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Volumetric elasticity imaging with a 2-D CMUT array.


ABSTRACT: This article reports the use of a two-dimensional (2-D) capacitive micro-machined ultrasound transducer (CMUT) to acquire radio-frequency (RF) echo data from relatively large volumes of a simple ultrasound phantom to compare three-dimensional (3-D) elasticity imaging methods. Typical 2-D motion tracking for elasticity image formation was compared with three different methods of 3-D motion tracking, with sum-squared difference (SSD) used as the similarity measure. Differences among the algorithms were the degree to which they tracked elevational motion: not at all (2-D search), planar search, combination of multiple planes and plane independent guided search. The cross-correlation between the predeformation and motion-compensated postdeformation RF echo fields was used to quantify motion tracking accuracy. The lesion contrast-to-noise ratio was used to quantify image quality. Tracking accuracy and strain image quality generally improved with increased tracking sophistication. When used as input for a 3-D modulus reconstruction, high quality 3-D displacement estimates yielded accurate and low noise modulus reconstruction.

SUBMITTER: Fisher TG 

PROVIDER: S-EPMC3089374 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Volumetric elasticity imaging with a 2-D CMUT array.

Fisher Ted G TG   Hall Timothy J TJ   Panda Satchi S   Richards Michael S MS   Barbone Paul E PE   Jiang Jingfeng J   Resnick Jeff J   Barnes Steve S  

Ultrasound in medicine & biology 20100601 6


This article reports the use of a two-dimensional (2-D) capacitive micro-machined ultrasound transducer (CMUT) to acquire radio-frequency (RF) echo data from relatively large volumes of a simple ultrasound phantom to compare three-dimensional (3-D) elasticity imaging methods. Typical 2-D motion tracking for elasticity image formation was compared with three different methods of 3-D motion tracking, with sum-squared difference (SSD) used as the similarity measure. Differences among the algorithms  ...[more]

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