System for 3D visualization and data mining of large vascular trees

Kun Chang Yu, Erik L. Ritman, William E. Higgins

Research output: Contribution to journalConference article

3 Scopus citations

Abstract

Modern micro-CT scanners produce very large 3D digital images of arterial trees. A typical 3D micro-CT image can consist of several hundred megabytes of image data, with a voxel resolution on the order of ten microns. The analysis and subsequent visualization of such images poses a considerable challenge. We describe a computerbased system for analyzing and visualizing such large 3D data sets. The system, dubbed the Tree Analyzer, processes an image in four major stages. In the first two stages, a series of automated 3D image-processing operations are applied to an input 3D digital image to produce a raw arterial tree and several supplemental data structures describing the tree (central-axis structure, surface rendering polygonal data, quantitative description of all tree branches), Next, the human interacts with the system to visualize and correct potential defects in the extracted raw tree. A series of sophisticated 3D editing tools and automated operations are available for this step. Finally, the corrected tree can be visualized and manipulated for data mining, using a large number of graphics-based rendering tools, such as 3D stereo viewing, global and local surface rendering, sliding-thin slabs, multiplanar reformatted views, projection images, and an interactive tree map. Quantitative data can also be perused for the tree. Results are presented for 3D micro-CT images of the heart and liver.

Original languageEnglish (US)
Article number60160B
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume6016
DOIs
StatePublished - Dec 1 2005
EventThree-Dimensional TV, Video, and Display IV - Boston, MA, United States
Duration: Oct 24 2005Oct 26 2005

Keywords

  • 3D visualization
  • Data mining
  • Micro-CT imaging
  • Tree analysis
  • Vascular trees
  • Virtual endoscopy

ASJC Scopus subject areas

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

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