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Proceedings Paper

Elasticity-based three dimensional ultrasound real-time volume rendering
Author(s): Emad M. Boctor; Mohammad Matinfar; Omar Ahmad; Hassan Rivaz; Michael Choti; Russell H. Taylor
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Paper Abstract

Volumetric ultrasound imaging has not gained wide recognition, despite the availability of real-time 3D ultrasound scanners and the anticipated potential of 3D ultrasound imaging in diagnostic and interventional radiology. Their use, however, has been hindered by the lack of real-time visualization methods that are capable of producing high quality 3D rendering of the target/surface of interest. Volume rendering is a known visualization method, which can display clear surfaces out of the acquired volumetric data, and has an increasing number of applications utilizing CT and MRI data. The key element of any volume rendering pipeline is the ability to classify the target/surface of interest by setting an appropriate opacity function. Practical and successful real-time 3D ultrasound volume rendering can be achieved in Obstetrics and Angio applications where setting these opacity functions can be done rapidly, and reliably. Unfortunately, 3D ultrasound volume rendering of soft tissues is a challenging task due to the presence of significant amount of noise and speckle. Recently, several research groups have shown the feasibility of producing 3D elasticity volume from two consecutive 3D ultrasound scans. This report describes a novel volume rendering pipeline utilizing elasticity information. The basic idea is to compute B-mode voxel opacity from the rapidly calculated strain values, which can also be mixed with conventional gradient based opacity function. We have implemented the volume renderer using GPU unit, which gives an update rate of 40 volume/sec.

Paper Details

Date Published: 16 March 2009
PDF: 9 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72612V (16 March 2009); doi: 10.1117/12.815166
Show Author Affiliations
Emad M. Boctor, Johns Hopkins Medical Institutions (United States)
Mohammad Matinfar, Johns Hopkins Medical Institutions (United States)
Omar Ahmad, Johns Hopkins Medical Institutions (United States)
Hassan Rivaz, Johns Hopkins Medical Institutions (United States)
Michael Choti, Johns Hopkins Medical Institutions (United States)
Russell H. Taylor, Johns Hopkins Medical Institutions (United States)


Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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