New techniques for efficient sliding thin-slab volume visualization

Janice Z. Turlington, William E. Higgins

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

High-resolution three-dimensional (3-D) volumetric images obtained by today's radiologic imaging scanners are rich in detailed diagnostic information. Despite the many visualization techniques available to assess such images, there remains information that is challenging to uncover, such as the location of small structures (e.g., mediastinal lymph nodes, narrowed-airway regions). Recently, sliding thin-slab (STS) visualization was proposed to improve the visualization of interior structures. These STS techniques sometimes depend on user opacity specifications or extra preprocessing, and other rendering approaches that use the general STS mechanism are conceivable. We introduce two techniques for STS volume visualization. The first, a depth (perspective) rendering process, produces an unobstructed, high-contrast 3-D view of the information within a thin volume of image data. Results are a function of relative planar locations. Thus, rendered views accurately depict the internal properties that were initially captured as position and intensity. The second method produces a gradient-like view of the intensity changes in a thin volume. Results can effectively detect the occurrence and location of dramatic tissue variations, often not visually recognized otherwise. Both STS techniques exploit the concept of temporal coherence to form sequences of consecutive slabs, using information from previously computed slabs. This permits efficient real-time computation on a general-purpose computer. Further, these techniques require no preprocessing, and results are not dependent on user knowledge. Results using 3-D computed tomography chest images show the computational efficiency and visual efficacy of the new STS techniques.

Original languageEnglish (US)
Pages (from-to)823-835
Number of pages13
JournalIEEE transactions on medical imaging
Volume20
Issue number8
DOIs
StatePublished - Aug 2001

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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