Three-Dimensional Path Planning for Virtual Bronchoscopy

Abstract

Multidetector computed-tomography (MDCT) scanners provide large high-resolution three-dimensional (3-D) images of the chest. MDCT scanning, when used in tandem with bronchoscopy, provides a state-of-the-art approach for lung-cancer assessment. We have been building and validating a lung-cancer assessment system, which enables virtual-bronchoscopic 3-D MDCT image analysis and follow-on image-guided bronchoscopy. A suitable path planning method is needed, however, for using this system. We describe a rapid, robust method for computing a set of 3-D airway-tree paths from MDCT images. The method first defines the skeleton of a given segmented 3-D chest image and then performs a multistage refinement of the skeleton to arrive at a final tree structure. The tree consists of a series of paths and branch structural data, suitable for quantitative airway analysis and smooth virtual navigation. A comparison of the method to a previously devised path-planning approach, using a set of human MDCT images, illustrates the efficacy of the method. Results are also presented for human lung-cancer assessment and the guidance of bronchoscopy.

3D CT-Video Fusion for Image-Guided Bronchoscopy

“…For airway tree segmentation, we have used methods based on 3D region growing and mathematical morphology [41]. For central-axes extraction, we have drawn upon techniques based on 3D thinning, B-spline analysis, and differential geometry [37,39,42]. For ROI definition, either direct manual slice tracing or more robust semi-automatic live-wire analysis have been used to identify region borders [32,43,44].…”

“…Cross-Sectional Viewer -Small gray-scale MDCT sections, orthogonal to a 3D viewing site of interest, reveal local structure along an airway axis during navigation and interrogation [23,33,[37][38][39].…”

“…Plot Tool -A plot of geometric measurements along an airway (e.g., cross-sectional area, maximum airway diameter) can be displayed [23,[37][38][39][40]. The user can point to a selected site along this plot to see graphical manifestations of the MDCT data at this site.…”

Computational Tasks in Bronchoscope Navigation During Computer-Assisted Transbronchial Biopsy

“…Thefore it precise computation is very important. Classification of algorithms for automatic generation of centerline (navigation path) in bronchial tree can be found in [14], [15].…”

Automated Anatomical Labeling of Bronchial Branches Extracted from CT Datasets Based on Machine Learning and Combination Optimization and Its Application to Bronchoscope Guidance

“…Several research groups have been working on the development of bronchoscopic navigation systems that utilize pre-operative CT images as maps. If we can overlay the anatomical names of branches currently being observed or paths to target locations [1] on real bronchoscope images, it would be helpful for physicians.…”