Automatic axis generation for 3D virtual-bronchoscopic image assessment

R. D. Swift, W. E. Higgins, E. A. Hoffman, G. McLennan, J. M. Reinhardt

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

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 × 512 × 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.

Original languageEnglish (US)
Pages (from-to)73-84
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3337
DOIs
StatePublished - Dec 1 1998
EventMedical Imaging 1998: Physiology and Function from Multidimensional Images - San Diego, CA, United States
Duration: Feb 22 1998Feb 23 1998

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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