In image-guided neurosurgery, a registration between the patient and their pre-operative images and the tracking of surgical tools enables GPS-like guidance to the surgeon. However, factors such as brainshift, image distortion, and registration error cause the patient-to-image alignment accuracy to degrade throughout the surgical procedure no longer providing accurate guidance. The authors present a gesture-based method for manual registration correction to extend the usage of augmented reality (AR) neuronavigation systems. The authors' method, which makes use of the touchscreen capabilities of a tablet on which the AR navigation view is presented, enables surgeons to compensate for the effects of brainshift, misregistration, or tracking errors. They tested their system in a laboratory user study with ten subjects and found that they were able to achieve a median registration RMS error of 3.51 mm on landmarks around the craniotomy of interest. This is comparable to the level of accuracy attainable with previously proposed methods and currently available commercial systems while being simpler and quicker to use. The method could enable surgeons to quickly and easily compensate for most of the observed shift. Further advantages of their method include its ease of use, its small impact on the surgical workflow and its small-time requirement.
Keywords: GPS-like guidance; augmented reality; augmented reality neuronavigation systems; biomedical MRI; brain; brainshift; computerised tomography; gesture-based method; gesture-based registration correction; image distortion; image registration; manual registration correction; median registration RMS error; medical image processing; mobile augmented reality image-guided neurosurgery system; mobile computing; neurophysiology; object tracking; patient-to-image alignment accuracy; preoperative images; size 3.51 mm; surgeon; surgery; surgical procedure; surgical tools; surgical workflow; tablet touchscreen capability; tracking errors.