WO2016159417A1

WO2016159417A1 - Image processing device and method removing afterimage of ultrasonic image

Info

Publication number: WO2016159417A1
Application number: PCT/KR2015/003308
Authority: WO
Inventors: 이지하
Original assignee: 알피니언메디칼시스템 주식회사
Priority date: 2015-04-02
Filing date: 2015-04-02
Publication date: 2016-10-06

Abstract

Disclosed are an image processing device and method removing an afterimage of an ultrasonic image. According to one aspect of one embodiment of the present invention, the main purpose is to provide an ultrasonic image processing method and device provided with a filter which adaptively filters an afterimage according to information input by a person operating an ultrasonic medical device.

Description

An image processing apparatus and method for removing afterimages of ultrasound images

The present embodiment relates to an image processing apparatus and method for removing afterimages that may occur in an ultrasound image.

The contents described in this section merely provide background information on the present embodiment and do not constitute a prior art.

Ultrasound medical devices have non-invasive and non-destructive characteristics, and thus are widely used in the medical field for obtaining information inside an object. Without the need for a surgical operation to directly incise and observe an object, an ultrasound medical apparatus can provide a doctor with a high-resolution image of an inside of an object in real time, and thus is very important in the medical field.

The ultrasound medical apparatus transmits an ultrasound signal to an object and forms an ultrasound image by using an ultrasound signal (for example, an ultrasound echo signal) reflected from the object. When the ultrasound medical apparatus forms an ultrasound image, when an ultrasound image of the stationary object is formed, an ultrasound image may be formed without any problem. However, when the ultrasound medical apparatus forms an ultrasound image of a moving object, an afterimage may occur on the formed ultrasound image.

Meanwhile, in the ultrasound medical apparatus, an ultrasound image to be formed varies according to preset information (eg, frame rate) in the device. Accordingly, there is a need for an ultrasound system having an ultrasound image processing apparatus that adaptively removes an afterimage occurring in an ultrasound image that is changed together when preset information is changed in the device.

An embodiment of the present invention is to provide an ultrasound image processing apparatus and method including a filter for adaptively filtering an afterimage based on information input by an operator of an ultrasound medical apparatus.

According to an aspect of the present embodiment, the frame data generation unit for generating frame data on the basis of the reflected signal of the ultrasonic wave transmitted to the object and the frame data generation unit, the previous weighted frame data and the frame data generation unit And a residual image processing unit for generating frame data from which afterimages are removed by weighted averaging currently input frame data using filter coefficients, wherein the filter coefficients include a decay ratio, a frame rate, and an afterimage sustain frequency. It provides an ultrasound medical device, characterized in that it is derived from a nonlinear function of Persistence Frequency.

According to another aspect of the present embodiment, a coefficient generator for generating filter coefficients using a frame rate, a persistence frequency, and a predetermined decay ratio, currently input frame data, previously A weighted average of the generated weighted frame data using the filter coefficients to generate frame data from which residual images are removed, and a storage unit for storing frame data weighted averaged by the filtering unit. Provide a processing device.

According to another aspect of the present embodiment, in the ultrasonic image processing method for reducing the afterimage effect, the filter coefficient is determined using a frame rate, a persistence frequency and a decay ratio. And weighted averaging the currently input frame data and previous weight frame data using filter coefficients to generate final weight frame data.

As described above, according to an aspect of the present embodiment, there is an advantage in that afterimages can be efficiently removed by adaptively adjusting filter coefficients according to information set to acquire an ultrasound image.

According to another aspect, there is an effect that the filter coefficients can be calculated by a simple operation without additional memory for separately storing each filter coefficient corresponding to the information input by the operator.

1 is a block diagram illustrating an ultrasound medical apparatus according to an embodiment of the present invention.

2 is a block diagram schematically illustrating an afterimage processing unit according to an exemplary embodiment of the present invention.

3 is a diagram illustrating a process of filtering by a filtering unit according to an embodiment of the present invention.

4 is a flowchart illustrating a procedure of an ultrasonic image processing method according to an embodiment of the present invention.

Hereinafter, some embodiments of the present invention will be described in detail through exemplary drawings. In adding reference numerals to the components of each drawing, it should be noted that the same reference numerals are assigned to the same components as much as possible even though they are shown in different drawings. In addition, in describing the present invention, when it is determined that the detailed description of the related well-known configuration or function may obscure the gist of the present invention, the detailed description thereof will be omitted.

In addition, throughout the specification, when a part is said to include, 'include' a certain component, which may further include other components rather than excluding other components unless otherwise stated. it means. In addition, as described in the specification. The terms 'unit' and 'module' refer to a unit that processes at least one function or operation, which may be implemented by hardware or software or a combination of hardware and software.

Referring to FIG. 1, an ultrasound medical apparatus 100 according to an exemplary embodiment of the present invention may include a transducer 110, a frame data generator 120, a controller 130, an afterimage processor 140, and a display unit 150. ). The configuration shown in FIG. 1 in relation to the ultrasound medical apparatus 100 is only an embodiment, and in other embodiments, some blocks may be added, changed, or deleted. In addition, the ultrasound medical apparatus 100 according to the present embodiment may be a device for performing a hardware-based ultrasound diagnosis, but may be implemented in software, for example, a central processing unit (CPU) and a general purpose graphic processing unit (GPGPU). ) May be configured to parallelize the functionality of each component in software.

The transducer 110 includes a transducer element for converting an electrical signal into acoustic energy (or vice versa), and transmits the converted ultrasonic waves (acoustic energy) to the object, and transmits the ultrasonic waves reflected from the object. Receives an echo signal and converts it into an electrical signal. The transducer may include a plurality of transducer elements, and the plurality of transducer elements may be formed in a one-dimensional or two-dimensional array.

The transducer 110 transmits focused ultrasound toward a focal point under the control of the controller 130 and receives an echo signal reflected from the object to form one scan line. In forming one ultrasonic scanline to transmit to the object, all of the plurality of transducer elements included in the transducer may be used, but in some cases, only one of the plurality of transducer elements may be used to An ultrasound scan line may be formed.

The transducer 110 sequentially transmits ultrasound to each scan line and collects data, thereby acquiring data for generating an ultrasound image of one frame.

Meanwhile, in the present embodiment, the transducer 110 has been described as transmitting focused ultrasound, but the present invention is not limited thereto. For example, the transducer 110 may transmit unfocused ultrasound, such as a plane wave, and may receive data for generating an ultrasound image of one frame by receiving an echo signal of the transmitted ultrasound.

The frame data generation unit 120 generates frame data based on the reflection signal of the ultrasonic wave received by the transducer. The frame data generator 120 includes a beamformer 122, a signal processor 124, and a scan converter 126.

The beamformer 122 includes a transmit beamformer and a receive beamformer.

The transmit beamformer delays the electrical signal applied to each transducer element so that ultrasound is focused on the object. The reason for delaying the electrical signal is that each element has a different distance to the focal point where the ultrasound is focused on the object. The transmission beamformer delays the electrical signal applied to each element differently according to the distance between the element and the focal point, thereby focusing the ultrasound to the desired focal point of the object.

When each transducer element receives the reflected signal and converts the signal into an electrical signal, the reception beamformer delays the signal output from each transducer element and converts the signal into the same phase signal. As described above, since there is a difference in distance between the respective elements and the focal point, each converted electric signal is out of phase with each ultrasonic path. The receive beamformer converts the electrical signal into the same phase through a time delay that compensates for path differences along different paths. Each electrical signal converted to the same phase is used as data to combine with each other to form one scan line.

The signal processor 124 converts the electrical signal received from the beamformer 122 into baseband signals and detects an envelope using a quadrature demodulator to generate one scan line data. .

As described above, the transducer sequentially generates and transmits one frame data by repeatedly transmitting and receiving ultrasonic waves to each scan line and generating scan line data accordingly.

The scan converter 126 records the generated frame data in a memory, matches the scanning direction of the data with the pixel direction of the display unit, and maps the corresponding data to the pixel position of the display unit. In other words, the scan converter converts the generated frame data into image data and then outputs it to the display unit.

The controller 130 receives an instruction by an operator's operation and performs overall management of the frame data generator 120. The controller 130 controls the frame data generator so that the transducer 110 transmits ultrasonic pulses having the same phase. The controller 130 transmits a control signal including a command by an operator's operation to control the frame data generator. Commands by the operator's operation include a frame rate, persistence frequency, attenuation rate, and the like.

The afterimage processing unit 140 receives the frame data from the signal processing unit 124 and filters the filter using a filter to remove the afterimage of the received frame data. This will be described in more detail with reference to FIGS. 2 and 3.

The display unit 150 outputs the final frame data from which the afterimage is removed by the afterimage processing unit 140.

In the exemplary embodiment of the present invention, the scan converter 126 is described as being positioned between the signal processor 124 and the afterimage processor 140. However, the present invention is not limited thereto, and the scan converter 126 is the afterimage processor. It may be connected to the rear end of 140. The scan converting unit 126 may be connected to the rear end of the afterimage processing unit 140 and scan-convert the data from which the afterimages are removed, and then output the scan data to the display unit 150.

2 is a block diagram illustrating an afterimage processing unit according to an embodiment of the present invention, and FIG. 3 is a diagram illustrating a process of filtering by a filtering unit according to an embodiment of the present invention. In Fig. 3, the filter coefficient is described as α for convenience.

2, the afterimage processor 120 according to an exemplary embodiment of the present invention includes a filter 210, a coefficient generator 220, and a storage 230.

The filtering unit 210 receives the frame data from the signal processor or the scan converter, and filters the residual image of the received frame data. The filtering unit 210 filters the residual image by performing a weighted average of the received frame data and the previous weighted frame data to filter the residual image of the received frame data. In the weighted average of the received frame data and the previous weighted frame data, the filtering unit 210 uses a filter coefficient received from the coefficient generator as a weight to multiply each of the received frame data and the previous weighted frame data. Looking at the filtering unit 210 to filter the residual image using the weighted average as follows.

Equation 1

K denotes a frame number, α denotes a filter coefficient, x (k) denotes the k-th input frame data, and y (k-1) denotes the weighted average of the (k-1) th frame. It means weighted frame data. Referring to Equation 1, the current weighted frame data is derived by linear combination between the previous weighted frame data and the currently input frame data. Specifically, the k th weight frame data y (k) is a value obtained by multiplying the k th received frame data x (k) by α (filter coefficient) and the previous weight frame data y (k-1) 1-α. It can be calculated as the sum of the product of (filter coefficients). To this end, the filtering unit may be implemented, for example, as shown in FIG. 3.

Referring to FIG. 3 illustrating a configuration of the filtering unit, the filtering unit 210 may include a first multiplier 310, a delay unit 320, a second multiplier 330, and an adder 340.

When the frame data obtained by transmitting the ultrasound is input, the first multiplier 310 multiplies the filter coefficient α generated by the coefficient generator 220 with the currently input frame data and outputs the multiplier 340 to the adder 340. Meanwhile, the weighted frame data generated by the weighting average just before the filtering unit 210 is delayed by one frame by the delay unit 320. The second multiplier 330 multiplies the previous weighted frame data output from the delayer 320 by the filter coefficients 1-α and outputs the result to the adder 340. The adder 340 adds the output of the first multiplier 310 and the output of the second multiplier 330 to generate current weighted frame data.

The number of frames n effectively used for weighted averaging may be calculated by the frame rate and persistence frequency set by the operator. For example, as shown in Equation 2, the frame rate can be obtained by dividing the afterimage sustain frequency.

Equation 2

The frame rate means a value indicating how many frame data are generated per second. Afterimage persistence frequency refers to an inverse value of the time (period) of afterimage persistence in a human eye. By dividing the persistence frequency by the frame rate (the same as multiplying the duration of the afterimage by the frame rate), you can see how many frames the afterimage lasts. Therefore, if the weighted average is repeated as many times as obtained using Equation 2, afterimages existing in the frame data can be effectively removed.

The coefficient generator 220 generates filter coefficients used by the filtering unit. The filter coefficients can be calculated by a nonlinear function of the number of frames and the decay rate effectively used to weight the average. Here, the number of frames effectively used for weighted averaging can be calculated using the frame rate and the residual persistence frequency, as described above. Hereinafter, the process of estimating the filter coefficient will be described in more detail.

Equation 3

Assuming that there is no additional frame data received in addition to the first input frame data and the afterimage in the frame data decreases at a constant rate with time, equation (2) can be derived from equation (1) since x (k) = 0. Here, y (0) refers to the first frame data input, and y (k) (k = 1, 2, ... n) refers to the frame data of which the afterimage is reduced at the time when the k-th frame is acquired. Means. If the afterimage of y (0) persists until the time of the nth frame elapses, (4) can be obtained from (3).

Equation 4

In Equation 4, K represents a decay rate. The decay rate means the ratio between the frame data y (n) immediately before the afterimage disappears and the first input frame data y (0). This attenuation rate K can experimentally obtain how much the residual image of the first input frame data remains after n frames have elapsed. Therefore, the filter coefficient α can be calculated by the decay rate K and the number of frames n in which the afterimage persists, as shown in Equation (5).

Equation 5

Since the frame number n effectively used for the weighted average can be calculated by dividing the frame rate by the afterimage sustain frequency as described in Equation 2, Equation 6 holds.

Equation 6

As can be seen from Equation 6, since the filter coefficient is configured in the form of a simple exponential function of the decay rate, it is not necessary to store all the filter coefficients corresponding to each condition according to a predetermined condition. Filter coefficients can be generated.

The coefficient generator 220 receives the input parameter from the controller and calculates a filter coefficient based on the above-described method when a parameter by manipulation such as attenuation rate, frame rate, and residual image sustain frequency is input from the operator. According to an embodiment of the present invention, since the filter coefficients can be generated by a simple operation from the parameters of the operation, the time required for filtering can be reduced, and the filter coefficients calculated according to the parameters are stored in the form of a lookup table in advance. There is an advantage that the coefficient generator can be implemented without a memory. However, the present invention is not limited thereto. For example, the filter coefficients calculated by Equation 6 are stored in a memory in the form of a lookup table, and when a parameter such as attenuation rate, frame rate and residual persistence frequency is input from an operator, the lookup table It may also be possible to implement the coefficient generator 210 by searching for a filter coefficient corresponding to the parameter input from the.

The storage unit 230 stores previous weighted frame data previously generated through the filtering process of the filtering unit 220 and current weighted frame data generated through the filtering process of the filtering unit 220. The storage unit 230 provides previous weighted frame data required for the filtering process to remove residual images of the received frame data. In addition, the filtering unit 220 stores the current weighted frame data generated by performing the filtering process according to the number of frames n effectively used to perform the weighted average.

Referring to FIG. 2, the afterimage processor 120 according to another exemplary embodiment of the present invention includes a filtering unit 210, a coefficient generator 220, and a storage unit 230.

The filtering unit 210 receives the frame data from the signal processor or the scan converter, and filters the residual image of the received frame data. The filtering unit 210 filters the residual image by performing a weighted average of the received frame data and the previous weighted frame data to filter the residual image of the received frame data. In the weighted average of the received frame data and the previous weighted frame data, the filtering unit 210 uses a filter coefficient received from the coefficient generator as a weight to multiply each of the received frame data and the previous weighted frame data. When the number n of frames effectively used to perform the weighted average is divided into the integer part A and the fractional part x, such as A.x, the filtering method 210 filters the residual image as follows.

Equation 7

Here k denotes a frame number and x (k) denotes k-th input frame data. Referring to equation (7), the current weighted frame data is the (k-A + 1) th frame data input from the kth input (currently input) frame weighted by 1 / n and the (kA) th input. The weighted frame data is weighted as 0.x (n fractional part of n) / n and can be calculated as a sum of these.

The coefficient generator 220 generates a filter coefficient (weighted value) used in the filtering unit. As described above, the number n of frames effectively used for weighted averaging can be known by dividing the frame rate among the parameters by the operation by the residual persistence frequency. Therefore, the coefficient generator calculates n values, n integer parts and n fractional parts from the frame rate and the residual persistence frequency among the parameters by the operation. The calculated n value, the integer part of n and the fractional part of n are provided to the filtering part and used as a filter coefficient in the filtering part.

The storage unit 230 stores previously input frame data required by the filtering unit. In addition, since the frame data currently input is required to weight average the frame data to be input later, when the weighted frame data of the currently input frame data is obtained (filtering is completed), the storage unit also stores the currently input frame data. do.

Each component included in the afterimage removal unit illustrated in FIG. 2 is connected to a communication path connecting a software module or a hardware module inside the device to operate organically with each other. These components communicate using one or more communication buses or signal lines.

The filter coefficient is generated using the frame rate, the afterimage persistence frequency, and the decay rate (S410). The coefficient generator included in the afterimage removal unit receives parameters from an operation such as a frame rate, an afterimage persistence frequency, and a decay rate from the control unit. Using the received information, the filter coefficient is calculated based on the method described above with reference to FIG. The filter coefficients consist of the exponential function of the above parameters. Here, the exponential function may be expressed in the form of having an attenuation rate lower and a value obtained by dividing the frame rate by the afterimage sustain frequency as an exponent.

A weighted average of the currently received frame data and the previous weighted frame data using the filter coefficients (S420). The generated filter coefficients, the current frame data, and the previous weighted frame data are received, and the currently received frame data and the previous weighted frame data are multiplied by different weight values composed of the filter coefficients. For example, as in Equation 1, the weighted average is obtained by multiplying the received frame data by the filter coefficient α and multiplying the previous weighted frame data by subtracting the filter coefficient (1-α). In this way, the weighted average is obtained to remove the afterimage present in the frame data.

In FIG. 4, processes S410 to S420 are described as being sequentially executed. However, this is only illustrative of the technical idea of the exemplary embodiment of the present invention. In other words, a person of ordinary skill in the art to which an embodiment of the present invention belongs may execute or change the order described in FIG. 4 without departing from the essential characteristics of an embodiment of the present invention, or one of processes S410 to S420. Since the above processes may be variously modified and modified to be executed in parallel, FIG. 4 is not limited to the time series order.

Meanwhile, the processes illustrated in FIG. 4 may be embodied as computer readable codes on a computer readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored. In other words, a computer-readable recording medium may include a magnetic storage medium (eg, a ROM, a floppy disk, a hard disk, etc.), an optical reading medium (eg, a CD-ROM, a DVD, etc.) and a carrier wave (eg, Storage media such as transmission over the Internet). The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.

The above description is merely illustrative of the technical idea of the present embodiment, and those skilled in the art to which the present embodiment belongs may make various modifications and changes without departing from the essential characteristics of the present embodiment. Therefore, the present embodiments are not intended to limit the technical idea of the present embodiment but to describe the present invention, and the scope of the technical idea of the present embodiment is not limited by these embodiments. The scope of protection of the present embodiment should be interpreted by the following claims, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of the present embodiment.

(Explanation of the sign)

100: ultrasonic medical device 110: transducer

120: frame data generation unit 122: beamformer

124: signal processing unit 126: scanning conversion unit

130: control unit 140: afterimage processing unit

150: display unit 210: filtering unit

220: coefficient generation unit 230: storage unit

310: first multiplier 320: delay

330: second multiplier 340: adder

Claims

A frame data generator for generating frame data based on the reflected signal of the ultrasound transmitted to the object; And

A residual image processing unit connected to the frame data generation unit and generating frame data from which residual images are removed by weighted averaging previously weighted frame data and frame data currently input from the frame data generation unit using filter coefficients;

And the filter coefficients are derived from nonlinear functions of decay ratio, frame rate, and persistence frequency.
The method of claim 1,

The nonlinear function is

And the attenuation rate as a base, and expressed as an exponential function in which the value obtained by dividing the frame rate by the after-image persistence frequency is an exponent.
A coefficient generator for generating filter coefficients using a frame rate, a persistence frequency, and a predetermined decay ratio;

A filtering unit which generates frame data from which residual images are removed by weighted averaging currently input frame data and previously generated weight frame data using the filter coefficients; And

A storage unit for storing frame data weighted and averaged by the filtering unit

Ultrasonic image processing apparatus comprising a.
The method of claim 3,

The coefficient generator,

And the filter coefficients are generated by using an exponential function of which the predetermined attenuation rate is lowered and the frame rate divided by the afterimage sustain frequency is an exponential function.
In the ultrasonic image processing method for reducing the afterimage effect,

Determining filter coefficients using a frame rate, a persistence frequency, and a decay ratio;

And performing weighted averaging of the currently input frame data and previous weight frame data using filter coefficients to generate final weight frame data.
The method of claim 5,

The filter coefficient is,

And a derivation function based on the decay rate as a base and a value obtained by dividing the frame rate by the afterimage sustain frequency as an exponent.