Hand–eye calibration using a target registration error model

Abstract

Surgical cameras are prevalent in modern operating theatres and are often used as a surrogate for direct vision. Visualisation techniques (e.g. image fusion) made possible by tracking the camera require accurate hand–eye calibration between the camera and the tracking system. The authors introduce the concept of ‘guided hand–eye calibration’, where calibration measurements are facilitated by a target registration error (TRE) model. They formulate hand–eye calibration as a registration problem between homologous point–line pairs. For each measurement, the position of a monochromatic ball-tip stylus (a point) and its projection onto the image (a line) is recorded, and the TRE of the resulting calibration is predicted using a TRE model. The TRE model is then used to guide the placement of the calibration tool, so that the subsequent measurement minimises the predicted TRE. Assessing TRE after each measurement produces accurate calibration using a minimal number of measurements. As a proof of principle, they evaluated guided calibration using a webcam and an endoscopic camera. Their endoscopic camera results suggest that millimetre TRE is achievable when at least 15 measurements are acquired with the tracker sensor ∼80 cm away on the laparoscope handle for a target ∼20 cm away from the camera.

Keywords

• image registration
• medical image processing
• calibration
• endoscopes
• image fusion
• surgery
• image sensors
• target registration error model
• surgical cameras
• modern operating theatres
• visualisation techniques
• image fusion
• camera tracking
• guided hand-eye calibration
• calibration measurements
• homologous point-line pairs
• monochromatic ball-tip stylus
• TRE model
• evaluated guided calibration
• webcam
• endoscopic camera
• tracker sensor
• laparoscope