Ultrasound imaging is used within numerous medical disciplines. Extensive and repeated training is needed
for efficient use of the technology. Simulator training has been proposed as a complement to other training
methods. Advantages of simulator training include access to a large number of normal and rare cases without
the need for suitable volunteers and available ultrasound equipment. The imaging of soft tissue can be simulated
by considering the interaction between the tissue and the ultrasound field. The objective of this study is to
include these effects in real-time simulators. One previous approach has been to simulate a three-dimensional (3D) ultrasound volume off line, and then cross-section the volume in real time. This approach, however, does
not take into account the anisotropic resolution of ultrasound imaging. If we assume that the average acoustical
properties of tissues are slowly varying and that the speckle pattern is independent of the tissue, we show that
ultrasound images can be simulated by multiplying a pre-simulated speckle image by an any-plane cross section
of a 3D representation of an anatomy. Thus anisotropic resolution can be simulated in real time. The simulated
images were compared to true ultrasound images of soft tissue. Since the speckle was simulated independently of the tissue, the most realistic results were obtained for still images, but the method was also satisfactory for moving images when speckle tracking between views was not important. The method is well applicable to ultrasound training simulators on low cost platforms.
KEYWORDS: Ultrasonography, 3D modeling, Data modeling, Image segmentation, Visualization, Computed tomography, 3D visualizations, Tissues, Process modeling, Navigation systems
The criterion for recommending treatment of an abdominal aortic aneurysm is that the diameter exceeds 50-55 mm or
shows a rapid increase. Our hypothesis is that a more accurate prediction of aneurysm rupture is obtained by estimating
arterial wall strain from patient specific measurements. Measuring strain in specific parts of the aneurysm reveals
differences in load or tissue properties. We have previously presented a method for in vivo estimation of circumferential
strain by ultrasound. In the present work, a position sensor attached to the ultrasound probe was used for combining
several 2D ultrasound sectors into a 3D model. The ultrasound was registered to a computed-tomography scan (CT), and
the strain values were mapped onto a model segmented from these CT data. This gave an intuitive coupling between
anatomy and strain, which may benefit both data acquisition and the interpretation of strain. In addition to potentially
provide information relevant for assessing the rupture risk of the aneurysm in itself, this model could be used for
validating simulations of fluid-structure interactions. Further, the measurements could be integrated with the simulations
in order to increase the amount of patient specific information, thus producing a more reliable and accurate model of the
biomechanics of the individual aneurysm. This approach makes it possible to extract several parameters potentially
relevant for predicting rupture risk, and may therefore extend the basis for clinical decision making.
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