Toward image-based global registration for bronchoscopy guidance

Virtual image-based bronchoscopy guidance systems have been found to be useful for carrying out accurate and skillindependent bronchoscopies. A crucial step to the success of these systems during a live procedure is the local registration of the current real bronchoscope position to the virtual bronchoscope of the guidance system. The synchronization between the live and the virtual bronchoscope is generally lost during adverse events such as patient coughing with guidance often adversely disrupted. Manual intervention by an assisting technician often helps in recovering from such a disruption, but this results in extra procedure time and some potential uncertainty in the locally registered position. To rectify this difficulty, we present for the first time a global registration algorithm that identifies the bronchoscope position without the need for significant bronchoscope maneuvers or technician intervention. The method involves a fast local registration search over all the branches in a global airway-bifurcation search space, with the weighted normalized sum of squares distance metric used for finding the best match. We have achieved a global registration accuracy near 90% in tests over a set of three different virtual bronchoscopic cases and with live guidance in an airway phantom. The method shows considerable potential for enabling global technician-independent guidance of bronchoscopy, without the need for any external device such as an electromagnetic sensor.