Full angle spatial compounding for improved replenishment analyses in contrast perfusion imaging: In vitro studies

For contrast enhanced perfusion imaging semi-quantitative methods (such as the bolus-, replenishment- or depletion-method) are commonly used to analyze the dynamic changes in concentration of contrast agent induced by insonification. In order to apply these methods and to decrease artifacts from tis...

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Vydáno v:IEEE transactions on ultrasonics, ferroelectrics, and frequency control Ročník 55; číslo 4; s. 819 - 831
Hlavní autoři: Hansen, C., Huttebrauker, N., Brunke, S., Ermert, H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.04.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0885-3010, 1525-8955
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Shrnutí:For contrast enhanced perfusion imaging semi-quantitative methods (such as the bolus-, replenishment- or depletion-method) are commonly used to analyze the dynamic changes in concentration of contrast agent induced by insonification. In order to apply these methods and to decrease artifacts from tissue nonlinearity, perfusion imaging is conducted using decreased transmit power. However, echo signals from deeper structures are often too weak to be successfully analyzed. Furthermore, shadowing artifacts may occur as a result of high concentration of contrast agent in the beam path. Thus, those semi-quantitative methods often fail or yield ambiguous diagnoses. Imaging an object (e.g., the female breast) from multiple viewing angles (spatial compounding) may overcome these issues. In addition, spatial compounding achieves an isotropic resolution and reduces speckle and further common artifacts. In this paper we present results obtained from a combination of spatial compounding with contrast-enhanced perfusion imaging. Applying the replenishment method, we extracted perfusion-related parameters and compared the conventional parametric images with the compound parametric images. We found that the compounded parametric images outperform the conventional images due to reduced noise and suppression of artifacts.
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ISSN:0885-3010
1525-8955
DOI:10.1109/TUFFC.2008.716