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

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

Research output: Contribution to journalConference article

3 Citations (Scopus)

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

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data mining
3D Visualization
Data mining
Data Mining
Visualization
Micro-CT
Liver
Data structures
Image processing
3D Image
Rendering
Defects
CT Image
Digital Image
editing
Series
data structures
Voxel
Scanner
liver

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

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title = "System for 3D visualization and data mining of large vascular trees",
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.",
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System for 3D visualization and data mining of large vascular trees. / Yu, Kun Chang; Ritman, Erik L.; Higgins, William Evan.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 6016, 60160B, 01.12.2005.

Research output: Contribution to journalConference article

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