regularize the surface matching term. Optimization is achieved through an accelerated gradient algorithm, further enhanced by our proposed method for determining the optimal step size. We evaluated our method and compared it to several state-of-the-art methods across various datasets. Our straightforward and effective approach consistently outperformed or achieved comparable performance to the state-of-the-art methods. Our code and datasets are available at https://github.com/zixinyang9109/BCF-FEM.
title Boundary Constraint-free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction
topic Image and Video Processing
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2403.09964