JPH0216140B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention obtains the power spectrum moment of any order of reflected wave data with fewer calculations than the conventional method, and displays a number of images to visualize biological characteristics in real time. The present invention relates to an ultrasonic diagnostic device that can display images.

Conventional so-called B-mode images mainly have the disadvantage of being able to display only the boundary surfaces of tissues, so a method of displaying the power spectrum moment of the reflected signal from each part has been considered in order to obtain the characteristics of the tissue itself. However, in this method, the power spectrum is first determined using FFT (Fast Fourier Transform), etc., and then the power spectrum moment is calculated, which requires a huge amount of calculation and is difficult to implement in real time. If this happens, the cost will also be high.

The purpose of the present invention is to obtain a power spectrum moment of an arbitrary order of reflected wave data with fewer calculations than the conventional method, and display a number of images, thereby making it possible to display biological characteristics in real time. To provide ultrasound diagnostic equipment.

FIG. 1 shows the entire configuration of an apparatus according to an embodiment of the present invention. In the figure, 1 is a transducer, 2 is a transmitting/receiving circuit, 3 is a power spectrum moment detection circuit, 4 is a timing control circuit for transmitting/receiving, etc., and 5 is a transmitting/receiving circuit.
1 is a circuit for calculating biological tissue characteristic values based on the obtained moment, 6 is a frame memory, 7 is a changeover switch, and 8 is an image display.

Assume that the power spectrum |X _T (f)| ² of a signal xT(t) is obtained by multiplying the reflected wave x(t) from a living body by a window of time width T shown in FIG. The moment of this power spectrum, ie, the power spectrum moment Mi, is defined by the following equation.

Mi＝ ^{∫ ∞} _-∞ |f ⁱ |_・| x(t)+jX^
It can be redefined by (t). However, X^(t) is x
This is the Hilbert transform of (t). That is, if we calculate the power spectrum |Z _T (f) | ² of the signal Z _T (t) by multiplying Z(t) by the window described above, then Mi=∫ ^∞ _-∞ f ⁱ |Z _T (f) | ² df...(2) becomes. Here, the autocorrelation function ² of Z _T (t) is defined as Rz _T
(τ), then RZT(τ)=∫ ^∞ _-∞ |Z _T (f)| ² e ^j2 〓 ^f 〓df ∴∫ ^∞ _-∞ f ⁱ |Z _T (f)| ² df = 1/(j2π )i [diRZT(τ)/dti] ₌₀ ………
(3) Here, the orthogonal detection output Hc (t), Hs (t) in Figure 3
A complex signal a(t) with real and imaginary parts, respectively, is
Signal a _T obtained by adding the above-mentioned window to Hc (t) + jHs (t)
If the autocorrelation function of (t) is Ra _T (τ), the following relationship holds true.

[dnRZT (τ) / dτn] ₌₀ = _o 〓 〓 ⁱ⁼¹ nCi (j2πν) ⁿⁱ [diRaT (τ) / dτi] ₌₀ ………
(4) From equations (3) and (4), Mn=∫ ^∞ _-∞ f ⁿ |Z _T (f) | ² df= _o 〓 ⁱ⁼¹ nCi(j2π)ν ^-in-i
………(5) (i) Ra _T (0) where _(i) RaT (0) = [diRaT(τ)/dτi] ₌₀ Therefore, as shown in FIGS. 3 and 4, the reflected signal x(t) is subjected to orthogonal detection using a positive arc wave of frequency ν, differentiated as many times as necessary, and the obtained Hc,
By multiplying, adding, and averaging Hs, H〓c, H〓s, ... by the combination determined by the above formula, R ₁
~R ₄ is determined, and the power spectrum moment Mi is obtained from equation (5).

A moving average filter is used to calculate R ₁ to _{R 4} , but this is equivalent to moving the window in Figure 2, so the power spectrum moment of the reflected wave from each part can be calculated using the above method. It was possible to calculate in real time. By writing the obtained power spectrum moment Mi or the biological characteristic value calculated from Mi to the frame memory, the power spectrum moment of the reflected wave from each part or the true characteristic value of each part is finally obtained in real time. The image can be displayed. Also, R ₀
When calculating ~R ₄ , it is possible to use either an analog arithmetic circuit or a digital arithmetic circuit for all parts, or it is also possible to realize a circuit in which both are mixed. Further, in the explanation, only the calculation of power spectrum moments of fourth order or lower is shown, but calculation of power spectrum moments of fifth order or higher can be derived in the same manner.

Next, the power spectrum moment Mi is divided by the zero-order power spectrum moment Mo to define the normal power spectrum moment mi.

mi=Mi/Mo Normal power spectrum moment like this
Write mi to frame memory in real time and display the image. As a result, the moment of the power spectrum distribution can be displayed as an image regardless of the reflection level of the reflected wave, so a stable image with little variation can be expected.

In particular, the first normal power spectral moment
m ₁ is equal to the average frequency. Since the attenuation coefficient of a living body is proportional to the frequency, if the incident power spectrum has a Gaussian distribution, the attenuation coefficient is proportional to the slope of the attenuation coefficient. Therefore, by displaying the normal power spectrum mi as an image, the attenuation rate distribution of the living body can be observed, which is of great help in diagnosis.

Further, in an application example of color composition, since normalization is performed by power, a high-quality image can be obtained in which only the color tone changes and the brightness itself remains constant regardless of the power.

FIG. 5 shows an embodiment of the present invention, in which each color is assigned to different power spectrum moments or normal power spectrum moments, and color synthesis is attempted. This method allows more information to be put on one screen. In the figure, 1 to 4 are the same as in FIG. 1, 6-1 to 6-3 are frame memories corresponding to different colors, such as red (R), green (G), and blue (B), and 8' is It is an RGB color display.

FIG. 6 shows yet another embodiment.
In the figure, 1 to 4, 6-1 to 6-3, and 8' are the same as those in FIG. 5, and 9 is a circuit for calculating components for each band from the power spectrum moment. Calculate the three band components W ₁ , W ₂ , W ₃ of the power spectrum from the power spectrum moment or normal power spectrum moment, and calculate W 1 , W 2 , _{W 3} from the power spectrum moment or normal power spectrum moment.
It attempts to assign colors to each of W ₂ and W ₃ and synthesize the colors. By using this method, it is possible to create a color image in which the attenuation increases with depth, for example, from a cool color to a warm color, and the information is conveyed more intuitively to people.

In addition to the above application example, as shown in Figure 7, the conventional B
Compose and display mode images. As a result, diagnosis is progressing while also considering conventional diagnostic methods.
In the figure, 1 to 4, 6-1 to 6-3, and 8' are the same as in FIG. 5, 10 is a well-known circuit for obtaining a B-mode image, and 11 is an addition circuit.

According to the present invention, power spectrum moments can be directly calculated with minimal calculations without the need for extensive calculations such as FFT (Fast Fourier Transform), so power spectrum moments indicating biological characteristics can be calculated with a small number of circuits. It becomes possible to display images in real time.

[Brief explanation of drawings]

FIG. 1 is a basic configuration diagram of an embodiment of the present invention. FIG. 2 is an explanatory diagram of the definition of a power spectrum moment, and FIGS. 3 and 4 show the configuration of a power spectrum moment detector. FIG. 5, FIG. 6, and FIG. 7 are block diagrams of other embodiments of the present invention.

Claims (1)

[Claims] 1. A means for orthogonally detecting an ultrasonic reflected signal from a living body, and a means for orthogonally detecting each of the real component and imaginary component of the orthogonally detected reflected signal n times (n=1, 2,...) Using means for differentiating, the real component and imaginary component of the orthogonally detected reflected signal, and the n times of differential values of the calculated real component and imaginary component, the complex autocorrelation function of the ultrasonic reflected signal is calculated at the origin. A means for calculating a differential coefficient of an arbitrary order, and a means for calculating a power spectrum moment of an ultrasonic reflected signal using the calculated differential coefficient of an arbitrary order, the calculated power spectrum moment of an arbitrary order or the power An ultrasonic diagnostic apparatus characterized by displaying biological tissue characteristic values of the living body calculated from spectral moments. 2 In claim 1, the normal power spectrum moment calculated by dividing the power spectrum moment of each order by the zero-order power spectrum moment, or the biological tissue characteristic value calculated from it, is calculated in real time. te2
An ultrasonic diagnostic device characterized by displaying dimensional images. 3. Ultrasonic diagnosis according to claim 1 or 2, characterized in that a color is assigned to the power spectrum moment of each order or a normal power spectrum moment of each order, and brightness is assigned to the value for synthetic display. Device. 4 In claim 1 or 2, the power or normalized power of each band is calculated from the determined power spectrum moment or normal power spectrum moment, and a corresponding color is assigned to each band. An ultrasonic diagnostic device characterized by synthetic display. 5. An ultrasonic diagnostic apparatus according to any one of claims 1 to 4, characterized in that an obtained image and a conventional B-mode image are displayed in a composite manner.