Siemens Medical Solutions Usa, Inc.

Duke University

Stephen J Rosenzweig

Liexiang Fan

Yassin Labyed

Kathryn R Nightingale

Mark L Palmeri

Seungsoo Kim

Paul Reynolds

David P Duncan

Manoj G Menon

Brett C Byram

Veronica Rotemberg

Stirling Dodd

Sterling Dodd

Ned C Rouze

For clutter reduction in ultrasound elasticity imaging, the contribution of clutter to different frequency components (e.g., the transmit fundamental and the propagation generated second harmonic) is different. As a result, a difference in displacements determined at the different frequency bands is used to reduce clutter contribution to displacements used for elasticity imaging.

Adaptive clutter filtering in acoustic radiation force-based ultrasound imaging

Asymmetry is provided for the pushing pulse in acoustic radiation force impulse (ARFI) imaging. MI is based on the negative pressure. By increasing the positive pressure more than the negative pressure, the magnitude of displacement may be increased without exceeding the MI limit. Similarly, negative voltages depole while positive do not, so using an ARFI or pushing pulse with asymmetric positive-to-negative peak pressures or voltages allows for generation of greater magnitude of displacement without harm to the transducer.

Asymmetry for acoustic radiation force impulse

For viscoelastic estimation with ultrasound, shear wave speed is measured for different locations in a region of interest. For each location, the shear wave speed is estimated without frequency band division. A distribution of shear wave speeds in the region of interest is matched a modeled distribution corresponding to a particular value of the viscoelastic property.

Tissue viscoelastic estimation from shear velocity in ultrasound medical imaging

Shear wave propagation is used to estimate the speed of sound in a patient. An ultrasound scanner detects a time of occurrence of a shear wave at each of multiple locations. The difference in time of occurrence, given tissue stiffness or shear velocity, is used to estimate the speed of sound for the specific tissue of the patient.

Sound speed imaging using shear waves

For noise reduction in elasticity imaging, frequency compounding is used. Displacements caused by the acoustic radiation force impulse are measured using signals at different frequencies, either due to transmission of tracking pulses and reception at different frequencies or due to processing received signals at different sub-bands. The displacements are (a) combined to compound and the compounded displacements are used to determine elasticity or (b) are used to determine elasticity and the elasticities from information at the different frequencies are compounded.

Frequency compounding in elasticity imaging

Methods, systems and computer program products for determining a mechanical parameter for a sample having a target region, include determining a prior probability density function that characterizes at least one physical property of the target region; generating a displacement of the sample in the target region to form a shear wave that propagates orthogonal to a direction of the displacement; transmitting tracking pulses in the target region; receiving corresponding echo signals for the tracking pulses in the target region at a plurality of lateral positions; estimating a propagation parameter of the shear wave in response to the echo signals and the prior probability density function using statistical inference; and determining at least one mechanical parameter of the target region based on the estimated propagation parameter.

Methods, systems and computer program products for estimating shear wave speed using statistical inference

A system for identifying a presence of an object in a tissue region of interest includes a controller configured to obtain first and second image data sets from the region of interest. A contrast identification module is configured to identify a contrasting region of altered stiffness in the first image data set corresponding to an object in the tissue region of interest. An image data enhancement module is configured to identify the object in the second image data set based on the contrasting region of altered stiffness in the first image data set.

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Seattle, WA, United States of America

Stephen J Rosenzweig