Plug-in for visualizing 3D tool tracking from videos of Minimally Invasive Surgeries
This addresses the problem of limited 2D views and hardware integration in surgery for medical practitioners, but it appears incremental as it builds on existing tracking techniques.
The paper tackled instrument tracking and 3D visualization in minimally invasive surgery by developing a method based on 2D segmentation and kinematics, achieving negligible errors in motion estimates.
This paper tackles instrument tracking and 3D visualization challenges in minimally invasive surgery (MIS), crucial for computer-assisted interventions. Conventional and robot-assisted MIS encounter issues with limited 2D camera projections and minimal hardware integration. The objective is to track and visualize the entire surgical instrument, including shaft and metallic clasper, enabling safe navigation within the surgical environment. The proposed method involves 2D tracking based on segmentation maps, facilitating creation of labeled dataset without extensive ground-truth knowledge. Geometric changes in 2D intervals express motion, and kinematics based algorithms process results into 3D tracking information. Synthesized and experimental results in 2D and 3D motion estimates demonstrate negligible errors, validating the method for labeling and motion tracking of instruments in MIS videos. The conclusion underscores the proposed 2D segmentation technique's simplicity and computational efficiency, emphasizing its potential as direct plug-in for 3D visualization in instrument tracking and MIS practices.