April 24, 2024International Journal of Computer Assisted Radiology and SurgeryOpen Access

Efficient EndoNeRF reconstruction and its application for data-driven surgical simulation

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Authors

YWYuehao WangXi'an University of Science and Technology BGBingchen GongÉcole Polytechnique YLYonghao LongChinese University of Hong Kong

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Implication

Computational framework demonstrates fast surgical scene reconstruction and soft tissue simulation, suggesting utility for virtual surgery training and planning.

Key Points

The data-driven framework achieves high-quality surgical scene 3D reconstruction using a fast neural radiance field, outperforming traditional approaches on large tissue deformations.
An automated creation pipeline generates interactive surgical simulation environments using a closed mesh extraction algorithm, converting continuous volumes into surface meshes.
Finite element method and material point method simulations demonstrate practical utility, indicating strong potential to enhance clinical education and data-driven surgery planning.

Cite This Study

Wang et al. (2024) studied this question.

synapsesocial.com/papers/68e6dd4fb6db643587658cf5 https://doi.org/10.1007/s11548-024-03114-1

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Implication

Computational framework demonstrates fast surgical scene reconstruction and soft tissue simulation, suggesting utility for virtual surgery training and planning.

Efficient EndoNeRF reconstruction and its application for data-driven surgical simulation

Discussion

Member takes

Implication

Key Points

Cite This Study

Efficient EndoNeRF reconstruction and its application for data-driven surgical simulation

Discussion

Member takes

Implication

Key Points

Cite This Study

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