From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction

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.

Multi Jet Fusion of Nylon-12: A Viable Method to 3D-print Concentric Tube Robots?

In this paper, we present a study on the viability of fabricating Concentric Tube Robots using Multi Jet Fusion (MJF) of Nylon-12, a type of elastic polymer commonly used in additive manufacturing. We note that Nylon-12 was already evaluated for the purpose of building CTRs in prior work, but fabrication was performed with Selective Laser Sintering (SLS), which produced unsatisfactory results. Our study is the first study to evaluate the suitability of MJF to 3Dprint CTRs.