Three-dimensional true color topographical analysis of the pulmonary airways

Melissa Suter, Joseph M. Reinhardt, Milan Sonka, William Higgins, Eric A. Hoffman, Geoffrey McLennan

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

The development of pulmonary airway disease is characterized by mucosal color and topographical changes. Traditionally subjective visual interpretation of a bronchoscope procedure defines the identification of pulmonary airway disease however we have developed an optical imaging system used in conjunction with CT images to potentially quantify and classify these subtle variations. This paper presents a method for the construction of true color 3D images of the pulmonary airways from both optical and CT image data. Shape from Shading methods in the past decade have continually strived to achieve this goal by extracting 3D information from captured 2D images however these attempts have been severely limited in their application to bronchoscope images. Conversely the utilization of CT scans provides a sound tool for determining the gross structural anatomy of the airways however the accuracy of the rendered topographical surface maps is limited due to the resolution of the CT image data. Through integration of both the optical and CT imaging modalities we hope to create high resolution true color 3D images providing the necessary color and texture information to aid in future detection and classification of possible pulmonary airway disease. Preliminary combined color and texture results associated with various pulmonary airway diseases are presented highlighting the usefulness of this analysis technique.

Original languageEnglish (US)
Pages (from-to)189-198
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5369
DOIs
StatePublished - 2004
EventMedical Imaging 2004: Physiology, Function, and Structure from Medical Images - San Diego, CA, United States
Duration: Feb 15 2004Feb 17 2004

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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