3 July 1998 Automatic axis generation for 3D virtual-bronchoscopic image assessment
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Abstract
Virtual bronchoscopy is emerging as a means for assessing high-resolution 3D CT images of the chest. The central axes, or paths, of the airways can provide virtual-bronchoscopic systems with a logical reference frame for quantitation and navigation. Unfortunately, the manual and automatic methods proposed to date for determining these axes are either time- consuming, error prone, or provide imprecise results. We give a preliminary presentation of an adaptive automated approach for finding smooth central axes through the major airways. Using this method, we are able to extract multiple axes through a 3D image in only a few minutes for a typical 512 by 512 by 25 CT image. The method works on anisotropically sampled gray-scale images and requires no prior segmentation. We describe the method and present initial validation results for phantom, animal, and human images. Visual results are also provided using a virtual bronchoscopic system.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roderick David Swift, William E. Higgins, Eric A. Hoffman, Geoffrey McLennan, Joseph M. Reinhardt, "Automatic axis generation for 3D virtual-bronchoscopic image assessment", Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); doi: 10.1117/12.312590; https://doi.org/10.1117/12.312590
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