Estimation and display for vector doppler imaging using plane wave transmissions

A method of producing blood flow velocity vector imagery, comprising:

• emitting unfocused acoustic signals at at least one angle to a transducer into a medium over substantially an entire field of measurement;
• receiving scattered and reflected ultrasonic signals on a transducer array in response to the emission;
• processing the received ultrasonic signals to extract information to construct a blood flow vector velocity signal corresponding to at least one point in the medium, the constructing including:
• wall filtering the extracted information;
• using the wall-filtered information to form compressed format conjugate-lagged products, wherein the conjugate-lagged products F(p,t,l) of a vector of time samples s(t), at pixel image point p, of signal data vector ŝ are computed in compressed amplitude format, for one or more lags l−0, l−1, . . . as
• F(p,t,l)=ŝ(t)ŝ(t−l)*|{circumflex over (s)}(t){circumflex over (s)}(t−l)*|−1/2
• wherein the terms ŝ(t)ŝ(l−1)*
• are summands of the sample autocorrelation at lag l;
• forming a vector velocity measurement model by using space-time gradient operation on the products, and solving said model by a weighted least squares scheme;
• detecting the presence of blood flow at a pixel by qualifying blood flow vector velocity signals through a series of tests on values of quality metrics produced as byproducts of the blood flow vector velocity estimation procedure;
• and
• generating on a display device blood flow vector velocity imagery from the blood flow vector velocity signal.

An ultrasound processing system, comprising:

• a module adapted to generate an acoustic signal, receive at least one echo of the acoustic signal at a plurality of receiving elements in the module and obtain a plurality of echo signals therefrom;
• and
• a processor coupled to the module and configured to:
• extract information from the plurality of echo signals to construct a blood flow vector velocity signal by:
• wall filtering the extracted information;
• using the wall-filtered information to form autocorrelation values and Doppler frequency estimates;
• partitioning of a bistatic range-rate model, f=Av+b+e, where the flow velocity vector at the image point is v=[νx,νz]T, b represents bias due to aliasing, e is stochastic error, and the model matrix A is dimensioned [M×2] and has rows am(θm), where:
• a
• m
• =
• 1
• λ
• 
• [
• sin
• 
• (
• θ
• m
• )
• ,
• 1
• +
• cos
• 
• (
• θ
• m
• )
• ]
• with explicit terms for bias due to aliasing of Doppler frequencies, into linear and nonlinear parts;
• and
• solving the partitioned model by the weighted least squares scheme corresponding to at least one point in the medium;
• and
• detect the presence of blood flow at a display device pixel by qualifying blood flow vector velocity signals through a series of tests on values of quality metrics produced as byproducts of the blood flow vector velocity estimation procedure;
• and
• a display device configured to generate blood flow vector velocity imagery from the blood flow vector velocity signals.

An ultrasound processing system, comprising:

• a module adapted to generate an acoustic signal, receive at least one echo of the acoustic signal at a plurality of receiving elements in the module and obtain a plurality of echo signals therefrom;
• and
• a processor coupled to the module and configured to:
• extract information from the plurality of echo signals to construct a blood flow vector velocity signal corresponding to at least one point in the medium, the constructing including the following steps of:
• wall filtering the extracted information;
• using the wall-filtered information to form compressed format conjugate-lagged products, the conjugate-lagged products F(p,t,l) of the vector of time samples s(t), at pixel image point p, of signal data vector ŝ are computed in compressed amplitude format, for one or more lags l−0, l−1, . . . as
• F(p,t,l)={circumflex over (s)}(t){circumflex over (s)}(t−l)*|{circumflex over (s)}(t){circumflex over (s)}(t−l)*|−1/2
• wherein the terms ŝ(t)ŝ(t−l)*
• are summands of the sample autocorrelation at lag l;
• forming a vector velocity measurement model by using space-time gradient operation on the products, and solving said model by a weighted least squares scheme;
• detect the presence of blood flow at a pixel by qualifying blood flow vector velocity signals through a series of tests on values of quality metrics produced as byproducts of the blood flow vector velocity estimation procedure;
• and
• a display device configured to display blood flow vector velocity imagery from the blood flow vector velocity signals.