An Ultrasound-Guided Tumor Puncture Framework With Vascular Avoidance for Human–Machine Collaborative Biopsy

Ultrasound (US) imaging has gained widespread application in guiding biopsy procedures. However, conventional manual US-guided biopsy remains limited by occupational exposure risks, limited accuracy in vessel and lesion identification, and strong dependence on operator proficiency. To address these challenges, we propose a tumor biopsy framework centered on a tele-assisted robotic system. The proposed framework, based on visual servoing control with a Kalman filter–assisted PD strategy and a leader–follower human–machine collaboration scheme, achieves high-precision puncture around the incision site, thereby enabling real-time tumor localization and vascular avoidance. At the end effector, a two-degree-of-freedom (2-DOF) remote center-of-motion (RCM) mechanism enables concurrent operation of the US probe and biopsy needle within confined spaces. In addition, a geometric quantification strategy based on spatial calibration is introduced to support millimeter-level error assessment. Performance was evaluated in silicone phantoms across three puncture modes. Compared with conventional manual puncture, the robotic system achieved a mean positioning error of 2.00±0.54 mm (a 47.8% improvement) and an angular error of 4.81°±1.10° (a 36.3% improvement), meeting clinical requirements for biopsy guidance. These results indicate that the proposed framework can substantially enhance procedural accuracy while reducing dependence on operator skill and clinical experience, thereby holding promise for safer and more reliable US-guided biopsy. The Project link: https://github.com/LinfieWang/HMC-Biopsy.