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Proceedings Paper

Multi-dimensional transfer functions for effective visualization of streaming ultrasound and elasticity images
Author(s): David Mann; Jesus J. Caban; Philipp J. Stolka; Emad M. Boctor; Terry S. Yoo
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Paper Abstract

The low-cost and minimum health risks associated with ultrasound (US) have made ultrasonic imaging a widely accepted method to perform diagnostic and image-guided procedures. Despite the existence of 3D ultrasound probes, most analysis and diagnostic procedures are done by studying the B-mode images. Currently, multiple ultrasound probes include 6-DOF sensors that can provide positioning information. Such tracking information can be used to reconstruct a 3D volume from a set of 2D US images. Recent advances in ultrasound imaging have also shown that, directly from the streaming radio frequency (RF) data, it is possible to obtain additional information of the anatomical region under consideration including the elasticity properties. This paper presents a generic framework that takes advantage of current graphics hardware to create a low-latency system to visualize streaming US data while combining multiple tissue attributes into a single illustration. In particular, we introduce a framework that enables real-time reconstruction and interactive visualization of streaming data while enhancing the illustration with elasticity information. The visualization module uses two-dimensional transfer functions (2D TFs) to more effectively fuse and map B-mode and strain values into specific opacity and color values. On commodity hardware, our framework can simultaneously reconstruct, render, and provide user interaction at over 15 fps. Results with phantom and real-world medical datasets show the advantages and effectiveness of our technique with ultrasound data. In particular, our results show how two-dimensional transfer functions can be used to more effectively identify, analyze and visualize lesions in ultrasound images.

Paper Details

Date Published: 2 March 2011
PDF: 10 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 796439 (2 March 2011); doi: 10.1117/12.878935
Show Author Affiliations
David Mann, National Institutes of Health (United States)
Jesus J. Caban, National Institutes of Health (United States)
Philipp J. Stolka, Johns Hopkins Univ. (United States)
Emad M. Boctor, Johns Hopkins Univ. (United States)
Terry S. Yoo, National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes, Editor(s)

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