Hybrid Bronchoscope Tracking Using a Magnetic Tracking Sensor and Image Registration

Abstract

In this paper, we propose a hybrid method for tracking a bronchoscope that uses a combination of magnetic sensor tracking and image registration. The position of a magnetic sensor placed in the working channel of the bronchoscope is provided by a magnetic tracking system. Because of respiratory motion, the magnetic sensor provides only the approximate position and orientation of the bronchoscope in the coordinate system of a CT image acquired before the examination. The sensor position and orientation is used as the starting point for an intensity-based registration between real bronchoscopic video images and virtual bronchoscopic images generated from the CT image. The output transformation of the image registration process is the position and orientation of the bronchoscope in the CT image. We tested the proposed method using a bronchial phantom model. Virtual breathing motion was generated to simulate respiratory motion. The proposed hybrid method successfully tracked the bronchoscope at a rate of approximately 1 Hz.

Deformable Registration of Bronchoscopic Video Sequences to CT Volumes with Guaranteed Smooth Output

“…between 12.8 and 14.9 minutes for the 781 to 911 frames of our video sequences. For other methods a run time between 0.75 and 2.5 seconds [2,3,5,4] per frame is reported, so our computation speed is equivalent to previous approaches.…”

“…We compare the proposed method to our own implementations of four previously published approaches, which have already been applied to similar trajectories: bronchoscope tracking by EMT only [1], intensity-based registration (IBR) with direct initialization from EMT [2], IBR with dynamic initialization from EMT [3], and IBR with a Sequential Monte Carlo sampler based on EMT [4]. Quantitative results for the accuracy are given in Table 1.…”

“…Since bronchoscopy is an inherently monitor-based procedure, augmentation of video images with guidance or targeting information is straightforward and promises high clinical acceptance due to smooth integration into the clinical workflow. The combination of flexible bronchoscopy with electromagnetic tracking (EMT) was first reported by Solomon et al [1], and hybrid image-based and EM tracking was proposed by Mori et al [2], and was improved by Luo et al [3,4] and Soper et al [5]. Hybrid tracking complements the advantages of image-based tracking and EMT, since imagebased tracking is inaccurate for frames with little to no information due to low contrast.…”

Navigation in Endoscopic Soft Tissue Surgery: Perspectives and Limitations

“…Since the bronchoscope always remains inside the tracheobronchial tree, its position can be approximated in a straight forward, non predictive manner, as proposed by Wegner et al [120]. Mori et al [79] extended their navigation system by including a predictive Kalman filter [80]. In Deligianni et al [19], a more sophisticated approach involves shape knowledge of the bronchial tree.…”

3D CT-Video Fusion for Image-Guided Bronchoscopy

“…These proposals, summarized below, show promise, but can be improved upon: (1) McAdams et al and Hopper et al applied 3D CT-based analysis (virtual bronchoscopy) to lymph-node biopsy, but these efforts involved no live guidance [3,4]; (2) Bricault et al did rudimentary registration of 3D CT chest data to videobronchoscopy, but their results were limited [17]; (3) other researchers have proposed a fundamentally different approach whereby an extra electromagnetic sensor is attached to the bronchoscope tip | this approach also requires considerable extra hardware [5,18,19]; (4) Mori et al registered videobronchoscopy images directly to rendered 3D CT images and also proposed including an electromagnetic sensor, but their efforts do not work interactively [20,21].…”