METHOD AND SYSTEM FOR COMPSENSATING DEPTH-DEPENDENT ATTENUATION IN ULTRASONIC SIGNAL DATA

Abstract

A method for compensating a depth-dependent attenuation in ultrasonic signal data of a medium and a system for performing the method. The method is implemented by a processing system (8), the method comprising the following: processing (c), in which ultrasound signal data is processed by the processing unit for providing in-phase and quadrature phase (IQ) data of the medium, and attenuation compensation (f), in which a phase of the IQ data is compensated as a function of a respective frequency shift amount for each of a plurality of different depths (z.sub.1, z.sub.2, z.sub.n) in the medium, such that the IQ data spectrum is recentered across the plurality of different depths.

Claims

1. A method for compensating a depth-dependent attenuation in ultrasonic signal data of a medium, wherein said method is implemented by a processing system, the method comprising: processing (c), in which ultrasound signal data is processed by the processing system for providing in-phase and quadrature phase (IQ) data of the medium, attenuation compensation (f), in which a phase of the IQ data is compensated as a function of a respective frequency shift amount for each of a plurality of different depths (z.sub.1, z.sub.2, z.sub.n) in the medium, such that the IQ data spectrum is re-centered across the plurality of different depths.

2. The method according to claim 1, wherein the IQ data spectrum is re-centered at a predefined reference frequency.

3. The method of claim 1, further comprising, subsequent to the processing (c) and before the attenuation compensation (f): shift amount determination (d1), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a frequency shift amount is determined based on a predefined shift map.

4. The method according to claim 1, wherein the shift map is derived from a single predefined attenuation coefficient or multiple attenuation coefficients respectively for the plurality of different depths, said attenuation coefficient specifying a decrease of ultrasound amplitude in the ultrasonic signal data as a function of frequency per unit of distance in the depth direction of the medium (dB/cm/MHz).

5. The method according to claim 1, the method comprising, subsequent to the processing (c), and before the attenuation compensation (f): function determination (d2), in which for each of a plurality of different depths (z.sub.1, Z2, Zn) in the medium an auto-correlation function of the IQ data is determined, center estimation (e2), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a central spectral location ω.sub.c(z) is estimated as a function of a phase of the auto-correlation function, wherein in the attenuation compensation (f) for each different depth (z.sub.1, z.sub.2, z.sub.n) the frequency shift amount is determined as a function of the respective central spectral location ω.sub.c(z). 10

6. The method according to claim 1, wherein the attenuation compensation (f) is done in the time domain by multiplication of a complex phase for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) on the input data processed by the attenuation compensation (f) up to a maximum depth (z.sub.max), the complex phase at a depth (z.sub.k) being a function of the total shift amount up to the depth (z.sub.k).

7. The method according to claim 1, the method further comprising, subsequent to the processing (c): bandwidth estimation (d2′), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a respective spectral standard deviation is estimated as a function of an autocorrelation coefficient of the IQ data, and bandwidth determination (e2′), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a frequency bandwidth of a filter is determined as a function of the spectral standard deviation, such that the IQ data is adaptively filtered across the plurality of different depths, and after the attenuation compensation (f), filtering (g), where the filter is applied to the compensated IQ data.

8. The method according to claim 5, wherein the ultrasonic signal data comprises data of a plurality of ultrasound lines of an ultrasound transducer, wherein the center estimation (e2) and/or the bandwidth estimation (d2′) is performed for each of the plurality of ultrasound lines and the output data of said steps (e2, e2′) is smoothed across the ultrasound lines.

9. The method according to claim 5, wherein the output data of the center estimation (e2) and/or the bandwidth estimation (d2′) is regularized by a regularization step in depth direction.

10. The method according to claim 5, wherein the robustness of the output data of the center estimation (e2) and/or the bandwidth estimation (d2′) is enhanced by hypothesis-testing a pure noise model i.e. H.sub.0: |ρ.sub.1|=0, wherein only statistically significant points are included in the output data such that the output data are less biased by noise.

11. The method according to claim 1, wherein a frequency shift map across the depth is generated based on the frequency shift amounts for the different depths (z.sub.1, z.sub.2, z.sub.n) by fitting piecewise attenuation functions for adjacent depths (z.sub.1, z.sub.2) to the map.

12. The method according to claim 1, wherein the in-phase and quadrature phase (IQ) data are scattered and/or backscattered IQ data and/or beamformed IQ data.

13. The method according to claim 1, further comprising beamforming (cf), in which the IQ data is processed by a beamforming process for providing beamformed acquisition data of the medium, wherein the processing (c), the attenuation compensation (f) and any operations between (c) and (f) are performed in the beamforming process.

14. The method of claim 1, wherein said method is implemented by a processing system (8) associated to at least one ultrasound transducer (2), the method comprising, prior to the processing (c): transmission (a), in which at least one pulse is transmitted in a medium by a transducer, and reception (b), in which ultrasound signal data is acquired by a transducer in response to the pulse.

15. The method according to claim 1, further comprising: filtering (g), in which a filter is applied to the compensated IQ data spectrum, the same filter being applied to the plurality of different depths (z.sub.1, z.sub.2, z.sub.n), and/or envelop detection (h), in which an envelop of the filtered compensated IQ data is output.

16. A computer program comprising computer-readable instructions which when executed by a data processing system cause the data processing system to carry out the method according to claim 1.

17. A system for compensating a depth-dependent attenuation in ultrasonic signal data of a medium, comprising a processing system configured to: process ultrasound signal data for providing in-phase and quadrature phase (IQ) data of the medium, compensate a phase of the IQ data as a function of a respective frequency shift amount for each of a plurality of different depths (z.sub.1, z.sub.2, z.sub.n) in the medium, such that the IQ data spectrum is re-centered across the plurality of different depths.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0080] FIG. 1 shows a schematic drawing showing an ultrasound apparatus according to examples of the present disclosure; and

[0081] FIG. 2 shows a block diagram showing part of the apparatus of FIG. 1;

[0082] FIG. 3 shows a flowchart of a method for compensating a depth-dependent attenuation in ultrasonic signal data of a medium according the present disclosure;

[0083] FIG. 4 shows a diagram of an example (using a predefined coefficient/map) of the method according the present disclosure;

[0084] FIG. 5 shows a diagram of another example (using automated shift amount determination) of the method according the present disclosure;

[0085] FIG. 6 shows a diagram of another example (additionally using automated bandwidth correction) of the method according the present disclosure;

[0086] FIG. 7a shows an example of a depth-dependent spectrum of an ultrasound image without attenuation compensation;

[0087] FIG. 7b shows the example of FIG. 7a with attenuation compensation;

[0088] FIG. 8a shows another example of a depth-dependent spectrum of an ultrasound image without attenuation compensation; and

[0089] FIG. 8b shows the example of FIG. 8a with attenuation compensation.

DETAILED DESCRIPTION EXAMPLE

[0090] The technologies described herein include imaging methods and apparatus implementing said methods. Such apparatus may perform medical imaging such as ultrasound imaging. In examples, a method is used for compensating a depth-dependent attenuation in ultrasonic signal data of a medium. The method may be implemented by a processing system which is for example associated to a plurality (e.g. a line or an array) of transducers in relation with said medium.

[0091] Reference will now be made in detail to examples of the disclosure, which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.

[0092] The apparatus shown on FIG. 1 is adapted for imaging of a region 1 of a medium, for instance living tissues and in particular human tissues of a patient or an animal or a plant. The apparatus may correspond to the system of the present disclosure. The apparatus may include for instance: [0093] (optionally) at least one transducer, for example a single transducer configured to transmit a pulse and receive the tissue response. Also, it is possible to use a plurality of transducers and/or a transducer array 2. For example, a linear array may be provided typically including a few tens of transducers (for instance 100 to 300) juxtaposed along an axis X (horizontal or array direction X) as already known in usual probes. In this case the array 2 is adapted to perform a bidimensional (2D) imaging of the region 1, but the array 2 could also be a bidimensional array adapted to perform a 3D imaging of the region 1. The transducer array 2 may also be a convex array including a plurality of transducers aligned along a curved line. The same transducer(s) may be used to transmit a pulse and receive the response, or different transducers are used for transmission and reception; [0094] an electronic bay 3 controlling the transducer array and acquiring signals therefrom; [0095] a microcomputer 4 for controlling the electronic bay 3 and for example viewing images obtained from the electronic bay (in a variant, a single electronic device could fulfil all the functionalities of the electronic bay 3 and of the microcomputer 4). The microcomputer may be for example a PC.

[0096] It is though possible that the transducer is external to the electronic bay 3 and/or the microcomputer 4. For example, the transducer may be remotely connectable to the electronic bay 3 and/or the microcomputer 4. In one example the transducer is an IOT device and/or is connectable to an IOT device and/or to a smartphone. The transducer may be connectable to the electronic bay 3 and/or the microcomputer 4 via the internet, the ‘cloud’, 4G or 5G protocols, WIFI, any local network or any other data contact or remote connection.

[0097] It is further possible that the electronic bay 3 and the microcomputer 4 are remotely connectable, for example via the internet, the ‘cloud’, 4G or 5G protocols, WIFI, any local network or any other data contact or remote connection.

[0098] The apparatus may further comprise a display for showing ultrasound images. Said display may be connected to or be comprised by the microcomputer 4. It is also possible that display is remotely connectable to the electronic bay 3 and/or the microcomputer 4, for example via the internet, the ‘cloud’, 4G or 5G protocols, WIFI, any local network or any other data contact or remote connection.

[0099] The axis Z on FIG. 1 is an axis perpendicular to the axis X, and it is usually the direction of ultrasound beams generated by the transducers of the array, for example in the depth direction of the examined medium. This direction is designated in present document as a vertical or axial direction.

[0100] As shown on FIG. 2, the electronic bay 3 may include for instance: [0101] L analog/digital converters 5 (A/Di-A/DL) individually connected to the L transducers (TI-TL) of the transducer array 2; [0102] L buffer memories 6 (Bi-Bn) respectively associated to the n analog/digital converters 5, [0103] a processing system 8, comprising for example a central processing unit 8a (CPU) and/or a graphical processing unit 8b (GPU) communicating with the buffer memories 6 and the microcomputer 4, [0104] a memory 9 (MEM) linked to the central processing system 8; [0105] a digital signal processor 10 (DSP) linked to the central processing system 8.

[0106] The apparatus herein disclosed is a device for ultrasound imaging, the transducers are ultrasound transducers, and the implemented method estimates an ultrasonic attenuation parameter for region 1 and optionally may produce ultrasound images of region 1.

[0107] However, the apparatus may be any imaging device using other waves than ultrasound waves (waves having a wavelength different than an ultrasound wavelength), the transducers and the electronic bay components being then adapted to said waves.

[0108] FIG. 3 shows a flowchart of a method for compensating a depth-dependent attenuation in ultrasonic signal data of a medium according the present disclosure. Said method may be implemented in the apparatus of FIG. 1.

[0109] The method may be controlled mainly by a processing system 8, for example comprising the central processing unit 8a and/or the GPU 8b, eventually with the contribution of the digital signal processor 10, or any other means. The method includes the following: [0110] an optional transmission (a), in which at least one pulse is transmitted in a medium by a transducer, and [0111] an optional reception (b), in which ultrasound signal data is acquired by a transducer in response to the pulse [0112] processing (c), in which ultrasound signal data is processed by the processing system for providing in-phase and quadrature phase (IQ) data of the medium, [0113] optional shift amount determination (d1), as described in context of FIG. 5, or [0114] optional function determination (d2), and optional center estimation (e2), as described in context of FIG. 6, [0115] optional bandwidth estimation (d2′), and optional bandwidth determination (e2′), as described in context of FIG. 7, [0116] attenuation compensation (f), in which a phase of the IQ data is compensated as a function of a respective frequency shift amount for each of a plurality of different depths (z.sub.1, z.sub.2, z.sub.n) in the medium, such that the IQ data spectrum is re-centered across the plurality of different depths [0117] an optional (e.g. low-pass-9 filtering step (g) in which a (e.g. single) filter is applied to the corrected compensated IQ data spectrum, the same filter being applied to the plurality of different depths (z.sub.1, z.sub.2, z.sub.n), and [0118] optional envelop detection (h), in which an envelope of the filtered compensated IQ data is output.

[0119] The method may further comprise beamforming (c-f), comprising processing (c), attenuation compensation (f) and any operations between (c) and (f), wherein in the optional beamforming, the IQ data is processed by a beamforming process for providing beamformed acquisition data of the medium.

[0120] The method may be carried out repeatedly, for example by a loop from operation (h) back to operation (a). In this way a repeated ultrasound data acquisition and/or ultrasound imaging becomes possible, for example in real-time or quasi real-time.

[0121] FIG. 4 shows a diagram of an example (using a predefined coefficient/map) of the method according to the present disclosure. As shown in FIG. 4, the method may comprise optional shift amount determination (d1), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a frequency shift amount is determined based on a predefined shift map, for example also as a function of the probe type. For example, either by user input or by estimation, the predefined shift map, for example an attenuation coefficient, may be obtained to compute the amount of frequency shift as a function of depth. The frequency shifts are applied on the input IQ data. The correction may be done in the time domain by the multiplication of a complex phase on the input data that corresponds to the shift amount. The corrected data are then low pass filtered to reduce noise, before being sent to envelop detection.

[0122] FIG. 5 shows a diagram of an example (using automated shift amount determination) of the method according the present disclosure. As shown in FIG. 5, the method may comprise optional function determination (d2), in which for each of a plurality of different depths (z.sub.1, z.sub.2, z.sub.n) in the medium an auto-correlation function of the IQ data is determined. Moreover, the method may comprise a subsequent optional center estimation (e2), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a central spectral location ω.sub.c(z) is estimated as a function of a phase of the auto-correlation function. In this example the attenuation compensation operation (f) for each different depth (z.sub.1, z.sub.2, z.sub.n) the frequency shift amount is determined as a function of the respective central spectral location ω.sub.c(z).

[0123] More, the frequency shift may be automatically estimated by an order-1 autocorrelation on the IQ data. The order-1 autocorrelation function R.sub.1(z) and coefficient ρ.sub.1(z) may be computed from the IQ at each depth. The central spectral location ω.sub.c(z) at each depth z is estimated by the phase of R.sub.1:

[00001]$\begin{array}{cc}{\omega }_c\left(z\right)\approx \phi \left(R_1\left(z\right)\right)& \left(1\right)\end{array}$

[0124] The IQ data phase at each depth may be compensated (corrected) by using this estimated location, such that the corrected data spectrum is recentered at zero frequency.

[0125] FIG. 6 shows a diagram of another example (additionally using automated bandwidth correction) of the method according the present disclosure. As shown in FIG. 6, the method may further comprise optional bandwidth estimation (e2′), in which for each of the plurality of different depths (z.sub.1, Z2, Zn) a respective spectral standard deviation is estimated as a function of an autocorrelation coefficient of the IQ data. The method may comprise further a subsequent optional bandwidth determination operation (f2″), in which for each of the plurality of different depths (z.sub.1, z.sub.2, z.sub.n) a frequency bandwidth of a filter is determined as a function of the spectral standard deviation, such that the IQ data is adaptively filtered across the plurality of different depths. After attenuation compensation (f), filtering (g) may be carried out where the filter is applied to the compensated IQ data.

[0126] Hence, it is also possible to adapt the filter bandwidth by estimating it through the same autocorrelation function. The spectral standard deviation may be estimated at each depth z by:

[00002]$\begin{array}{cc}{\sigma }_{\omega }\left(z\right)\approx 2\sqrt{1-.Math.{\rho }_1\left(z\right).Math.}& \left(2\right)\end{array}$

[0127] Both estimates (frequency shift and bandwidth) may be further improved in accuracy by smoothing the estimates from multiple ultrasound lines. Both estimates may also be regularized in depth to have smoother variation as a function of depth, and thus to improve the stability of the filtering. The robustness of both estimators may be improved by hypothesis-testing a pure noise model i.e. H.sub.0: |ρ.sub.1|=0. Only statistically significant points are included in the estimation such that the estimates are less biased by noise.

[0128] FIG. 7a shows an example of a depth-dependent spectrum of an ultrasound image without attenuation compensation. FIG. 7b shows the same example with attenuation compensation, an example of automatic spectrum correction as a function of depth on a phantom with a linear attenuation coefficient.

[0129] In said example the ultrasound signal spectrum is distorted by attenuation when propagating in depth. The method according to the present disclosure allows to automatically estimate the frequency center and the bandwidth at each depth. This allows to recenter the spectrum, and adaptively low-pass filter the ultrasound signal data, to compensate the attenuation distortion. The method is applicable to nonlinear attenuation also. In FIG. 7b it is exemplarily and schematically shown that a single lowpass filter may be used for each depth level in the spectrum. This is possible, because a depth-dependent spectrum shifting for attenuation compensation has already been carried out by the method of the present disclosure.

[0130] FIG. 8a shows another example of a depth-dependent spectrum of an ultrasound image without attenuation compensation, wherein FIG. 8b shows yet another example with attenuation compensation. As shown in the example, the attenuation is not necessarily linear. Said example illustrates an in vivo example and the result of the automatic correction as disclosed. In FIG. 8b it is exemplarily and schematically shown that a plurality of filters of matching bandwidths may be used for a respective plurality of depth levels in the spectrum. In the illustrated example only two filters are shown but there may be used more than two filters, for example 10 or 20. Said filters may be lowpass filters. They may be identical with regard to their center. In other words, the filters may not need to match any spectrum shifting of the ultrasound signal data. This is not necessary, because a depth-dependent spectrum shifting (i.e. re-centering) for attenuation compensation has already been carried out by the method of the present disclosure. The filters may though differ with regard to their bandwidth. In other words, the filters may have varying bandwidths across the depth. Accordingly, it becomes possible to use filters of different matching bandwidths across different depths. Said bandwidths may be calculated for example in steps d2′ and e2′ as described above.

[0131] Throughout the description, including the claims, the term “comprising a” should be understood as being synonymous with “comprising at least one” unless otherwise stated. In addition, any range set forth in the description, including the claims should be understood as including its end value(s) unless otherwise stated. Specific values for described elements should be understood to be within accepted manufacturing or industry tolerances known to one of skill in the art, and any use of the terms “substantially” and/or “approximately” and/or “generally” should be understood to mean falling within such accepted tolerances.

[0132] Although the present disclosure herein has been described with reference to particular examples, it is to be understood that these examples are merely illustrative of the principles and applications of the present disclosure.

[0133] It is intended that the specification and examples be considered as exemplary only, with a true scope of the disclosure being indicated by the following claims.

[0134] In summary the method according the present disclosure as described above allows a more precise attenuation estimation and implies less computational costs, what in particular improves a real time computation mode. Further, due to the increased preciseness a decreased variance and thus an increased reproducibility can be achieved.