Preliminary Research on Autonomous Robotic System for DDH Ultrasound Examination

Ultrasound examination for developmental dysplasia of the hip (DDH) in infants is highly dependent on operator experience, leading to inconsistent imaging quality and poor reproducibility between sonographers. This study proposes an autonomous robotic ultrasound system to improve the standardization and automation of hip ultrasound examinations. The system consists of a robotic arm, a six-axis force/torque sensor, an RGB-D camera and an ultrasound probe, integrating multiple functions including contact force control, visual localization, deep-learning-based segmentation and ultrasound image screening. To ensure stability and safety during scanning, an admittance-based hybrid force/position control strategy is adopted to achieve constant contact force control. For Graf standard plane acquisition, a stage-wise search strategy is designed, in which the search space is progressively narrowed through femoral head searching and multi-angle scanning. The optimal Graf standard plane is then automatically selected by combining image segmentation with a scoring mechanism. A customized hip phantom was used for validation. Experimental results show that the Dice coefficient for femoral head segmentation reaches 0.872, while the average Dice coefficient for multi-structure segmentation reaches 0.866. In 30 autonomous scanning trials, the success rate of Graf standard plane acquisition is 90.0%. Meanwhile, the system can maintain the contact force stably within the target range during scanning, validating the effectiveness of the force control strategy. These results indicate that the proposed robotic system, image recognition algorithm and visual servo control strategy exhibit favorable safety and feasibility, providing an innovative solution for automated infant hip ultrasound examination of DDH.