FLex:用于立体内镜视频的联合姿势和动态辐射场优化.
Florian Stilz1, Mert Karaoglu2,3, Felix Tristram2
1Chair for Computer Aided Medical Procedures, Technical University of Munich, Boltzmannstr. 3, 85748, Garching, Germany. nguyenthikimson.haui@gmail.com.
本研究介绍了流量优化的局部六面平面 (FLex) 用于重建移动的立体内镜场景. 在没有外部跟踪的情况下,FLex可以准确地重建手术场景和估计摄像头姿势,从而改善医疗应用.
科学领域:
- 医学成像医学成像
- 计算机视觉 计算机视觉 计算机视觉
- 手术技术手术技术的使用
背景情况:
- 内镜场景重建对于医学培训和分析至关重要.
- 目前的方法与动态环境,有限的变形和依赖外部跟踪作斗争.
研究的目的:
- 开发一种新的方法,用于在动态环境中重建移动的立体内镜场景.
- 克服现有方法的局限性,通过实现准确的重建和摄像头姿势估计,而无需外部跟踪.
主要方法:
- 引入了流量优化的局部六面平面 (FLex).
- 隐含地将场景分成重叠的4D神经辐射场 (NeRFs).
- 采用渐进式优化来进行关节重建和从头开始对摄像头姿势进行估计.
主要成果:
- 测试了多达5000的序列,比以前的方法长五倍.
- 为显著更长的手术视频实现了高度详细的重建.
- 消除了对外部跟踪信息的需求.
结论:
- 在具有挑战性的手术场景中,FLex可用于移动立体内镜的准确重建和摄像头姿势估计.
- 推进神经染的适用性,以改善手术场景的理解.
- 代码和数据将会发布.
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