Vector field analysis for surface registration in computer-assisted ENT-surgery.

BACKGROUND: Manual paired-point registration for navigated ENT-surgery is prone to human errors; automatic surface registration is often caught in local minima.

METHODS: Anatomical features of the human occiput are integrated into an algorithm for surface registration. A vector force field is defined between the patient and operating room datasets; registration is facilitated through gradient-based vector field analysis optimization of an energy function. The method is validated exemplarily on patient surface data provided by a mechanically positioned A-mode ultrasound sensor.

RESULTS: Successful registrations were achieved within the entire parameter space, as well as from positions of local minima that were found by the Gaussian fields algorithm for surface registration. Sub-millimetric registration error was measured in clinically relevant anatomical areas on the anterior skull and within the generally accepted margin of 1.5 mm for the entire head.

CONCLUSION: The satisfactory behavior of this approach potentially suggests a wider clinical integration.