KR20220040826A - Adaptive hybrid flow measurement method and apparatus for performing the same - Google Patents

Abstract

Disclosed are an adaptive hybrid flow measurement method and a device performing the same. According to one embodiment, the flow measurement method includes the steps of: acquiring a first ultrasound image and a second ultrasound image for the same measurement area; generating a first velocity vector field including flow information of the measurement area based on the first ultrasound image; generating a second velocity vector field including flow information of the measurement area based on the second ultrasound image; and correcting an error of the second velocity vector field based on the first velocity vector field.

Description

ADAPTIVE HYBRID FLOW MEASUREMENT METHOD AND APPARATUS FOR PERFORMING THE SAME

The present disclosure relates to an adaptive hybrid flow measurement method and an apparatus for performing the same.

Ultrasound imaging (USI) has been widely used to diagnose and analyze various cardiovascular diseases because of its advantages such as non-invasiveness, economical efficiency, and rapid image processing. A color Doppler imaging (CDI) technique can represent information about the direction and size of blood flow as a color map, and thus is widely used for analysis of hemodynamic characteristics.

CDI can measure only the flow velocity magnitude information in the traveling direction of the ultrasound. When the incidence angle of ultrasound is sufficiently secured, measurement accuracy is increased, and blood flow to be measured may be distorted differently from reality by unintentionally compressing tissues around blood vessels. When the pulse repetition frequency (PRF) of the CDI is not sufficient, the quality of the ultrasound image is deteriorated.

Echocardiographic particle image velocimetry (Echo-PIV) for cardiovascular measurement is a PIV technique applied to a B-mode (brightness mode) ultrasound image. Measure information. In the Echo-PIV technique, an ultrasound contrast medium must be added to the flow. Controversy over the biocompatibility of the ultrasound contrast agent has not yet been resolved, and the ultrasound contrast agent may not function properly as a target particle (or tracer particle) in the blood flow depending on the extinction rate and concentration of the contrast agent.

VFM (vector flow mapping) is a technique for measuring blood flow by applying a continuity equation to anatomical boundary conditions and flow information between adjacent pixels, and is used to measure intraventricular blood flow. However, the VFM based on the movement information of the wall of blood vessels cannot be applied in the condition of the cardiovascular wall with little or very much movement.

Speckle image velocimetry (SIV) is a technology that uses the ultrasonic speckle signal of red blood cells as tracer particles and can obtain information about the velocity field of the flow by applying the cross-correlation PIV (PIV) algorithm. am. However, in the case of SIV, the temporal resolution is lower than that of CDI, so the measurable maximum blood flow rate is relatively low. The technical limitations of SIV can be improved through hardware enhancements of USI devices, but they are expensive. Since SIV has not been completely clinically verified, there are practical limitations to its immediate clinical application.

The present invention relates to a flow measurement technique for improving the accuracy of color Doppler ultrasound imaging using speckle image velocity measurement.

However, the technical tasks are not limited to the above-described technical tasks, and other technical tasks may exist.

A flow measurement method according to an embodiment includes acquiring a B-mode ultrasound image and a Color Doppler image for the same measurement area, and adding a speckle image to the B-mode ultrasound image. generating a first velocity vector field by applying Velocimetry (SIV)), generating a second velocity vector field by applying a vector transformation algorithm to the color Doppler image, and based on the first velocity vector field and correcting an error in the second velocity vector field.

The correcting includes: detecting an error vector in a second velocity vector field based on a first error criterion; and placing a vector satisfying the second error criterion among the error vectors at the same measurement position in the first velocity vector field generating a third velocity vector field by substituting a corresponding vector.

The first error criterion is determined based on a difference between vector components of the first velocity vector field and the second velocity vector field for the same measurement position, and the second error criterion is the error vector and the error vector It can be determined based on the standard deviation of the difference of adjacent vectors.

The step of correcting includes generating a fourth velocity vector field by replacing a vector satisfying a third error criterion among vectors in the third velocity vector field with a vector corresponding to the same measurement position in the first velocity vector field. may include more.

The third error criterion may be determined based on a standard deviation of a difference between each vector in the third velocity vector field and a vector adjacent to each vector. and a processor for executing the instructions, wherein when the instructions are executed by the processor, the processor obtains a B-mode ultrasound image and a Color Doppler image for the same measurement area. A first velocity vector field is generated by applying Speckle Image Velocimetry (SIV) to the B-mode ultrasound image, and a vector transformation algorithm is applied to the color Doppler image to apply the second velocity vector. A field is generated, and an error of the second velocity vector field is corrected based on the first velocity vector field.

The processor detects an error vector in a second velocity vector field based on a first error criterion, and converts a vector satisfying a second error criterion among the error vectors to a vector corresponding to the same measurement position in the first velocity vector field. Alternatively, a third velocity vector field can be generated.

The first error criterion is determined based on a difference between vector components of the first velocity vector field and the second velocity vector field for the same measurement position, and the second error criterion is the error vector and the error vector It can be determined based on the standard deviation of the difference of adjacent vectors.

The processor may generate a fourth velocity vector field by replacing a vector satisfying a third error criterion among vectors in the third velocity vector field with a vector corresponding to the same measurement position in the first velocity vector field.

The third error criterion may be determined based on a standard deviation of a difference between each vector in the third velocity vector field and a vector adjacent to each vector.

1 is a diagram illustrating an ultrasound imaging system according to an exemplary embodiment.
FIG. 2 is a diagram illustrating an operation of the image processing apparatus shown in FIG. 1 .
3A to 3G are views illustrating images processed by the image processing apparatus shown in FIG. 1 at each stage.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, since various changes may be made to the embodiments, the scope of the patent application is not limited or limited by these embodiments. It should be understood that all modifications, equivalents and substitutes for the embodiments are included in the scope of the rights.

The terms used in the examples are used for the purpose of description only, and should not be construed as limiting. The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that a feature, number, step, operation, component, part, or a combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiment belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

In addition, in the description with reference to the accompanying drawings, the same components are given the same reference numerals regardless of the reference numerals, and the overlapping description thereof will be omitted. In describing the embodiment, if it is determined that a detailed description of a related known technology may unnecessarily obscure the gist of the embodiment, the detailed description thereof will be omitted.

In addition, in describing the components of the embodiment, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only for distinguishing the elements from other elements, and the essence, order, or order of the elements are not limited by the terms. When it is described that a component is "connected", "coupled" or "connected" to another component, the component may be directly connected or connected to the other component, but another component is between each component. It will be understood that may also be "connected", "coupled" or "connected".

Components included in one embodiment and components having a common function will be described using the same names in other embodiments. Unless otherwise stated, descriptions described in one embodiment may be applied to other embodiments as well, and detailed descriptions within the overlapping range will be omitted.

1 is a diagram illustrating an ultrasound imaging system according to an exemplary embodiment.

The flow measurement system 10 may measure the flow of the measurement target based on the ultrasound image. The flow measurement system 10 may measure the direction and magnitude of blood flow based on the ultrasound image.

The flow measurement system 10 may improve the accuracy of flow measurement through color Doppler imaging (CDI). The ultrasound imaging system 10 may improve the accuracy of flow measurement through CDI by using speckle image velocimetry (SIV), which has high spatial resolution and is capable of multidirectional analysis of flow.

The flow measurement system 10 may improve the performance of the CDI by combining the CDI and the SIV in an adaptive hybrid (AH) method. For example, the flow measurement system 10 measures the fast blood flow velocity in the center of the blood vessel with high temporal resolution through CDI, and measures the change in the flow velocity of the blood flow in the blood vessel edge region adjacent to the vessel wall with high spatial resolution using SIV. can be precisely measured.

The flow measurement system 10 includes an ultrasound imaging apparatus 100 and an image processing apparatus 200 .

The ultrasound imaging apparatus 100 may capture an ultrasound image of the measurement area. The ultrasound imaging apparatus 100 may photograph a continuous B-mode (brightness-mode) ultrasound image and a color Doppler image for the flow in the same measurement area.

The ultrasound imaging apparatus 100 may be implemented such that one device captures both a B-mode ultrasound image and a color Doppler image as shown in FIG. 1 , but is not limited thereto, and the ultrasound imaging apparatus 100 may be configured in the B-mode It may be implemented as separate photographing apparatuses for photographing an ultrasound image and a color Doppler image, respectively.

The image processing apparatus 200 may detect a flow in the image based on the B-mode ultrasound image and the color Doppler image. The image processing apparatus 200 may correct an error of the color Doppler image based on a result of applying SIV to the B-mode ultrasound image. The image processing apparatus 200 may improve accuracy of flow measurement by correcting an error of a color Doppler image.

The image processing apparatus 200 includes a memory 300 and a processor 400 .

The processor 400 may execute computer readable codes (eg, software) stored in the memory 300 and instructions induced by the processor.

The processor 400 may be a hardware-implemented data processing device having a circuit having a physical structure for executing desired operations. For example, desired operations may include code or instructions included in a program. For example, a data processing device implemented as hardware includes a microprocessor, a central processing unit, a processor core, a multi-core processor, and a multiprocessor. , an Application-Specific Integrated Circuit (ASIC), and a Field Programmable Gate Array (FPGA).

The memory 300 may store instructions (or programs) executable by the processor. For example, the instructions may include instructions for executing an operation of a processor and/or an operation of each component of the processor.

The memory 300 may be implemented as a volatile memory device or a nonvolatile memory device. The volatile memory device may be implemented as dynamic random access memory (DRAM), static random access memory (SRAM), thyristor RAM (T-RAM), zero capacitor RAM (Z-RAM), or twin transistor RAM (TTRAM). Nonvolatile memory devices include EEPROM (Electrically Erasable Programmable Read-Only Memory), Flash memory, MRAM (Magnetic RAM), Spin-Transfer Torque (STT)-MRAM (Spin-Transfer Torque (STT)-MRAM), Conductive Bridging RAM (CBRAM) , FeRAM(Ferroelectric RAM), PRAM(Phase change RAM), Resistive RAM(RRAM), Nanotube RRAM(Nanotube RRAM), Polymer RAM(Polymer RAM(PoRAM)), Nano Floating Gate Memory (NFGM)), a holographic memory, a molecular electronic memory device, or an Insulator Resistance Change Memory.

Hereinafter, a flow measurement method performed by the processor 400 of the image processing apparatus 200 will be described in detail with reference to FIGS. 2 to 3G .

FIG. 2 is a diagram illustrating an operation of the image processing apparatus shown in FIG. 1 .

The processor 400 may acquire a continuous B-mode ultrasound image and a color Doppler image for the flow in the same measurement area. For example, the processor 400 may acquire a B-mode ultrasound image and a color Doppler image from the ultrasound imaging apparatus 100 . The color Doppler image may be an image generated through CDI.

The processor 400 may generate a two-dimensional first velocity vector field by applying SIV to a continuous B-mode ultrasound image, and a data grid of a velocity vector field obtained through SIV by applying a vector transformation algorithm to a color Doppler image. A two-dimensional second velocity vector field can be generated that coincides with .

The processor 400 may find and exclude a measurement error value in the second velocity vector field generated through CDI using a measurement error threshold. The processor 400 may replace an error value excluded from the second velocity vector field with a measured value in the first velocity vector field generated through the SIV. In this case, the measurement error criterion may include two criteria.

The processor 400 may determine the first error criterion as a difference between vector components at the same position in the first velocity vector field and the second velocity vector field. When the difference between the vector components of the first velocity vector field and the second velocity vector field at the same measurement position is close to 0, the processor 400 may determine that the position measurement result through CDI at the position is accurate.

The processor 400 may calculate a difference between the vector components of the first velocity vector field and the second velocity vector field at each measurement position, and may sequentially extract 10 values from the value closest to 0 among them. The processor 400 may determine a three standard deviation range (m±3σ) of the mean as the first error criterion according to a three-sigma rule.

When the difference between the vector components between the first velocity vector field and the second velocity vector field is greater than the first error criterion, the processor 400 regards the flow measurement result through CDI as a measurement error vector and applies the second error criterion. can do.

The processor 400 may calculate a difference between a vector component and an adjacent vector component in each of the first velocity vector field and the second velocity vector field based on the second error criterion, and calculate a standard deviation of the differences to compare magnitudes. For example, the second error criterion can be expressed as Equation (1).

및

는 각각 제2 속도 벡터장 내 특정 벡터의 제1 및 제2 성분 값을 의미하고,

및

는 각각 제2 속도 벡터장 내 특정 벡터와 인접한 벡터의 제1 성분 및 제2 성분을 의미하고,

및

는 각각 제1 속도 벡터장 내 특정 벡터의 제1 및 제2 성분 값을 의미하고,

및

는 제1 속도 벡터장 내 특정 벡터와 인접한 벡터의 제1 성분 및 제2 성분을 의미하고, c ₁ 은 1보다 작은 보정 상수로 측정 결과에 따라 실험적으로 정의될 수 있다.At this time,

and

denotes the values of the first and second components of a specific vector in the second velocity vector field, respectively,

and

denotes a first component and a second component of a vector adjacent to a specific vector in the second velocity vector field, respectively,

and

denotes the values of the first and second components of a specific vector in the first velocity vector field, respectively,

and

denotes a first component and a second component of a vector adjacent to a specific vector in the first velocity vector field, and c ₁ is a correction constant less than 1 and may be experimentally defined according to a measurement result.

The processor 400 determines whether the vector identified as the measurement error vector according to the first error criterion among the vectors in the second velocity vector field satisfies the second error criterion expressed by Equation 1, the first velocity vector field at the same position It can be replaced with a vector. That is, the CDI measurement result satisfying the first error criterion and the second error criterion may be replaced with the SIV measurement result.

The processor 400 may generate an adaptive hybrid velocity field by combining the adaptive hybrid method in the above-described first ^iteration .

The processor 400 may perform a second iteration to improve flow measurement accuracy by combining the adaptive hybrid method.

The processor 400 may calculate a difference between a vector component and an adjacent vector component in each of the first velocity vector field and the second velocity vector field based on the second error criterion, and calculate a standard deviation of the differences to compare magnitudes.

In the second iteration, the processor 400 may repeat the same process of substituting the vector for the AH velocity vector field according to the second error criterion applied in the first iteration. For example, the processor 400 may calculate a difference between a vector in the third velocity vector field and an adjacent vector based on the third error criterion, calculate a standard deviation of the differences, and compare magnitudes. The processor 400 may check the measurement error through statistical comparison analysis of the vector difference according to the location of the correction result by the combination of the adaptive hybrid method and the measurement result of the SIV.

The processor 400 may correct the error according to the third measurement error criterion. The processor 400 may calculate a difference between a vector and an adjacent vector with respect to the vector of the AH velocity vector field, calculate a standard deviation of the differences, and compare the values. For example, the third error criterion can be expressed as Equation (2).

및

는 AH 속도 벡터장 내 특정 벡터의 제1 성분 및 제2 성분을 의미하고,

및

는 특정 벡터와 인접한 벡터의 제1 성분 및 제2 성분을 의미하고, c ₂ 는 1보다 작은 보정 상수로 측정 결과에 따라 실험적으로 정의될 수 있다.At this time,

and

denotes the first and second components of a specific vector in the AH velocity vector field,

and

denotes a first component and a second component of a vector adjacent to a specific vector, and c ₂ is a correction constant less than 1 and may be experimentally defined according to a measurement result.

When the vector in the AH velocity vector field satisfies the third error criterion expressed by Equation (2), the processor 400 may substitute the vector in the first velocity vector field at the same location.

The processor 400 may accurately measure the flow in the measurement area based on the finally acquired velocity vector field.

The processor 400 may perform real-time imaging by expressing information on the flow velocity field detected based on the velocity vector field on the ultrasound B-mode image.

3A to 3F are diagrams illustrating images processed by the image processing apparatus shown in FIG. 1 at each stage.

3A shows a color Doppler image obtained through CDI. The processor 400 may detect flow velocity magnitude information in the ultrasonic pulse traveling direction as shown in FIG. 3B based on the color Doppler image. The processor 400 may convert a color Doppler image obtained through CDI into a two-dimensional velocity field as shown in FIG. 3C using a vector transformation algorithm. 3C shows the result of adding flow direction information to velocity magnitude component information.

The processor 400 obtains velocity vector fields having different velocity information based on a color Doppler image captured through ultrasound of different incidence angles through a vector conversion algorithm, and synthesizes the velocity vector fields with different velocity vector fields, as shown in FIG. 3C . A more accurate velocity vector field can be generated as

3D shows a two-dimensional velocity vector field obtained by applying SIV to a B-mode ultrasound image. The velocity vector field obtained by applying SIV may be a vector field generated based on a B-mode ultrasound image measured under the same flow conditions as a color Doppler image.

The processor 400 may match the data grid of the velocity vector field obtained through the color Doppler image with the data grid of the velocity vector field obtained through the SIV as shown in FIG. 3E .

After matching the data grid, the processor 400 may generate a more accurate flow velocity vector field by combining the two velocity vector fields in an adaptive hybrid manner as shown in FIG. 3F .

The processor 400 may display the result of the flow velocity field together with the ultrasound B-mode image for real-time imaging as shown in FIG. 3G . At this time, Figure 3g shows 2D, 4D, and 6D from the valve near the valve of the greater saphenous vein (GSV) on the knee side of the person (in this case, D means the valve diameter of the person's knee side great saphenous vein) It may be that the velocity field information of the blood flow is obtained at points S1, S2, and S3 downstream by a distance and displayed together with the B-mode ultrasound image.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The 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 the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. 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.

Software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or apparatus, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques are performed in an order different from the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (10)

acquiring a B-mode ultrasound image and a Color Doppler image for the same measurement area;
generating a first velocity vector field by applying speckle image velocity measurement (SIV) to the B-mode ultrasound image;
generating a second velocity vector field by applying a vector transformation algorithm to the color Doppler image; and
correcting an error of the second velocity vector field based on the first velocity vector field
Including, flow measurement method.
According to claim 1,
The correcting step is
detecting an error vector in a second velocity vector field based on the first error criterion; and
generating a third velocity vector field by replacing a vector satisfying a second error criterion among the error vectors with a vector corresponding to the same measurement position in the first velocity vector field
Including, flow measurement method.
3. The method of claim 2,
The first error criterion is,
is determined based on the difference between the vector components of the first and second velocity vector fields for the same measurement position,
The second error criterion is,
is determined based on a standard deviation of the error vector and a difference between the error vector and an adjacent vector.
3. The method of claim 2,
The correcting step is
and generating a fourth velocity vector field by substituting a vector that satisfies a third error criterion among the vectors in the third velocity vector field with a vector corresponding to the same measurement position in the first velocity vector field. method.
5. The method of claim 4,
The third error criterion is,
and a standard deviation of each vector in the third velocity vector field and a difference between each vector and an adjacent vector.
a memory containing instructions; and
a processor for executing the instructions
including,
When the instructions are executed by the processor, the processor
A first velocity vector is obtained by acquiring a B-mode ultrasound image and a Color Doppler image for the same measurement area, and applying a speckle image velocity measurement (SIV) to the B-mode ultrasound image. generating a field, generating the second velocity vector field by applying a vector transformation algorithm to the color Doppler image, and correcting an error in the second velocity vector field based on the first velocity vector field.
7. The method of claim 6,
The processor is
An error vector in the second velocity vector field is detected based on the first error criterion, and a vector satisfying the second error criterion among the error vectors is replaced with a vector corresponding to the same measurement position in the first velocity vector field to obtain a third A flow measuring device that produces a velocity vector field.
8. The method of claim 7,
The first error criterion is,
is determined based on the difference between the vector components of the first and second velocity vector fields for the same measurement position,
The second error criterion is,
and a standard deviation of the error vector and a difference between the error vector and an adjacent vector.
9. The method of claim 8,
The processor is
and generating a fourth velocity vector field by replacing a vector satisfying a third error criterion among vectors in the third velocity vector field with a vector corresponding to the same measurement position in the first velocity vector field.
10. The method of claim 9,
The third error criterion is,
and a standard deviation of each vector in the third velocity vector field and a difference between each vector and an adjacent vector.

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