仅用单目相机实现精准3D重建，助力微创手术自主导航
From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction
- 基于单目RGB图像构建解剖结构的分割点云
- 在多个指标上优于或媲美双目/深度相机的3D映射效果
- 适用于空间受限的微创手术，推动手术机器人自动化
外科自动化需要精确的场景感知与理解。现有方法依赖体积庞大的深度相机生成解剖结构地图，但难以适配空间受限的临床场景。单目相机体积小，适合微创手术，但需额外处理才能实现3D场景理解。本文提出一种仅使用RGB图像的3D映射流程，生成目标解剖结构的分割点云。为确保重建精度，我们对比了多种结构光运动算法在气道阻塞区域的性能表现，并在肿瘤切除这一下游任务中测试该流程。在多项评估指标中，包括术后组织模型评价，本方法表现可媲美甚至超越RGB-D相机，证明在微创手术中仅靠单目相机即可实现高精度自动化引导。此项研究是迈向手术机器人完全自主的重要一步。
原文摘要 · Abstract (English)
Surgical automation requires precise guidance and understanding of the scene. Current methods in the literature rely on bulky depth cameras to create maps of the anatomy, however this does not translate well to space-limited clinical applications. Monocular cameras are small and allow minimally invasive surgeries in tight spaces but additional processing is required to generate 3D scene understanding. We propose a 3D mapping pipeline that uses only RGB images to create segmented point clouds of the target anatomy. To ensure the most precise reconstruction, we compare different structure from motion algorithms' performance on mapping the central airway obstructions, and test the pipeline on a downstream task of tumor resection. In several metrics, including post-procedure tissue model evaluation, our pipeline performs comparably to RGB-D cameras and, in some cases, even surpasses their performance. These promising results demonstrate that automation guidance can be achieved in minimally invasive procedures with monocular cameras. This study is a step toward the complete autonomy of surgical robots.
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