English(EN) Endo-NeRF++: Uncertainty-Aware Neural Rendering with Multi-Resolution Hash Encoding for Dynamic Surgical Scene Reconstruction

Endo-NeRF++ 通过不确定性感知增强手术场景重建

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-31 04:00

研究人员开发了 Endo-NeRF++，一个先进的神经渲染框架，旨在改进动态手术场景的重建。该新系统通过引入不确定性感知来解决组织变形、遮挡和有限视角等挑战。关键增强功能包括用于详细解剖捕获的多分辨率哈希网格编码、用于运动期间稳定性的时间特征融合以及用于在复杂区域提高渲染质量的不确定性感知自适应采样。实验表明，与前代 EndoNeRF 相比，在 PSNR、SSIM 和 LPIPS 等指标上有了显著改进。 AI

影响提高了手术场景重建的准确性和时间连贯性，可能有助于机器人辅助手术。

排序理由这是一篇研究论文，详细介绍了一种在特定领域（手术场景）进行神经渲染的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Gousia Habib, Laura Ruotsalainen · 2026-07-31 04:00

Endo-NeRF++：用于动态手术场景重建的不确定性感知神经渲染与多分辨率哈希编码

arXiv:2607.27825v1 Announce Type: cross Abstract: Reconstructing dynamic surgical scenes is crucial for robot-assisted minimally invasive surgery; however, it continues to be difficult because of tissue deformation, occlusions, specular reflections, and restricted viewpoints. In …

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Endo-NeRF++：用于动态手术场景重建的不确定性感知神经渲染与多分辨率哈希编码

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