Ultrasound waveform tomography with spatial and edge regularization
Synthetic-aperture ultrasound tomography systems and methods using scanning arrays and algorithms configured to simultaneously acquire ultrasound transmission and reflection data, and process the data for improved ultrasound tomography imaging, wherein the tomography imaging comprises total-variation regularization, or a modified total variation regularization, particularly with edge-guided or spatially variant regularization.
1. A synthetic aperture ultrasound tomography imaging method for imaging a tissue medium with one or more ultrasound transducer arrays comprising a plurality of transducers, the method comprising:
exciting a first transducer with plurality of transducers to generate an ultrasound field within the tissue medium;
acquiring a transmission signal and a reflection signal from a second transducer within the one or more ultrasound transducer arrays; and
generating an ultrasound waveform tomography image reconstruction;
wherein generating an ultrasound waveform tomography image reconstruction comprises computing an acoustic wave property of the reflection and transmission signals by performing iterative waveform inversion with regularization, including iteratively updating model parameters to minimize a mean square difference between observed and synthetic waveforms relating to:
the reflection signal;
the transmission signal; or
a combination of the reflection and transmission signals,
the synthetic waveforms being synthesized based on the model parameters;
wherein the generating the ultrasound waveform tomography image reconstruction comprises: applying a regularization function;
applying a plurality of spatially-variant parameters to two or more spatial regions within the ultrasound waveform tomography image reconstruction;
performing spatially-variant regularization as the regularization function to generate sound-speed reconstructions of the acquired reflection signal and the acquired transmission signal;
wherein the spatially-variant regularization comprises a modified total-variation regularization comprising:
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where m is a model parameter, k is a current iteration value, ∥d−ƒ(m)∥ 2 2 comprises a data misfit function, d comprises data relating to the acquired reflection signal and transmission signals, where λ 1 and λ 2 are both positive regularization parameters, and u i is an auxiliary variable.
2. The method of claim 1 , wherein the one or more ultrasound transducer arrays comprises two or more transducer arrays spaced apart from each other, each of the two or more transducer arrays comprising a corresponding plurality of transducers.
3. The method of claim 1 , wherein the applying the spatially-variant parameters comprises: obtaining approximate locations of the two or more spatial regions; and applying the plurality of spatially-variant parameters to each of the located two or more spatial regions.
4. The method of claim 3 , further comprising computing approximate locations of the two or more spatial regions based on ray tomography migration results.
5. The method of claim 1 , wherein the spatially-variant parameters vary based on a size of the two or more spatial regions.
6. The method of claim 1 , wherein the observed waveform is calculated using the reflection and transmission signals.
7. The method of claim 1 , wherein the iterative waveform inversion with regularization to compute the acoustic wave property of the reflection and transmission signals is
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where m is a model parameter, k is a current iteration value, ∥d−ƒ(m)∥ 2 2 comprises a misfit function, d comprises data relating to the acquired reflection signal and transmission signal, λ i is a positive regularization parameter, and R(m i ) is a spatially-variant regularization term.
8. The method of claim 7 , wherein a gradient of the misfit function is obtained using an adjoint state method.
9. A synthetic aperture ultrasound tomography imaging system comprising:
one or more ultrasound transducer arrays, an ultrasound transducer array of the one or more ultrasound transducers comprising a plurality of transducers;
a processor; and
memory storing instructions that, when executed by the processor, cause the processor to:
excite a first transducer of the plurality of transducers to generate an ultrasound field within a tissue medium;
receive a transmission signal and a reflection signal at a second transducer of the plurality of transducers of the one or more ultrasound transducer arrays; and
generate an ultrasound waveform tomography image reconstruction by computing an acoustic wave property of the reflection and transmission signals by performing iterative waveform inversion with regularization, including iteratively updating model parameters to minimize a mean square difference between observed and synthetic waveforms relating to:
the reflection signal;
the transmission signal; or
a combination of the reflection and transmission signals,
the synthetic waveforms being synthesized based on the model parameters;
wherein the instructions that cause the processor to generate the ultrasound waveform tomography image reconstruction comprise instructions that, when executed by the processor, cause the processor to:
apply a regularization function;
apply a plurality of spatially-variant parameters to two or more spatial regions within the ultrasound waveform tomography image reconstruction;
perform spatially-variant regularization as the regularization function to generate sound-speed reconstructions of the received reflection signal and the received transmission signal,
wherein the spatially-variant regularization comprises a modified total-variation regularization comprising:
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k
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=
argmin
m
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-
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where m is a model parameter, k is a current iteration value, ∥d−ƒ(m)∥ 2 2 comprises a data misfit function, d comprises data relating to the acquired reflection signal and transmission signals, where λ 1 and λ 2 are both positive regularization parameters, and u i is an auxiliary variable.
10. The synthetic aperture ultrasound tomography imaging system of claim 9 , wherein the one or more ultrasound transducer arrays comprises two or more transducer arrays spaced apart from each other, each of the two or more transducer arrays comprising a corresponding plurality of transducers.
11. The method of claim 9 , the instructions that configure the processor to apply the spatially-variant parameters comprise instructions that, when executed by the processor, cause the processor to: obtain approximate locations of the two or more spatial regions; and apply the plurality of spatially-variant parameters to each of the located two or more spatial regions.
12. The synthetic aperture ultrasound tomography imaging system of claim 11 , wherein the memory further stores instructions that, when executed by the processor, cause the processor to compute approximate locations of the two or more spatial regions based on ray tomography migration results.
13. The method of claim 9 , wherein the spatially-variant parameters vary based on a size of the two or more spatial regions.
14. The synthetic aperture ultrasound tomography imaging system of claim 9 , wherein the observed waveform is calculated using the reflection and transmission signals.
15. The synthetic aperture ultrasound tomography imaging system of claim 9 , wherein the function of computing iterative waveform inversion with regularization to compute the acoustic wave property of the reflection and transmission signals is
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m
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=
min
m
{
d
-
f
(
m
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2
2
+
λ
i
R
(
m
i
)
}
where m is a model parameter, k is a current iteration value, ∥d−ƒ(m)∥ 2 2 comprises a misfit function, d comprises data relating to the acquired reflection signal and transmission signal, λ i is a positive regularization parameter, and R(m i ) is a spatially-variant regularization term.
16. The synthetic aperture ultrasound tomography imaging system of claim 15 , wherein the processor is configured to obtain a gradient of the misfit function using an adjoint state method.