KR102670008B1 - method and apparatus for diagnosing fatty liver quantification by ultrasonic scanning frequency in an ultrasound image - Google Patents

Abstract

A method of using a device for diagnosing fatty liver lightening according to an ultrasound frequency according to an embodiment of the present invention includes the steps of preparing a plurality of virtual fatty liver phantoms with a fat deposition rate in the range of 3 to 30%; Collecting fat percentage ultrasound image data reflecting signal attenuation for each ultrasound probe frequency by gradually varying the ultrasound frequency of the plurality of virtual fatty liver phantoms; Measuring signal intensity according to ultrasound travel distance (depth) from the fat percentage ultrasound image data for each ultrasound transducer frequency; The slope of the signal intensity is calculated through linear regression analysis of the measured signal intensity according to the ultrasonic travel distance (depth), and among the calculated results, the coefficient of determination of the linear regression function used in the linear regression analysis ( ) It includes determining a value of 80% or more using ultrasound quantification data.

Description

Apparatus and method for diagnosing fatty liver quantification by ultrasonic scanning frequency in an ultrasound image {method and apparatus for diagnosing fatty liver quantification by ultrasonic scanning frequency in an ultrasound image}

The present invention is a technology that measures and quantifies the attenuation of ultrasound reflected waves according to the liver depth at each scanning frequency in order to quantify fatty liver in ultrasound imaging diagnostic tests. The present invention determines the degree of absorption in human organs according to the scanning frequency of ultrasound and magnetic resonance This relates to a device and method of use for diagnosing the quantification of fatty liver by ultrasound scanning frequency in ultrasound images, which quantifies the degree of intrahepatic fat deposition by ultrasound frequency through correlation studies with images (spectroscopy).

The disease process of the liver begins with fatty liver and progresses to steatohepatitis, liver fibrosis, liver cirrhosis, and finally liver cancer. Identifying the progression of fatty liver through ultrasound imaging has become an essential part of health checkups. Diagnosis of fatty liver using ultrasound cannot express the exact content of fatty liver and is diagnosed by dividing it into mild, moderate, severe, etc. In addition, ultrasound imaging is a very subjective test that depends on the examination timing and examination method due to the subjective opinion of the ultrasound operator when diagnosing patients with fatty liver using images, and has limitations in follow-up observation and judgment of the significance of pathological progression.

Ultrasound images have a high reflection intensity in liver tissue with a high fat content, so the ultrasound penetration intensity changes depending on the depth. By measuring the change in the intensity of these reflected waves, the fat content can be quantitatively evaluated. In addition, the degree of absorption of ultrasound varies depending on the depth depending on the frequency of the injected ultrasound, so in the case of ultrasound with a high frequency, the degree of absorption increases in the organ, so a difference in the degree of absorption of ultrasound occurs at each frequency. The characteristics of star absorption should be determined and quantification of fat deposition should be performed.

Existing ultrasound images compensate for loss of image signals due to the decrease in ultrasound progress with distance using time gain control (TGC).

Accordingly, in the present invention, which will be described later, when time gain control (TGC) is not compensated, the physical characteristics seen during the ultrasound process are used to attenuate the signal according to the depth of the organ in the case of intrahepatic fat deposition. The degree of fat deposition is predicted using the slope of attenuation, and when the reflection intensity caused by the difference in the degree of fat deposition is severe, the signal intensity decreases as the degree of ultrasound penetration decreases depending on the depth of the organ. We would like to disclose a device and method for quantifying the fat content by determining the change in signal intensity according to the change in distance by frequency due to the gain control that is small and not compensated for.

Publication of Patent No. 10-2021-0010100 (Title of invention: Non-alcoholic fatty liver disease diagnosis method using body mass index and magnetic resonance imaging)

The purpose of the present invention is to provide a device and method of use for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images that can solve conventional problems.

To solve the above problem, a method of using a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention involves preparing a plurality of virtual fatty liver phantoms with a fat deposition rate in the range of 3 to 30%. steps; Collecting fat percentage ultrasound image data reflecting signal attenuation for each ultrasound probe frequency by gradually varying the ultrasound frequency of the plurality of virtual fatty liver phantoms; Measuring signal intensity according to ultrasound travel distance (depth) from the fat percentage ultrasound image data for each ultrasound transducer frequency; The slope of the signal intensity is calculated through linear regression analysis of the measured signal intensity according to the ultrasonic travel distance (depth), and among the calculated results, the coefficient of determination of the linear regression function used in the linear regression analysis ( ) It includes determining a value of 80% or more using ultrasound quantification data.

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In order to solve the above problem, a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention transmits ultrasound waves in a preset frequency range to each of a plurality of virtual fatty liver phantoms with different fat deposition ratios. an ultrasound unit that oscillates and collects fat percentage ultrasound image data at each frequency according to the thickness (depth) of the plurality of virtual fatty liver phantoms; A signal intensity measurement unit that measures signal intensity according to ultrasound travel distance (depth) from fat percentage ultrasound image data by frequency collected from each of a plurality of virtual fatty liver phantoms; A slope calculation unit that calculates the slope of the signal strength by applying a linear regression analysis algorithm to the measured signal strength according to the ultrasonic travel distance (depth); And the coefficient of determination of the linear regression function among the results of the slope calculation unit ( ) It includes a quantification unit that determines the value of 80% or more using ultrasound quantification data.

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Using the device and method for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention, it is a diagnostic technology that can more accurately express information about the fat content of the liver in ultrasound images, and the progression of the patient's fatty liver It has the advantage of being able to accurately express the process and being applicable to both (small) animals and the human body. Additionally, it has the advantage of being able to replace magnetic resonance imaging diagnostic methods, which are expensive and have complicated procedures.

In addition, by overcoming the limitations of ultrasound diagnosis of fatty liver, which is influenced by changes in ultrasound images due to image selection and parameter changes and the subjective judgment of the examiner, the pathological progression of fatty liver can be prevented during follow-up observation of the patient's fatty liver. It has the advantage of being able to accurately observe the process.

For example, not only is the current ultrasound-related market growing, but the number of obese patients is increasing worldwide, so it is expected that it will be possible to enter the related ultrasound diagnostic market, and not only in the medical field but also in the agricultural and life science field, as well as the degree of fat deposition in live animals. It has the advantage of being highly usable in quantifying the grade of Korean beef.

Figure 1 is an example diagram to explain ultrasonic signal attenuation depending on the type of medium.
Figure 2 is a flowchart explaining a method of using a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention.
Figure 3 is a configuration diagram of a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention.
Figures 4 and 5 are illustrations illustrating the in-vivo fatty liver ultrasound quantification experiment process using a fatty liver rat model using the present invention.

Hereinafter, embodiments of the present specification are described with reference to the attached drawings. However, this does not limit the technology described herein to specific embodiments, and should be understood to include various modifications, equivalents, and/or alternatives to the embodiments herein. . In connection with the description of the drawings, similar reference numbers may be used for similar components. In this specification, expressions such as “have,” “may have,” “includes,” or “may include” refer to the presence of the corresponding feature (e.g., a numerical value, function, operation, or component such as a part). , and does not rule out the existence of additional features.

As used herein, expressions such as “A or B,” “at least one of A or/and B,” or “one or more of A or/and B” may include all possible combinations of the items listed together. . For example, “A or B,” “at least one of A and B,” or “at least one of A or B” (1) includes at least one A, (2) includes at least one B, or (3) it may refer to all cases including both at least one A and at least one B.

As used herein, expressions such as “first,” “second,” “first,” or “second,” can modify various components regardless of order and/or importance, and refer to one component. It is only used to distinguish from other components and does not limit the components. For example, a first user device and a second user device may represent different user devices regardless of order or importance. For example, a first component may be renamed a second component without departing from the scope of rights described in this specification, and similarly, the second component may also be renamed to the first component.

A component (e.g., a first component) is “(operatively or communicatively) coupled with/to” another component (e.g., a second component). When referred to as being “connected to,” it should be understood that any component may be directly connected to the other component or may be connected through another component (e.g., a third component). On the other hand, when a component (e.g., a first component) is said to be “directly connected” or “directly connected” to another component (e.g., a second component), the component and the It may be understood that no other component (e.g., a third component) exists between other components.

As used herein, the expression “configured to” may mean, for example, “suitable for,” “having the capacity to,” or “having the capacity to.” ," can be used interchangeably with "designed to," "adapted to," "made to," or "capable of." The term “configured (or set to)” may not necessarily mean “specifically designed to” in hardware. Instead, in some contexts, the expression “a device configured to” may mean that the device is “capable of” working with other devices or components.

For example, the phrase "processor configured (or set) to perform A, B, and C" refers to a processor dedicated to performing the operations (e.g., an embedded processor), or by executing one or more software programs stored on a memory device. , may refer to a general-purpose processor (e.g., CPU or application processor) capable of performing the corresponding operations.

Terms used in this specification are merely used to describe specific embodiments and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions, unless the context clearly dictates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as generally understood by a person of ordinary skill in the technical field described herein. Among the terms used in this specification, terms defined in general dictionaries may be interpreted to have the same or similar meaning as the meaning they have in the context of related technology, and unless clearly defined in this specification, have an ideal or excessively formal meaning. It is not interpreted as In some cases, even terms defined in this specification cannot be interpreted to exclude embodiments of this specification.

Hereinafter, based on the attached drawings, an apparatus and method of use for quantifying fatty liver disease by ultrasound frequency according to an embodiment of the present invention will be described in more detail.

First, before explaining the device and method of use for diagnosing fatty liver quantification according to ultrasound frequency of the present invention, ultrasound imaging examination will be briefly described.

ultrasonic wave Imaging tests are based on the principle of diagnosing tissue by injecting ultrasound into the human body and using reflected waves returning from the tissue boundary.

In general, ultrasound does not propagate well in air, but it has the characteristic of propagating well in parenchymal or liquid tissues of human tissue.

Ultrasound has a physical theory of cycle (the time it takes for one complete cycle) and its reciprocal frequency (T=1/f, where T is the cycle f frequency), and the length of space occupied by one cycle is defined as the wavelength. It is defined as wavelength = propagation speed/frequency (MHz). As ultrasonic waves pass through a medium, their amplitude and intensity are attenuated. This phenomenon occurs due to absorption, scattering, and reflection of ultrasonic waves, and the concept that expresses the degree of such attenuation is the attenuation coefficient.

Here, the attenuation coefficient is defined as the sound attenuation per unit length when a sound wave passes through a medium (unit db/cm).

Acoustic resistance refers to the resistance that ultrasonic waves have when they hit a medium (acoustic resistance (Z) = density of the medium × propagation speed).

In other words, since the propagation speed of soft tissue is constant (assuming there is no fatty tissue), the propagation speed of soft tissue is constant, so it has acoustic resistance due to the density of the tissue.

As shown in Figure 1, when ultrasonic waves travel, the amount of transmitted ultrasonic waves is reduced due to reflection at the interface for imaging, resulting in signal attenuation depending on the distance.

Like soft tissue and fatty tissue, ultrasound with a reflection intensity of 10% and 90% transmitted contributes to imaging at the next depth, and as the fat content increases, ultrasound is greatly attenuated (as shown in the ultrasound image in Figure 1). As attenuation occurs, the signal becomes increasingly darker).

In other words, this signal attenuation is caused by the increase in the rate of fat deposition and the deep depth of the ultrasound. By measuring the signal according to the depth of the ultrasound, that is, the signal attenuation according to the depth is measured by a polynomial algorithm in the fat region. This invention aims to perform quantification by identifying the content by %.

Figure 2 is a flowchart explaining a method of using a device for quantifying and diagnosing fatty liver by ultrasound frequency according to an embodiment of the present invention, and Figure 3 is a device configuration diagram of a device for quantifying and diagnosing fatty liver by ultrasound frequency according to an embodiment of the present invention. am.

First, referring to FIGS. 2 and 3, the device 100 for diagnosing the quantification of fatty liver by ultrasound frequency according to an embodiment of the present invention includes an ultrasound unit 110, a signal intensity measurement unit 120, and a slope calculation unit 130. ) and a quantification unit 140. Before explaining the above-described configurations, the present invention uses a virtual fatty liver phantom for ultrasound quantification of fatty liver.

Here, the virtual fatty liver fatum is a test object for testing the degree of fat deposition in virtual tissues. It is made by mixing fat and water into an emulsion and then gelatinizing the agarose gel to 2-5%. It may be an experimental object (artificial structure). That is, the present invention increases the fat content by 3 to 30% (-3% (0, 3, 6, 9, ..... 21%) in order to collect fat percentage ultrasound according to the fat thickness of the fatty liver. Use the included virtual fatty liver phantom.

Meanwhile, the ultrasound unit 110 may be configured to oscillate ultrasound in a preset frequency range to each of a plurality of virtual fatty liver phantoms having different fat deposition rates and collect ultrasound images reflecting signal attenuation according to the fat deposition rate. there is.

That is, the ultrasound unit 110 may be configured to collect fat percent ultrasound data for each ultrasound probe frequency.

Here, the fat % ultrasound data by ultrasound probe frequency is obtained by varying the content of soybean oil using agarose gel, and then the signal attenuation by frequency (when the ultrasound progresses, the amount of transmitted ultrasound decreases due to reflection at the interface, and this causes It may be ultrasonic data measuring a phenomenon in which signal strength decreases with distance.

In these ultrasound images, a shaded area occurs within the ultrasound image due to signal attenuation.

Additionally, during ultrasound diagnosis, the data may be measured by frequency (Hz) after setting various parameter values.

Here, various parameters may include the dynamic range of the ultrasound image, and the dynamic range of the ultrasound image determines the shading level of the ultrasound image and is a factor that determines the contrast of the ultrasound image. This is because the wider the dynamic range, the wider the level of shading, which increases the contrast according to depth.

In other words, the fat percentage ultrasound data of the virtual fatty liver phantom collected from each of the plurality of virtual fatty liver phantoms is image information obtained by frequency for various fatty liver phantoms with different fat contents, and signal processing is performed according to the ultrasound travel distance (subject thickness). It may be performed data.

In addition, it can be image information for each frequency (high Hz for epidermal organs and low Hz transducer for deep organs).

In addition, it may be image data obtained from each fatty liver phantom (phantom with different fat content) according to the difference in ultrasound frequency in b-mode (bright mode, a method commonly expressed in ultrasound images).

For reference, the ultrasound image of the 5, 10, and 30% virtual fatty liver phantom may be an axial image of the fatty liver phantom. More specifically, the image was obtained by placing the manufactured virtual fatty liver phantom in a water tank and using 11.7MHz ultrasound. The purpose is to reflect ultrasound more strongly as the fat content increases, thereby changing the signal intensity as it goes deeper.

Next, the signal intensity measurement unit 120 may be configured to measure signal intensity according to the ultrasound travel distance (depth) from fat percentage ultrasound image data for each frequency collected from each of a plurality of virtual fatty liver phantoms.

Here, signal intensity refers to the change in brightness of pixels located in the signal measurement direction among the pixels in the ultrasound image.

Next, the slope calculation unit 130 may be configured to calculate the slope of the signal strength by applying the measured signal strength to the ultrasonic travel distance (depth) to a linear regression analysis algorithm. As an example, looking at the change in fat percentage signal according to distance (depth), when examined by simple linear regression, the higher the fat content, the lower the slope value.

Next, the quantification unit 140 determines the linear regression coefficient of determination ( ) It may be a configuration that constructs only values with a value of 80% or more as quantifiable data.

In other words, the change in the ultrasound signal according to the pixel distance is quantified through a linear regression function.

Therefore, we can evaluate the exact fat content percentage through ultrasound images and quantitatively express the fatty liver content using the slope value analyzed by simple linear regression.

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Figure 2 is a flowchart explaining a method of using a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention.

Referring to FIG. 2, the method (S700) of using a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in an ultrasound image according to an embodiment of the present invention first uses a plurality of virtual devices with a fat deposition rate in the range of 3 to 30%. After preparing the fatty liver phantom (S710), the ultrasound signal intensity of the plurality of virtual fatty liver phantoms is gradually varied to collect fat percentage ultrasound image data reflecting signal attenuation at each ultrasound probe frequency (S720).

Afterwards, the signal intensity according to the ultrasonic travel distance (depth) is measured from the fat percentage ultrasound image data for each frequency of the ultrasonic probe (S730), and the measured signal intensity is converted to signal intensity through linear regression analysis according to the ultrasonic travel distance (depth). Calculate the slope of , and among the calculated results, the coefficient of determination of the linear regression function ( ) consists of a process of determining a value greater than 80% of the value using ultrasound quantification data (S740).

The step of preparing the virtual fatty liver phantom includes mixing fat and water into an emulsion, and then using agarose gel to gelatinize the fatty liver phantom to contain fat and water. It can be.

Additionally, the step of collecting the ultrasound data may be a step using a frequency within the range of 3 to 5 MHz.

Additionally, the step of collecting the ultrasound image data may be a step of collecting ultrasound image data of a dicom file according to the dynamic range for each ultrasound frequency and the depth of the phantom.

Meanwhile, the S700 process sets the collected fat quantification data of fatty liver as a reference value and uses the selected frequency, dynamic range, and linear function of ultrasound as variables to determine the actual fat deposition rate of fatty liver. A prediction step may be further included.

Meanwhile, the method and device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images mentioned in the present invention can be applied to ultrasound fatty liver quantification for small animals.

For example, as shown in Figures 4 and 5, the degree of fat deposition in the process of inducing obese or non-obese fatty liver disease can be quantified using ultrasound and magnetic resonance spectroscopy.

More specifically, fatty liver is induced by administering a high-fat diet (or non-obese fatty liver MDC model) (here, the present invention uses mice to induce fatty liver disease using a high-fat diet or non-obese fatty liver model (methionine choline deficient induced fatty liver). induces.

Next, based on ultrasound image acquisition and MRS data, the degree of ultrasound attenuation (index) according to the fat content of mice is identified (quantified).

Referring to Figure 4, the induced fatty liver model undergoes ultrasound examination and 3TMRS examination at approximately the same time, and finally, the degree of signal attenuation of the ultrasound image is determined using the percentage of fatty liver obtained through magnetic resonance spectroscopy (MRS) as a reference value. Each fat % is quantified by ultrasound by polynomialization.

In other words, to secure data on early fatty liver, ultrasound and MRS were acquired during the fatty liver induction period (1 week), and mice (small animals) in which fatty liver was induced were subjected to phantom experiments using high Hz ultrasound (above 10 MHz). Imaging was performed in the same manner, and ultrasound imaging was performed without adjusting the TGC.

Afterwards, because changes in the dynamic range cause changes in slope, the dynamic range is fixed (dynamic rage determined through phantom experiments).

Afterwards, quantification of fat in the liver is performed through magnetic resonance spectroscopy immediately after the ultrasound image is acquired.

For reference, the data acquisition parameters using magnetic resonance spectroscopy are STEAM pulse sequence, Time to repeat: 8000msec (minimize T1 effect), Time of Echo: 30msec, but T2 Correction is performed.

Based on the experiment, the quantification method of fatty liver using a total of 7 lipid protons can be performed through MRS based on rat liver MRS data using rat 9.4T.

methyl protons (-CH ₃ );0.90ppm), methyleneprotons(-CH ₂ -)n;1.30ppm), ßresonance to the carboxy group(-CH ₂ -CH ₂ -CO;1.60ppm), allylic protons(-CH ₂ - C=C-CH ₂ -;2.03ppm), αmethylene resonance to the carboxyl group(-CH ₂ -CH ₂ -CO-;2.25ppm), diallylic protons(=C-CH ₂ -C=;2.78ppm), methane The fat percentage can be quantified through the water signal ratio of the sum of a total of 7 LPs, including protons (-CH=CH-; 5.30ppm).

In experiments, when acquiring data, the degree of signal attenuation of the lipid proton expressed is different, so the data is corrected using a correction coefficient.

Fat percentage (%) = [(t2-corrected 7 peak lipid protons integrated concentration value)/(t2-corrected 7 peak lipid protons integrated value + t2-corrected water value)]×100

As described above, the ultrasound image analysis method can perform graph fitting (polynomial graph fitting) by measuring signal intensity according to distance in the same way as in the phantom experiment, and the signal change according to distance is converted to distance as in the phantom experiment. It was confirmed that the signal was attenuated and that the higher the fat deposition, the higher the change in slope (polynomial change).

Therefore, by using the device and method for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images according to an embodiment of the present invention, it is possible to more accurately express information about the fat content of the liver in ultrasound images, as a diagnostic technology that can more accurately express the fatty liver of a patient. It has the advantage of being able to accurately express the process and being applicable to both (small) animals and the human body. Additionally, it has the advantage of being able to replace magnetic resonance imaging diagnostic methods, which are expensive and have complicated procedures.

In addition, by overcoming the limitations of ultrasound diagnosis of fatty liver, which is influenced by changes in ultrasound images due to image selection and parameter changes and the subjective judgment of the examiner, the pathological progression of fatty liver can be prevented during follow-up observation of the patient's fatty liver. It has the advantage of being able to accurately observe the process.

For example, not only is the current ultrasound-related market growing, but the number of obese patients is increasing worldwide, so it is expected that it will be possible to enter the related ultrasound diagnostic market, and not only in the medical field but also in the agricultural and life science field, as well as the degree of fat deposition in live animals. It has the advantage of being highly usable in quantifying the grade of Korean beef.

“~ part” used in one embodiment of the present invention may be implemented as a hardware component, a software component, and/or a combination of hardware components and software components. For example, devices and components described in embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general-purpose or special-purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may execute an operating system (OS) and one or more software applications that run on the operating system. Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, a single processing device may be described as being used; however, those skilled in the art will understand that a processing device includes multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, a processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software and/or data may be used by any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. , or may be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

The method according to an embodiment of the present invention may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The embodiments described above are examples, and those skilled in the art will be able to make various modifications and variations without departing from the essential characteristics of the present invention. Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical idea of the present invention, but rather to explain it, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention should be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope should be construed as being included in the scope of rights of the present invention.

100: Device for quantifying fatty liver disease by ultrasound frequency
110: Ultrasonic unit
120: Signal strength measurement unit
130: slope calculation unit
140: Quantification unit

Claims (10)

Preparing to produce a plurality of virtual fatty liver phantoms with a fat deposition rate ranging from 3 to 30%;
Collecting fat percentage ultrasound image data reflecting signal attenuation for each ultrasound probe frequency by gradually varying the ultrasound frequency of the plurality of virtual fatty liver phantoms;
Measuring signal intensity according to ultrasound travel distance (depth) from the fat percentage ultrasound image data for each ultrasound transducer frequency;
The slope of the signal intensity is calculated through linear regression analysis of the measured signal intensity according to the ultrasonic travel distance (depth), and among the calculated results, the coefficient of determination of the linear regression function used in the linear regression analysis ( ) Method of using a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images, including determining a value of 80% or more as ultrasound quantification data.
According to paragraph 1,
The step of preparing the virtual fatty liver phantom is,
Ultrasound scanning frequency in ultrasound images, characterized in that the step is to mix fat and water by forming an emulsion and then using agarose gel to produce a gelatinized fatty liver phantom to contain fat and water. How to use a device to diagnose fatty liver quantification.
According to paragraph 1,
The step of collecting ultrasound data is a method of using a device for diagnosing fatty liver quantification according to ultrasound scanning frequency in ultrasound images using frequencies within the range of 3 to 5 MHz.
According to paragraph 1,
The step of collecting the ultrasound image data is
A method of using a device to diagnose fatty liver quantification by ultrasound scanning frequency in ultrasound images, which is a step of collecting ultrasound image data of dicom files according to the dynamic range by ultrasound frequency and the depth of the phantom.
delete An ultrasound unit that oscillates ultrasound waves in a preset frequency range to each of a plurality of virtual fatty liver phantoms having different fat deposition ratios, and collects fat percentage ultrasound image data at each frequency according to the thickness (depth) of the plurality of virtual fatty liver phantoms;
A signal intensity measurement unit that measures signal intensity according to ultrasound travel distance (depth) from fat percentage ultrasound image data by frequency collected from each of a plurality of virtual fatty liver phantoms;
A slope calculation unit that calculates the slope of the signal strength by applying a linear regression analysis algorithm to the measured signal strength according to the ultrasonic travel distance (depth); and
Among the results of the slope calculation unit, the coefficient of determination of the linear regression function used in the linear regression analysis ( ) A device for diagnosing fatty liver quantification according to ultrasound scanning frequency, including a quantification unit that determines a value of 80% or more using ultrasound quantification data.
delete According to clause 6,
The virtual fatty liver phantom is
A device for quantifying fatty liver disease by ultrasound scanning frequency, which is an artificial structure made by mixing fat and water into an emulsion and gelatinizing it to contain fat and water using agarose gel. .
According to clause 6,
A device for diagnosing fatty liver quantification according to ultrasound scanning frequency, characterized in that the ultrasound unit oscillates at a frequency within the range of 3 to 5 MHz.
According to clause 6,
The ultrasound unit
A device for quantifying fatty liver disease by ultrasound scanning frequency that collects ultrasound images according to the dynamic range by ultrasound frequency and the depth (thickness) of the virtual fatty liver phantom as a dicom file.