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Related Concept Videos

Deformations in a Transverse Cross Section01:21

Deformations in a Transverse Cross Section

When a material is subjected to uniaxial stress, it elongates or contracts in the direction of the applied force, and also undergoes changes in the perpendicular directions. This behavior is crucial for understanding how materials behave under stress and is governed by mechanical properties such as Poisson's ratio v, which measures the ratio of transverse strain to axial strain.
As the material stretches, it expands or contracts in orthogonal directions to the load. This phenomenon varies...
Transformation of Plane Strain01:12

Transformation of Plane Strain

When analyzing elongated structures like bars subjected to uniformly distributed loads, it is essential to understand the transformation of plane strain when coordinate axes are rotated. This transformation helps to assess how material deformation characteristics vary with orientation, which is crucial in materials science and structural engineering.
Under plane strain conditions, typical for members where one dimension significantly exceeds the others, deformations and resultant strains are...

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Related Experiment Video

Updated: Jun 10, 2026

Anatomically Inspired Three-dimensional Micro-tissue Engineered Neural Networks for Nervous System Reconstruction, Modulation, and Modeling
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Efficient Deformable Tissue Reconstruction via Orthogonal Neural Plane.

Chen Yang, Kailing Wang, Yuehao Wang

    IEEE Transactions on Medical Imaging
    |April 16, 2024
    PubMed
    Summary

    Fast Orthogonal Plane (Forplane) reconstructs deformable tissues using neural radiance fields (NeRF) for improved surgical imaging. This efficient framework accelerates both training and inference, enhancing real-time surgical applications.

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    Area of Science:

    • Medical Imaging
    • Computer Vision
    • Surgical Technology

    Background:

    • Intraoperative imaging is crucial for advanced surgical systems, but current methods for reconstructing deformable tissues are either slow or produce low-quality renderings.
    • Existing techniques often require extensive computational resources and time, limiting their real-world surgical applicability.

    Purpose of the Study:

    • To introduce Fast Orthogonal Plane (Forplane), a novel and efficient framework for in vivo deformable tissue reconstruction.
    • To significantly improve the speed and efficiency of intraoperative imaging while maintaining or enhancing rendering quality.

    Main Methods:

    • Forplane utilizes neural radiance fields (NeRF) by conceptualizing surgical procedures as 4D volumes, decomposed into static and dynamic fields of orthogonal neural planes.
    • A spatiotemporal importance sampling scheme addresses tool occlusion and motion, while an efficient ray marching method skips empty regions to accelerate processing.
    • The framework supports both binocular and monocular endoscopy videos.

    Main Results:

    • Forplane demonstrated over 100x acceleration in optimization and over 15x acceleration in inference compared to existing methods.
    • The framework maintained or improved rendering quality across various non-rigid deformations on the EndoNeRF and Hamlyn datasets.
    • Significant performance gains were observed in both optimization and inference speeds.

    Conclusions:

    • Forplane offers a substantial advancement in intraoperative imaging for deformable tissue reconstruction.
    • The framework's efficiency and effectiveness make it a promising tool for future real-time surgical applications.
    • The open-source code facilitates further research and development in this area.