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A Framework for Fast Automatic Robot Ultrasound Calibration

Ruixuan Li, Kenan Niu, Emmanuel Vander Poorten

发表年份
2021
引用次数
23

摘要

Ultrasound (US) has been increasingly used as medical imaging technology across various clinical diagnostic and therapeutic scenarios thanks to its availability and non-radiative nature. While 3D US probes are becoming available, most systems are still using 2D probes. For 3D US reconstruction based on 2D probes, US image calibration forms an essential step. Through calibration, one can find the transformation matrix between a coordinate frame attached to an optical marker or the robot’s end effector towards the coordinate frame of the US probe. Current US calibration methods usually require hereto lengthy free hand gestures as well as some manual interventions, which hampers the use and integration with advanced robotic systems. This paper introduces a reliable automatic calibration framework that is also fast. Demonstrated on a KUKA lightweight robot and 2D US probe, the full calibration procedure was completed in 224.8 seconds with a 1.29 mm mean 3D localization error. Within this procedure, camera-to-robot calibration was accomplished within only 47 seconds and reached a 0.17 mm mean error. Validation of the US image calibration was done through 3D printed model, leading to a mean deviation of 1.05 mm from the respective CAD models.

关键词

CalibrationComputer visionComputer scienceArtificial intelligenceRobotTransformation matrixCoordinate systemRobot calibrationTransformation (genetics)Frame (networking)

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