Real-time CT-video registration for continuous endoscopic guidance

Abstract

Previous research has shown that CT-image-based guidance could be useful for the bronchoscopic assessment of lung cancer. This research drew upon the registration of bronchoscopic video images to CT-based endoluminal renderings of the airway tree. The proposed methods either were restricted to discrete single-frame registration, which took several seconds to complete, or required non-real-time buffering and processing of video sequences. We have devised a fast 2D/3D image registration method that performs single-frame CT-Video registration in under 1/15th of a second. This allows the method to be used for real-time registration at full video frame rates without significantly altering the physician's behavior. The method achieves its speed through a gradient-based optimization method that allows most of the computation to be performed off-line. During live registration, the optimization iteratively steps toward the locally optimal viewpoint at which a CT-based endoluminal view is most similar to a current bronchoscopic video frame. After an initial registration to begin the process (generally done in the trachea for bronchoscopy), subsequent registrations are performed in real-time on each incoming video frame. As each new bronchoscopic video frame becomes available, the current optimization is initialized using the previous frame's optimization result, allowing continuous guidance to proceed without manual re-initialization. Tests were performed using both synthetic and pre-recorded bronchoscopic video. The results show that the method is robust to initialization errors, that registration accuracy is high, and that continuous registration can proceed on real-time video at >15 frames per sec. with minimal user-intervention.

Development and comparison of new hybrid motion tracking for bronchoscopic navigation

“…In the operating room, we may integrate this graphical user interface into the bronchoscopic navigation system. However, since manual initialization is timeconsuming for a bronchoscopist, we also plan to accomplish initialization by adding an automatic camera position estimation algorithm (Shinohara et al, 2006;Merritt et al, 2006).…”

3D CT-Video Fusion for Image-Guided Bronchoscopy

“…But more definitive 3D MDCT-based path planning would offer a more exhaustive and straightforward means for preplanning appropriate endobronchial routes for maneuvering the bronchoscope through the complex airway tree and would specify the final biopsy site (often invisible in current practice) definitively [66]. Finally, recent developments in real-time continuous CTvideo registration during bronchoscopy could potentially further improve image-based guidance [67,68].…”

3D MDCT-based system for planning peripheral bronchoscopic procedures

“…Unfortunately, small child airways branching off of the route may be missed. Even though such airways do not need to be traversed during later bronchoscopy, their definition is important for later report generation and image-based guidance of bronchoscopy [25,26,35,43]. Failing to include all airways branching off of a route leading to an ROI could be misleading and disorienting and ultimately result in unsuccessful bronchoscopy.…”