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适应性支持基于重量的立体声匹配与代差异精细化
Alexander Richter1,2, Till Steinmann1, Andreas Reichenbach1
1Electrical Instrumentation and Embedded Systems, Department of Microsystems Engineering, Albert-Ludwigs-Universität Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
这项研究引入了一种用于微创手术的新实时3D重建方法. 新型立体相匹配算法增强了深度感知和外科导航,克服了内镜成像挑战.
科学领域:
- 医疗成像医学成像
- 计算机视觉 计算机视觉
- 手术技术 手术技术
背景情况:
- 最少侵入性手术 (MIS) 从实时3D重建中受益,以改善深度感知和导航.
- 在MIS中的内镜成像面临着诸如镜面反射,低质感和组织变形等挑战.
研究的目的:
- 开发一种新的,决定性的和代的立体匹配方法,用于在MIS中准确的实时3D重建.
- 为了解决内镜成像的特殊限制,以改善外科可视化.
主要方法:
- 开发了一种使用自适应支权重的确定性和代立体匹配算法.
- 该方法在CUDA和C++中实现了实时性能.
- 在立体对应和内镜数据重建 (SCARED) 数据集和定制合成数据集上进行了评估.
主要成果:
- 在SCARED数据集8和9上,该方法在24.9FPS时分别达到3.79mm和3.61mm的平均绝对误差 (MAE).
- 在合成数据上,该方法表明MAE为140.06μm,根平均平方误差 (RMSE) 为251.9μm.
- 在具有挑战性的内镜条件下,性能与现有的决定性立体匹配方法相比或超过.
结论:
- 开发的方法为MIS提供了准确,确定性,实时的深度估计.
- 它为单拍3D重建,立体拼接和全场景建模提供了基础.
- 潜在的应用包括整合到外科导航,机器人辅助和增强现实系统中.
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