JP6008814B2 - Image analysis system, image analysis method, image analysis program, and ultrasonic diagnostic apparatus - Google Patents

Description

  The present invention acquires and outputs analysis information based on image movement, for example, an image analysis system to display, an image analysis method, an image analysis program, and an ultrasonic diagnostic apparatus, and more specifically, image movement such as an ultrasonic image Image analysis system that acquires and outputs analysis information based on (displacement), for example, when it is displayed, improves stability while maintaining responsiveness, an image analysis method, an image analysis program that executes the image analysis method, and The present invention relates to an ultrasonic diagnostic apparatus including an image analysis system or an image analysis program.

Conventionally, continuous images are input, their movements are analyzed, and analysis results are displayed.
In particular, there is a technique called elastography in ultrasonic medical equipment such as an ultrasonic diagnostic apparatus and system. In elastography, first, an image is acquired while pressing and shaking a living body with a probe. Then, the motion (displacement) between the acquired images is sequentially calculated, and various estimated values related to tissue elasticity are calculated by differentiating the displacement, and these are continuously displayed.

However, for example, when the probe is shaken by the hand of an inspection engineer (operator), the fluctuation width is not always constant. On the other hand, since the estimated tissue elasticity is obtained from the differential of the amount of displacement, there is a drawback that the tissue elasticity may not be calculated correctly especially when the swing width is small.
Further, since the elastic image is acquired by shaking the probe, it is necessary to always move the hand, and since the display always fluctuates, there is a drawback that it is difficult to observe the image.
For this reason, various attempts have been made in the past to eliminate these drawbacks (see Patent Documents 1, 2, and 3).

In Patent Document 1, in order to deal with the above-described drawbacks, in particular, the tissue elasticity may not be calculated correctly, the distortion of each position of the target tissue based on a plurality of RF signal frame data of the target tissue of the subject. Alternatively, in the ultrasonic diagnostic apparatus that generates elastic frame data by calculating the elastic modulus and generates and displays an elastic image from the elastic frame data, the reliability of the elastic frame data is evaluated, and the evaluation result Accordingly, a technique for adjusting the addition of a plurality of elastic frame data is proposed. And in patent document 1, this addition adjustment is performed by changing a weighting coefficient or changing the number of frames of elastic frame data when averaging a plurality of elastic frame (image) data. Has been done.
Thus, in Patent Document 1, an optimal elasticity image can be displayed according to the reliability evaluation result.

Further, in Patent Document 2, in order to deal with the above-described drawbacks, the RF signal frame data of the tomographic part of the subject is generated, and the measurement points of the tomographic part are determined based on a pair of RF signal frame data having different acquisition times. Generate elasticity information frame data representing the degree of tissue hardness or softness, and for each elasticity information of each measurement point of the generated elasticity frame data, elasticity information of multiple measurement points including adjacent measurement points Ultrasound that performs weighting according to the steepness of the distribution of the image, smoothes the elasticity information of the plurality of weighted elastic frame data, generates an elastic image based on the smoothed elastic frame data, and displays it on the display A diagnostic device is disclosed. In Patent Document 2, this weighting is performed by binarizing the steepness of the distribution of the elasticity information based on a predetermined threshold value to detect a noise area of the elasticity frame data, and the elasticity information of the detected noise area is obtained. Is done by removing.
In Patent Document 2, it is possible to improve the image quality of an elastic image obtained by smoothing a plurality of elastic frame data having different generation times, excluding information (noise) other than tissue displacement information.

On the other hand, in Patent Document 3, in order to cope with the above-described drawbacks, particularly, the difficulty of observing images, the displacement of the tissue on the tomographic plane is measured based on the RF signal frame data of the tissue on the tomographic plane of the subject. Displacement frame data is generated, and elastic images are generated based on the elastic frame data generated by calculating elasticity information representing the hardness or softness of the tissue on the tomographic plane based on the generated displacement frame data. In the ultrasonic diagnostic apparatus to be displayed, a plurality of elastic images are stored, and the tomographic plane of the subject is based on at least one of the displacement frame data, the elastic frame data, and the pressure applied to the tissue of the tomographic plane of the subject. We propose a technique for calculating and detecting an appropriate compression cycle of the tissue and selecting and displaying an appropriate one from the stored elasticity image based on the compression cycle.
Thus, Patent Document 3 states that an elastic image suitable for diagnosis can be selected and provided in consideration of the compressed state of the tissue on the tomographic plane of the subject.

Japanese Patent No. 4898809 Republished WO2009 / 104525 JP 2011-120614 A

  However, the technique disclosed in Patent Document 1 attempts to display an elasticity image by adjusting an addition coefficient according to reliability or displacement, but it is difficult to improve accuracy because an average is obtained for the elasticity data after differentiation. There was a problem. Further, in the technique of Patent Document 1, since weighting is average even if there is weighting, there remains a problem that if the average number is increased aiming at low noise, the responsiveness deteriorates. Furthermore, in the technique of Patent Document 1, since it is necessary to always store a plurality of elastic images, there is a problem that memory consumption increases. Further, the technique of Patent Document 1 has a problem that even if an elastic image is stopped when there is no movement, it cannot cope after the average number of frames has elapsed.

  In the technique disclosed in Patent Document 2, the weighting when averaging is basically changed in accordance with the steepness of the distribution of elastic information such as displacement, and the weighting is performed with the steepness of the distribution of elastic information such as displacement. This is done by removing the noise as a noise, but by using the steepness, the noise mixed in the elastic information can be reduced by removing the influence of the suddenly moving (isolated) point. There is a problem that the accuracy of elasticity information is not directly improved. Further, in the technique of Patent Document 2, as in the technique of Patent Document 1, when the number of frames for averaging is increased, there is a problem that responsiveness deteriorates and memory consumption increases.

On the other hand, the technique disclosed in Patent Document 3 requires the user to freeze (stop) the shooting once and to check whether the selected frame is really appropriate. For this reason, it is difficult for the technique of Patent Document 3 to perform these procedures in parallel during the compression operation, and the two steps of compression operation → device operation, and if necessary, three steps of compression operation → device operation → recompression operation. There was a problem that is required.
Moreover, in the technique of Patent Document 3, there is a problem that if the selected elastic image is inappropriate, another appropriate frame is searched for and selected again, or elastography imaging is required again. Therefore, the technique of Patent Document 3 has a problem that it cannot be said that convenience is sufficiently improved. Furthermore, since the technique disclosed in Patent Document 3 must store a plurality of elastic images without fail, there is a problem that memory consumption increases according to the number of storage frames.

In view of the above-described problems of the prior art, the present invention can maintain the responsiveness while improving the stability of analysis information with respect to a change in image motion, and is suitable for a user in a natural procedure. To provide an image analysis system, an image analysis method, an image analysis program, and an ultrasonic diagnostic apparatus capable of presenting analysis information, for example, an image thereof, and further reducing the memory consumption as much as possible. It is aimed.
That is, a first object of the present invention is to provide a technique for stably outputting, for example, displaying analysis information based on image motion. In addition, a second object of the present invention is to provide a technique for maintaining responsiveness to movement at that time. A third object of the present invention is to provide a technique for presenting appropriate analysis information, for example, an image thereof, to a user in a natural procedure. In addition, a fourth object of the present invention is to provide a technique for reducing the memory consumption as much as possible in realizing it.

  In order to achieve the first to fourth objects, the image analysis system according to the first aspect of the present invention is input by an image input unit that inputs a plurality of continuous images of an object and an image input unit. Displacement calculation unit that calculates the displacement amount for each position of the object by sequentially analyzing the displacement between adjacent images of multiple images, and update the displacement amount accumulated value using the displacement amount calculated by the displacement amount calculation unit A cumulative value updating unit that outputs the displacement amount cumulative value updated by the cumulative value update unit as it is or after converting it to an output image or other physical quantity, and updating the displacement amount cumulative value according to the displacement amount And an update degree control unit for controlling the degree.

  In order to achieve the first to fourth objects, an image analysis method according to the second aspect of the present invention includes an input step of inputting a plurality of continuous images of an object, and a plurality of inputs input in the input step. A calculation step for calculating the displacement amount for each position of the object by sequentially analyzing the displacement between adjacent images of the image, and a control step for controlling the update degree of the displacement amount cumulative value according to the displacement amount calculated in the calculation step And an accumulation step for updating the displacement amount accumulated value using the displacement amount and the update degree of the displacement amount accumulated value controlled in the control step, and the displacement amount accumulated value updated in the accumulation step as it is or in an output image or other An output step of converting the physical quantity into a physical quantity and outputting the physical quantity.

In order to achieve the first to fourth objects, an image analysis program according to a third aspect of the present invention includes a procedure for inputting a plurality of continuous images of an object, and a plurality of images input in the input procedure. A procedure for sequentially analyzing the displacement between adjacent images and calculating the displacement amount for each position of the object, a procedure for controlling the update degree of the displacement amount accumulated value according to the displacement amount calculated in the calculation procedure, and the displacement A procedure for updating the displacement amount accumulated value using the amount and the update degree controlled by the control procedure, and a procedure for outputting the displacement amount accumulated value updated by the accumulation procedure as it is or by converting it to an output image or another physical quantity. Is an image analysis program for causing a computer to execute.
In order to achieve the first to fourth objects, a recording medium according to a fourth aspect of the present invention is a computer-readable recording medium recording the image analysis program according to the third aspect.

Here, in each of the above aspects, the update degree control unit is configured such that when the displacement amount is small, the update amount of the displacement amount cumulative value is small, and when the displacement amount is large, the update degree of the displacement amount cumulative value is also large. It is preferable to control so that it becomes.
Moreover, it is preferable that an output part has a 1st image conversion part which converts a displacement amount accumulated value into an output image, and a display part which displays the output image converted by the 1st image conversion part.
When the first threshold value of the displacement amount and the lower limit value of the update degree are set, the update degree control unit sets the update degree to the lower limit value when the displacement amount is smaller than the first threshold value. Is preferred.
Moreover, it is preferable that an update degree control part has a 1st setting part which sets the 1st threshold value of displacement amount, and the lower limit of an update degree previously.

When the second threshold value of the displacement amount and the upper limit value of the update degree are set, the update degree control unit sets the update degree to the upper limit value when the displacement amount is larger than the second threshold value. Is preferred.
Moreover, it is preferable that an update degree control part has a 2nd setting part which sets the 2nd threshold value of a displacement amount, and the upper limit of an update degree previously.
In addition, it is preferable that the accumulated value updating unit uses the displacement amount with the same sign or the absolute value of the displacement amount when updating the displacement amount accumulated value.
The displacement amount calculation unit further includes a reliability evaluation unit that evaluates the reliability of the displacement amount, and the update degree control unit sets the reliability of the displacement amount evaluated by the reliability evaluation unit to the update degree. It is preferable to take into account.
Further, the displacement amount calculation unit further includes a continuity determination unit that determines whether adjacent images are in a continuous relationship, and the update degree control unit has a determination result by the continuity determination unit that is not a continuous relationship. In this case, it is preferable to reset the accumulated displacement amount.

In addition, the cumulative value updating unit calculates a sum of a value obtained by multiplying the displacement amount cumulative value updated last time by the first coefficient and a value obtained by multiplying the displacement amount calculated this time by the second coefficient, as a new displacement amount cumulative value. And
The update degree control unit is configured such that when the displacement amount is small, the second coefficient is relatively small with respect to the first coefficient, and when the displacement amount is large, the second coefficient is relatively large with respect to the first coefficient, It is preferable to control the second coefficient and the first coefficient in accordance with the amount of displacement.
The cumulative value update unit further includes an elastic relationship value calculation unit that calculates the strain or elasticity relationship value by differentiating the amount of displacement, and the output unit calculates the strain or elasticity relationship calculated by the elasticity relationship value calculation unit. It is preferable to have a second image conversion unit that converts a value into an output image, and a display unit that displays an output image converted by the second image conversion unit.

  In order to achieve the first to fourth objects, an ultrasonic diagnostic apparatus according to a fifth aspect of the present invention includes the image analysis system according to the first aspect or the image analysis program according to the third aspect. It is characterized by that.

According to the present invention, as is clear from the above-described aspects and embodiments described later, since the motion of the image is calculated based on the accumulated displacement amount, the first object of the present invention is stably achieved. For example, a technique for outputting analysis information, for example, displaying an image can be provided. That is, in the present invention, since it is based on the accumulation of the displacement amount, there is no undisplayed area because there is no movement, and since the displacement data before differentiation is accumulated, it is easy to improve accuracy.
Further, according to the present invention, by controlling the update degree of the displacement amount cumulative value based on the displacement amount, the responsiveness to movement, which is the second object of the present invention, can be maintained. That is, in the present invention, when the movement is fast, the tracking speed is automatically increased, so that the response is good.

In addition, according to the present invention, since the follow-up is slowed by slowing down the movement, and the accumulated displacement value up to that point is maintained without being attenuated by stopping, the third object of the present invention is achieved. Appropriate analysis information, for example, the image can be presented to the user in a natural procedure. That is, in the present invention, since the frame interval is closest, the calculation accuracy does not drop, and when stopping the motion, the image stops naturally without any time limit, so that it can be observed slowly without the need for another operation.
In addition, according to the present invention, any of the above can be calculated by using a work area for two frames of the displacement amount cumulative value and the latest displacement amount, and therefore, a memory for implementation, which is the fourth object of the present invention. It can be provided as a technology to reduce consumption. That is, according to the present invention, the additional memory usage is only one accumulated frame image.

1 is a block diagram conceptually showing an example of the configuration of an ultrasonic diagnostic apparatus having an image analysis system according to the present invention. 1 is a block diagram conceptually showing an example of the configuration of an image analysis system according to the present invention. It is a flowchart which shows notionally an example of the image analysis method implemented with the image analysis system shown in FIG. It is explanatory drawing which illustrates typically the elastography system comprised in the ultrasound diagnosing device shown in FIG. (A), (b), and (c) are explanatory drawings for explaining the state of the probe with respect to the living body in the elastography system shown in FIG. 4, respectively. (D), (e), and (f) are ( It is an example of the conventional elastic image display displayed on a monitor corresponding to a), (b), and (c), (g), (h), and (i) are (a), (b), respectively. It is an example of the elastic image display of this invention displayed on a monitor corresponding to (c).

An image analysis system, an image analysis method, an image analysis program, and an ultrasonic diagnostic apparatus according to the present invention will be described below in detail based on preferred embodiments shown in the accompanying drawings.
FIG. 1 is a block diagram conceptually showing an embodiment of the configuration of the ultrasonic diagnostic apparatus of the present invention.
As shown in FIG. 1, the ultrasonic diagnostic apparatus 10 includes an ultrasonic probe 12, a transmission unit 14 and a reception unit 16 connected to the ultrasonic probe 12, an A / D conversion unit 18, and a tomographic image generation unit 20. An elastic image generation unit 24, an output control unit 26, a display unit (monitor) 28, a printer 29, a control unit 30, an operation unit 32, and a storage unit 34. The elastic image generation unit 24, the output control unit 26, the display unit 28, and the printer 29 constitute an image analysis system 22 according to the present invention.

The ultrasonic probe 12 has a probe 36 used in a normal ultrasonic diagnostic apparatus.
The probe 36 has a plurality of elements arranged in a one-dimensional or two-dimensional array, that is, ultrasonic transducers. These ultrasonic transducers transmit an ultrasonic beam to a subject in accordance with a drive signal supplied from the transmission unit 14 when an ultrasonic image of an object to be examined (hereinafter referred to as a subject) is captured. Receives ultrasonic echoes from the specimen and outputs a received signal. In the present embodiment, each of a predetermined number of ultrasonic transducers constituting a set of the plurality of ultrasonic transducers of the probe 36 generates each component of one ultrasonic beam, and a set of a predetermined number of ultrasonic transducers. The ultrasonic transducer generates one ultrasonic beam that is transmitted to the subject.

  Each ultrasonic transducer is, for example, a piezoelectric ceramic represented by PZT (lead zirconate titanate), a polymer piezoelectric element represented by PVDF (polyvinylidene fluoride), or PMN-PT (magnesium niobate / lead titanate). It is constituted by an element in which electrodes are formed at both ends of a piezoelectric body made of a piezoelectric single crystal or the like typified by a solid solution, that is, a vibrator. That is, the probe 36 can be referred to as a transducer array in which a plurality of transducers are arranged in a one-dimensional or two-dimensional array as a plurality of ultrasonic elements.

  When a pulsed or continuous wave voltage is applied to the electrodes of such a vibrator, the piezoelectric material expands and contracts, and pulse or continuous wave ultrasonic waves are generated from the respective vibrators, and the synthesis of these ultrasonic waves. As a result, an ultrasonic beam is formed. In addition, each transducer generates an electric signal by expanding and contracting by receiving propagating ultrasonic waves, and these electric signals are output as ultrasonic reception signals.

  The transmission unit 14 includes, for example, a plurality of pulsars, and according to the sound speed or the distribution of sound speeds set based on the transmission delay pattern selected according to the control signal from the control unit 30, one of the probes 36. A plurality of sets formed by adjusting the delay amount of each drive signal so that ultrasonic beam components transmitted from a predetermined number of ultrasonic transducers (hereinafter referred to as ultrasonic elements) form one ultrasonic beam. To the ultrasonic element.

The receiving unit 16 receives, from the subject, an ultrasonic echo generated by the interaction between the ultrasonic beam and the subject by each ultrasonic element of the probe 36 in accordance with a control signal from the control unit 30. Then, the reception signal, that is, the analog element signal for each ultrasonic element is amplified and output, and the amplified analog element signal is supplied to the A / D converter 18.
The A / D converter 18 is connected to the receiver 16 and converts the analog element signal supplied from the receiver 16 into digital element data. The A / D converter 18 supplies the A / D converted digital element data to the tomographic image generator 20.

The tomographic image generation unit 20 generates a sound ray signal (reception data) from the element data supplied from the A / D conversion unit 18 under the control of the control unit 30, and generates an ultrasonic image from the sound ray signal. Is.
The tomographic image generation unit 20 includes a phasing addition unit 38, a detection processing unit 40, a DSC 42, an image creation unit 44, and an image memory 46.

The phasing addition unit 38 selects one reception delay pattern from a plurality of reception delay patterns stored in advance according to the reception direction set in the control unit 30, and based on the selected reception delay pattern The reception focus processing is performed by adding the respective delays to the element data in accordance with the set sound speed or the distribution of sound speed. By this reception focus processing, reception data (RF data or sound ray signal: RF signal of ultrasonic echo) in which the focus of the ultrasonic echo is narrowed is generated.
The phasing addition unit 38 supplies the received data to the detection processing unit 40.

The detection processing unit 40 performs an envelope detection process after correcting the attenuation by the distance according to the depth of the reflection position of the ultrasonic wave on the reception data generated by the phasing addition unit 38, or By applying quadrature detection (IQ detection) to improve the S / N ratio as IQ complex number data (hereinafter referred to as IQ data) to reduce noise, the tissue is converted into amplitude information, thereby converting the tissue in the subject. B-mode image data (B-mode amplitude image data), which is tomographic image information relating to the
A DSC (digital scan converter) 48 converts (raster conversion) the B-mode image data generated by the detection processing unit 40 into image data according to a normal television signal scanning method.

The image creation unit 44 performs various necessary image processing such as gradation processing on the B-mode image data input from the DSC 42 to create B-mode image data for use in output such as inspection and display, and then creates The B-mode image data for inspection or display is output to the output control unit 26 for display or stored in the image memory 46.
The image memory 46 temporarily stores the inspection B-mode image data created by the image creation unit 44. The inspection B-mode image data stored in the image memory 46 is read by the output control unit 26 for display on the display unit 28 or for outputting a hard copy image from the printer 29 as necessary.

The image analysis system 22 acquires analysis information based on the movement (displacement) of an image such as an ultrasonic image of a subject tissue, for example, an output image such as a distortion or an elastic relation value, or an elastic image obtained by imaging them. Specifically, the hardness of the tissue of the subject is examined by repeatedly pressing and loosening the probe 12 against the subject to compress and relax the tissue of the subject. This constitutes an elastography system for evaluation (see FIG. 4).
The image analysis system 22 includes an elastic image generation unit 24, an output control unit 26, a display unit 28, and a printer 29.
Here, the elastic image generation unit 24 is the most characteristic part of the present invention, and determines the hardness and softness of the subject tissue based on the IQ data subjected to IQ (orthogonal) detection processing by the detection processing unit 40. An elastic image to be represented is generated, and details thereof will be described later.

The output control unit 26, the display unit 28, and the printer 29 constitute the output unit 58 (see FIG. 2) of the image analysis system 22. As described above, the tomographic image generated by the tomographic image generation unit 20 is used. It is also shared when displaying.
The output control unit 26 causes the display unit 28 to display a tomographic image (ultrasonic image) based on the inspection B-mode image signal subjected to the image processing by the image creation unit 44 of the tomographic image generation unit 20, or an elastic image. The elastic image generated and imaged by the image converting unit 56 (see FIG. 2) of the generating unit 24 is displayed on the display unit 28. Alternatively, the output control unit 26 may display the tomographic image and the elasticity image on the display unit 28 so as to overlap or line up.
The display unit 28 includes, for example, a display such as an LCD, a monitor, and the like. Under the control of the output control unit 26, an ultrasonic image (B-mode image) or an elastic image is displayed, or both are superimposed or arranged. To do.
The printer 29 includes a laser printer, an ink jet printer, and the like, and under the control of the output control unit 26, an ultrasonic image (B-mode image), a displacement amount (displacement amount accumulation value) or an elastic image described later, or Both are overlapped or arranged and output as a hard copy image.

The control unit 30 controls each unit of the ultrasonic diagnostic apparatus 10 based on a command input from the operation unit 32 by the operator.
Here, the control unit 30 provides various information by the operator via the operation unit 32, particularly information necessary for calculating the delay time used in the phasing addition unit 38 of the tomographic image generation unit 20 and the elastic image generation unit 24. When the various information necessary for the process is input, the above-described various information input from the operation unit 32 is converted into the transmission unit 14, the reception unit 16, the tomographic image generation unit 20, as necessary. And the elastic image generation unit 24 and the output control unit 26 of the image analysis system 22.

The operation unit 32 is for an operator to perform an input operation, and can be formed from a keyboard, a mouse, a trackball, a touch panel, and the like.
In addition, the operation unit 32 is used by the operator for various types of information, in particular, a plurality of ultrasonic elements of the probe 36 of the probe 12 used for calculating the delay time described above, the sound speed of the examination target region of the subject, An input device is provided for performing input operations on the focal position of the ultrasonic beam, information on the transmission aperture and reception aperture of the probe 36, and various information on the elastic image generation processing.

The storage unit 34 receives various information input from the operation unit 32, in particular, information on the probe 12, the sound speed, the focal position, the transmission aperture, the reception aperture, and the like, information on the tomographic image and elastic image generation processing, and the like. Information necessary for processing and operation of each unit controlled by the control unit 30 such as the transmission unit 14, the reception unit 16, the tomographic image generation unit 20, the elastic image generation unit 24 of the image analysis system 22, and the output control unit 26, and , Which stores operation programs and processing programs for executing the processes and operations of each unit, and recording media such as hard disks, flexible disks, MO, MT, RAM, CD-ROM, and DVD-ROM can be used. .
In addition, the phasing addition part 38 of the tomographic image generation part 20, the detection process part 40, DSC42, the image creation part 44, each part of the elastic image generation part 24 of the image analysis system 22, and the output control part 26 are CPU, CPU The computer program is composed of operation programs for causing the computer to perform various types of processing.

Embodiment 1

FIG. 2 conceptually shows a block diagram of an example of the configuration of the image analysis system according to the first embodiment of the present invention. FIG. 3 conceptually shows a flowchart of an example of the image analysis method according to the first embodiment implemented by the image analysis system shown in FIG.
Here, the image analysis system 22 of the present invention, in particular, its elastic image generation unit 24 will be described in detail with reference to FIGS.
The image analysis system 22 of the first embodiment shown in FIG. 2 is incorporated in the ultrasonic diagnostic apparatus 10 of the present invention and is used for ultrasonic image capturing and diagnosis. However, the present invention is not limited to this. Instead, it may be independent from the ultrasonic diagnostic apparatus 10 of the present invention, and can be applied to any apparatus that acquires and outputs analysis information based on image motion. For example, the image analysis system of the present invention can be applied to an X battle moving image capturing apparatus, a photoacoustic imaging apparatus, and the like, and can be used for X battle moving image capturing, photoacoustic imaging, and the like.

The image analysis system 22 of the present invention is incorporated in the ultrasonic diagnostic apparatus 10 shown in FIG. 1, and constitutes an elastography system shown in FIG. As shown in FIG. 2, the image analysis system 22 includes an image input unit 48, a displacement amount calculation unit 50, an update degree control unit 52, a cumulative value update unit 54, an image conversion unit 56, and an output control unit 26. A display unit 28, a printer 29, and a memory 60.
Here, the image input unit 48, the displacement amount calculation unit 50, the update degree control unit 52, the cumulative value update unit 54, and the image conversion unit 56 constitute the elastic image generation unit 24, and the image conversion unit 56. The output control unit 26, the display unit 28, and the printer 29 constitute an output unit 58.

The image input unit 48 shown in FIG. 2 is a part that performs the image data input step S10 shown in FIG. 3, and a plurality of continuous images, preferably different in motion, of the subject (inspection subject) of the subject. Is input. Specifically, the image input unit 48 inputs two images (frame image data A and B) from continuous image data (I), preferably of different motions, into the image analysis system 22. It is for input.
Since the process performed in the image analysis system 22 is a continuous process, a method of sequentially replacing the latest images is desirable. Here, it is preferable that the input two images (frame image data A and B) are stored in the memory 60 so that they can be referred to. Therefore, when the image analysis method shown in FIG. 3 is performed, particularly when the image analysis program executes the image data input step S10, the frame image data of the input images A and B is arranged in the memory 60. It means that it can be referred to.

As in the example shown in FIG. 1, when the image analysis system 22 of the present invention is incorporated in the ultrasonic diagnostic apparatus 10 of the host system as a subsystem, preferably, if the image is different in motion, the image is added to the host system. Only a part of the input image or the image generated by the host system may be captured and regarded as a series of “continuous image data”.
In the following, the processing performed in each unit (component) of the image analysis system 22 is processing in which each corresponding step is performed, and therefore, will be described as processing of each component, and will be described as processing of each step. Is omitted.

Here, in the example illustrated in FIG. 1, the IQ data generated by the detection processing unit 40 of the tomographic image generation unit 20 of the ultrasonic diagnostic apparatus 10 is continuously input to the image input unit 48 of the image analysis system 22. Although it is image data, the present invention is not limited to this, and as shown by a dotted line in FIG. 1, element data that is A / D converted by the A / D converter 18 and input to the tomographic image generator 20 is used. It may be RF data that is phased and added by the phasing addition unit 38 of the tomographic image generation unit 20 and input to the detection processing unit 40, or the B mode output from the detection processing unit 40 It may be image data, or inspection or output B-mode image data output from the image creation unit 44.
Note that IQ data, element data, RF data, and various B-mode image data, which are preferably continuous image data with different motions, are temporarily stored in the external memory or the image memory 46 outside the image analysis system 22. In this case, two continuous image data (A, B) may be read from the external memory or the image memory 46 and input to the image input unit 48.

The displacement amount calculation unit 50 is a part that performs the displacement amount calculation step S12 shown in FIG. 3, and sequentially inputs displacements between adjacent images of a plurality of images, preferably different in motion, input by the image input unit 48. The amount of displacement for each position of the object is calculated by analysis. Specifically, the displacement amount calculation unit 50 is for calculating a displacement amount (displacement amount data f) between the two images A and B input to the image input unit 48. That is, the two images A and B are aligned.
The image alignment method is not particularly limited, and various alignment methods including a conventionally known image alignment method can be used. Examples of the image alignment method include a method of tracking corresponding points for each image position, for example, each pixel (pixel), using a block matching method, a gradient method, or the like. Note that the block matching method divides an image into, for example, blocks of N × N pixels, focuses on blocks in the region of interest of the current frame, and searches for the block closest to the block of interest from the previous frame. Then, a process for calculating the amount of displacement is performed by obtaining the difference with reference to these. Since these methods are well-known in various documents, description thereof is omitted here.
Note that the displacement amount calculated by the displacement amount calculation unit 50 in this manner is preferably stored in the memory 60 as displacement amount data f in which the displacement amount for each pixel corresponding to the image frame is recorded.
The displacement amount calculation unit 50 is preferably provided with a reliability evaluation unit 62 and a continuity evaluation unit 64. The reliability evaluation unit 62 and the continuity evaluation unit 64 will be described later as Embodiments 2 and 3 of the present invention.

The update degree control unit 52 is a part that performs the update degree control step S14 shown in FIG. 3, and the displacement amount cumulative value that is updated by the cumulative value update unit 54 in accordance with the displacement amount calculated by the displacement amount calculation unit 50. The degree of update is controlled. Specifically, the update degree control unit 52 is for controlling the update degree α of the displacement amount cumulative value according to the displacement amount calculated by the displacement amount calculation unit 50. That is, the update degree control unit 52 sets the update degree α controlled according to the calculated displacement amount.
In order to determine the update degree α, the update degree control unit 52 first calculates a representative displacement amount V for each frame. The representative displacement amount V may be an average of the entire image, or may be an average of a specific area such as the image edge or the center of the image. Of course, other statistics such as the median may be used instead of the average.

The update degree α can be expressed by the following formula (1), for example, when t is time (time) and the reference amount is S.
α (t) = | V (t) | / S (1)
Here, the reference amount S is for normalizing the update degree α (t). In the present invention, when the update degree α (t) is normalized to 0 to 1, by experiment or the like, for example, the maximum value of | V (t) | / S is 1 or close to 1. The reference amount S is preferably set so as not to exceed 1. At the same time, it is preferable to set the reference amount S so that the minimum value of | V (t) | / S becomes 0, or close to 0 and not smaller than 0.
In this way, by setting the update degree α (t), when the movement (displacement) is large, the latest frame displacement information, that is, the displacement amount is heavier or larger than the displacement amount accumulated value so far. When the movement (displacement) is small, the latest information on the displacement of the frame, that is, the displacement amount can be reflected lightly or small with respect to the accumulated displacement amount value so far.

By the way, in the case where the tissue of the subject is hard, or when the swing of the probe 12 by the laboratory technician (operator) is small or stopped, it hardly moves. The lower limit threshold value S0 of the displacement amount for incorporating the update degree α (t) into the displacement amount accumulated value with respect to the reference value S1, and the lower limit value of the update degree α (t) is set to 0 by the following formula (2) May be represented.
α (t) = 0 if | V (t) | <S0
= (| V (t) | −S0) / S1 if | V (t) | ≧ S0 (2)
On the other hand, in consideration of when the movement is intense, an upper limit threshold value S2 of the displacement amount that incorporates the update degree α (t) into the displacement amount accumulated value is provided, the upper limit value of the update degree α (t) is set to 1, and the upper limit value S2 May be represented by the following formula (3).
α (t) = (| V (t) |) / S2 if | V (t) | <S2
= 1 if | V (t) | ≧ S2 (3)
In addition, when it is considered that the displacement calculation is not successful when the representative displacement amount V exceeds a certain upper limit value, a mechanism for reducing α can be combined.
The lower limit value and the upper limit value of the update degree α are set to 0 and 1, respectively, but are not limited to this.
It is preferable that the lower limit threshold and the upper limit threshold of the displacement amount and the lower limit value and the upper limit value of the update degree α are set by the setting unit 66 in the update degree control unit 52. These values may be stored in the internal memory 60 of the image analysis system 22, an external memory or the like, and may be set by calling the setting unit 66 as necessary. You may make it input from.

Alternatively, in the present invention, the reference value S may be determined dynamically. For example, by setting the reference value S (t) as in the following formula (4), the maximum displacement amount can be set in the reference value S. In particular, the update degree α (t) is set in the following formula (5). The displacement amount based on the past maximum displacement amount can be maintained.
S (t) = max {V (t)} (4)
α (t) = 1 if | V (t) | ≧ S (t)
= 0 if | V (t) | <S (t) (5)
In the above description, the update degree α (t) is a uniform value for the image. However, the image is divided into a plurality of segments n (n is an integer of 2 or more), and the update degree α (n , T), or in particular, the update degree α (x, y, t) for each pixel. In these cases, the representative displacement amount V may be set for each segment or pixel.

The cumulative value update unit 54 performs the cumulative value update step S <b> 16 shown in FIG. 3, and uses the update degree controlled by the update degree control unit 52 and the displacement amount calculated by the displacement amount calculation unit 50. The accumulated displacement value is updated. Specifically, the accumulated value update unit 54 uses the update degree α controlled by the update degree control unit 52 and the displacement amount f calculated by the displacement amount calculation unit 50 to update the displacement amount accumulated value F. belongs to.
That is, when the segment or pixel position of the image is represented by xy two-dimensional coordinates, and time (time) is represented by t, the displacement amount accumulated value is F (x, y, t), and the displacement amount is f (x, y, t). Since the update degree is represented by α (t), the displacement amount accumulated value F (x, y, t) can be updated according to the following formula (6).
F (x, y, t) = {1-α (t)} · F (x, y, t−1)
+ Α (t) · | f (x, y, t) | (6)
Here, F (x, y, t) represents the displacement amount accumulated value updated this time, f (x, y, t) represents the displacement amount calculated this time, and F (x, y, t). -1) represents the displacement amount cumulative value updated this time.

  In the above equation (6), since the update degree α (t) is normalized, the sum of the coefficients of F (x, y, t−1) and | f (x, y, t) | Is adjusted to be 1. For this reason, when the displacement amount f (x, y, t) calculated this time is small and the representative displacement amount V is small, the update degree α (t) is controlled to be small, so | f (x, y , T) | the coefficient α (t) is updated by the update degree control unit 52 so as to be relatively smaller than the coefficient {1-α (t)} of the coefficient F (x, y, t−1). Will be controlled. On the other hand, when the displacement amount f (x, y, t) is large and the representative displacement amount V is large, the update degree α (t) is controlled to be large, so that | f (x, y, t) | The update degree control unit 52 controls the coefficient α (t) so as to be relatively larger than the coefficient {1-α (t)} of the coefficient F (x, y, t−1). Become.

The cumulative value update unit 54 is not limited to updating the displacement amount cumulative value F according to the above equation (6), and may update the displacement amount cumulative value F according to the above equation (7).
F (x, y, t) = C1 · F (x, y, t−1)
+ C2 · | f (x, y, t) | (7)
In the above equation (7), when the representative displacement amount V is small, the coefficient C2 is relatively small with respect to the coefficient C1, and when the representative displacement amount V is large, the coefficient C2 is relatively large with respect to the coefficient C1. Thus, the coefficient C1 and the coefficient C2 are preferably controlled by the update degree control unit 52 in accordance with the representative displacement amount V.

However, by fixing one side of the above formulas (6) and (7), for example, in the above formula (7), C1 is fixed at 1 and C2 is set to α (t). For example, (x, y, t) can be changed to the following equation (8).
F (x, y, t) = F (x, y, t−1)
+ Α (t) · | f (x, y, t) | (8)
In the present invention, “relative magnitude” means, for example, in the above formula (8), relative to α for a certain representative displacement amount V relative to α for another representative displacement amount V having a different magnitude. Needless to say, the size is a problem and does not necessarily mean “α> 1” or “α <1”.
Further, since the position (pixel position, etc.) of the displacement amount cumulative value F moves for each frame, the above equation (6) is changed into the following equation (9) with reference to the calculation result of the displacement amount calculation unit 50. May be represented.
F (x, y, t) = {1-α (t)} · F (x ′, y ′, t−1)
+ Α (t) · | f (x, y, t) | (9)
Here, x ′ represents the position of x before movement, and y ′ represents the position of y before movement.

Here, the reason for performing the update degree control and the displacement amount accumulated value update in the present invention, that is, the update degree control step S14 by the update degree control unit 52 and the accumulated value update step S16 by the cumulative value update unit 54 described above. The significance will be explained in detail.
The present invention is proposed for a system for observing the amount of displacement.
First, as a measure for improving the S / N ratio of observation values at a single time, it is conceivable to accumulate observation values. The simplest formula is a simple summation (integration). That is, when f (t) is a measured value at time t and F (t) is a cumulative value at time t, the following equation (10) is obtained.
F (t) = F (t-1) + f (t) (10)

In this way, the S / N ratio can be improved by handling F (t) as a culmination of a large number of observation results instead of f (t) at a single time.
However, if f (t) is simply integrated as described above, when f (t) = v (t) is set for both v (t) of the image as in this case, for example, In the analysis in which the image fluctuates up and down, the expected value of F (t) becomes zero, and the efficiency of improving the S / N ratio deteriorates. That is, the sign of f (t) is reversed in the middle, so that the sum of motion finally converges near zero.

Therefore, in the present invention, for example, f (t) = | v (t) | (or f (t) = v (t) if v (t) ≧ 0, f (t) = 0 if v (t) <0, etc.) is proposed to propose to maintain the efficiency of S / N improvement by estimating the net motion amount of the image. It is.
However, these equations are not sufficient. In other words, the responsiveness gradually deteriorates with the passage of time, especially in a computer system that can store only a finite value, there is a risk that F (t) may diverge, so the observation time becomes longer than a certain degree. It is not practical in the system to obtain.

For this reason, a cumulative system generally known as a type of IIR can be substituted as shown in the following formula (11).
F (t) = (1−α) · F (t−1) + α · f (t) (11)
Here, “α” is an update rate. However, it is known that if α is fixed statically, it may not be able to cope with dynamic observation fluctuations. For example, if α is set small, the stability of the output is improved, but the response is deteriorated instead. Conversely, if α is set large, the responsiveness improves, but the stability deteriorates. Also, when there is no particular movement, F (t) decays with time.

Therefore, there is a technique called “adaptive filter” that controls “α” by an analytical method. That is, α is made variable according to time and improved as shown in the following formula (12).
F (t) = {1−α (t)} · F (t−1) + α (t) · f (t) (12)
Here, there are various studies on how to determine the “α (t)” of the adaptive filter. For example, a method of analytically determining the error by minimizing the error by applying a model formula is known.
The present invention proposes one of the above-mentioned “adaptive filters”, which is one result of such research, and that is simple and good for image processing for motion analysis. Is. That is, by setting a large “α” for a large fluctuation that can be expected to have a good output, it is possible to improve the responsiveness expected by the user without losing stability. Also, for small fluctuations that the user would rather not expect responsiveness, by setting a small “α”, stability can be improved and attenuation of F (t) can be prevented. .

As described above, it is one of the proposals of the present invention to obtain good F (t) by limiting the sign of v (t) input to f (t).
In addition, for example, the following formula (13) shown in the present embodiment is characterized in that α (t) = 0 automatically when v (t) = 0. T is a reference value for normalization.
α (t) = | v (t) | / T (if | v (t) | <T),
1 (if | v (t) | ≧ T) (13)
That is, at this time, the following equation (14) is obtained, and F (t) is not attenuated, and the previous value is held.
F (t) = {1−α (t)} · F (t−1) + α (t) · f (t)
= F (t-1) (14)

That is, when the movement is stopped, the accumulated value up to that point will be saved, so for example, when observation is performed while giving external movement, the image is displayed by stopping the external movement. You can stop. In other words, after a good image is obtained by applying an external motion, the external image is slowly stopped so that the good image can be observed calmly without giving a new new operation. It becomes. Therefore, according to the present invention, a method for easily obtaining an appropriate image by a natural operation is presented to the user.
Although the above shows an example of a proposed adaptive filter as an extension of a simple IIR, an image change with respect to “v” can be applied to other various filters and the like based on the essential configuration of the present invention. It is also possible to easily construct a mechanism for controlling
In the present invention, the update degree control unit 52 and the update degree control step S14, and the cumulative value update unit 54 and the accumulated value update step S16 are configured as described above.

Subsequently, the image conversion unit 56 constituting the output unit 58 is a part that performs the image conversion step S18 shown in FIG. 3 and converts the displacement amount cumulative value updated by the cumulative value update unit 54 into an output image. Is. Specifically, the image conversion unit 56 converts the displacement amount accumulated value (cumulative value data) F updated by the accumulated value update unit 54 into an image by converting it into another physical quantity as it is, and displays it on the output unit 58. This is for conversion into a converted image, such as an elastic image, for output to the monitor of the unit 28 or the printer 29.
In the image conversion unit 56, for example, a color image is formed by changing the color spectrally so that a place where the displacement amount accumulated value F (x, y, t) is large is “red” and a small place is “blue”. Also good.
Further, as a conversion process in the image conversion unit 56, an elastic relation value calculation unit 68 may be provided inside the image conversion unit 56, and another physical quantity may be obtained once from the displacement amount accumulated value F. For example, in the case of deformed images of the same photographed object, the elastic relationship value calculation unit 68 may differentiate the displacement amount accumulated value F into a strain and convert it into a tissue elasticity relationship value. Thereafter, such an elastic relation value may be converted into a color image to be finally displayed using a lookup table (LUT) or the like.
The elastic relationship value calculation unit 68 may be provided not in the image conversion unit 56 but in the previous stage of the image conversion unit 56, for example, in the cumulative value update unit 54.

The display unit 28 constituting the output unit 58 is a part that performs the image display step S20 shown in FIG. 3, and displays an output image such as an elastic image converted by the image conversion unit 56. Specifically, the display unit 28 displays image data of a converted image such as an elastic image converted by the image conversion unit 56 into display image data after the output control unit 26 converts the image data, for example, on a display or a monitor. Is for.
The printer 29 constituting the output unit 58 converts the image data of the converted image such as an elastic image converted by the image conversion unit 56 into hard copy image data after the output control unit 26 converts the image data into a hard copy image data, and outputs the hard copy image data. Is for.
An output image such as an elastic image may be displayed on the display unit 28, output from the printer 29, or both.
In the display unit 28 and the printer 29, the image data of the output image such as an elastic image may be regarded as a numerical value and output in text or table format, or the displacement accumulated value F updated by the accumulated value updating unit 54 may be output. The numerical value itself may be output as it is in text or table format without being imaged by the image conversion unit 56.

The memory 60 stores data used in the image analysis system 22 according to the first embodiment, generated data, and the like so as to be readable. As data stored in the memory 60, for example, a plurality of input image data I, preferably different in motion, such as IQ data, RF data, B-mode image data, or element data input to the image input unit 48, Image data A and B selected from the input image data I, preferably having different motions, displacement amount data f calculated by the displacement amount calculation unit 50, and setting values set in the setting unit 66 of the update degree control unit 52 For example, the upper limit threshold and lower limit threshold of the displacement amount, the upper limit value and lower limit value of the update degree α, the reference values S, S1, etc., the displacement amount accumulated value F updated by the accumulated value update unit 54, and converted by the image conversion unit 56 Each part of the image analysis system 22 such as the converted image (image data), the distortion calculated by the internal elasticity relation value calculation unit 68, the elasticity relation value, the elasticity image obtained by converting them into an image, and the like. It can be mentioned various kinds of control data required for controlling the steps performed.
Of course, various types of data stored in the memory 60 are read out to each part of the image analysis system 22 as necessary.
The image analysis system 22 according to the first embodiment of the present invention is basically configured as described above.

Embodiment 2

Since an accumulation system such as the image analysis system 22 of the first embodiment affects the entire subsequent time, it is preferable that unreliable values are not mixed in.
Therefore, in the second embodiment, it is preferable to provide the reliability evaluation unit 62 in the displacement amount calculation unit 50, evaluate the reliability in the displacement amount calculation in the displacement amount calculation step S12, and exclude unreliable values. .
In the displacement amount calculation of the displacement amount calculation unit 50 (displacement amount calculation step S12), for example, when the block matching method is used, “probability” for a plurality of displacement amount candidates is obtained for each pixel, and the numerical value is obtained. The place where is the highest is the amount of displacement. Therefore, the “probability” is regarded as the reliability R, and is referred to in the update degree control unit 52. For example, if the reliability R is smaller than a set threshold value, α is set to a predetermined lower limit value, for example, 0. You may do it.
Further, for example, in the case of a B-mode image, the luminance for each pixel corresponds to the echo signal (RF signal) intensity, and therefore, for each pixel or for the entire image, a pixel point that is darker than a certain threshold value or an update for an image. You may not make it.

Embodiment 3

A cumulative system such as the image analysis system 22 of the first embodiment is effective when images have continuity.
Therefore, in the third embodiment, a continuity evaluation unit 64 is provided in the displacement amount calculation unit 50, and the continuity of the input adjacent image data A and B is evaluated in the displacement amount calculation in the displacement amount calculation step S12. When there is no continuity, it is preferable to reset the displacement amount accumulated value F (F (x, y, t−1)) of the accumulated value update unit 54.
In the displacement amount calculation of the displacement amount calculation unit 50 (displacement amount calculation step S12), for example, the reliability evaluation unit 62 of the second embodiment determines that the image has no continuity when the reliability R of the entire image is small. The displacement amount accumulated value F may be reset once.
Note that when the displacement amount cumulative value F is reset, the image may be whiteout or blackout. In addition, the image may be gradually faded from whiteout or blackout for a while immediately after the reset including the start-up, not only at the time of resetting the displacement amount accumulated value F. Similarly, it may be gradually faded out when the reliability R decreases.

Embodiment 4

An embodiment of an ultrasonic imaging apparatus in which the ultrasonic diagnostic apparatus 10 shown in FIG. 1 incorporating the image analysis system 22 shown in FIG. 2 is configured as an elastography system will be described with reference to FIG.
As shown in FIG. 4, the elastography system 70 including the ultrasonic diagnostic apparatus 10, that is, the ultrasonic imaging apparatus, has a probe 12 for transmitting and receiving ultrasonic waves, and is continuously in contact with a living body 72. The ultrasonic wave is transmitted and the received signal is acquired. In particular, in the elastography system 70, the ultrasonic wave reception signal of a continuous frame is acquired while the probe 12 is brought into contact with the living body 72 and lightly swung up and down.
The ultrasonic reception signal thus acquired is sent to the processor 74 including the tomographic image generation unit 20, the elastic image generation unit 24, and the output control unit 26 of the ultrasonic diagnostic apparatus 10 shown in FIG. Through processing such as detection, the data is converted into IQ data (IQ complex number data) and B-mode image data obtained by luminance (amplitude) conversion. Since the processing of each part of the processor 74 has been described in detail in the description of the ultrasonic diagnostic apparatus 10 shown in FIG. 1, description thereof is omitted here. Here, for example, it is assumed that B image data is input and stored in the memory 60 and is processed.
In FIG. 4, for example, the living body 72, a digital image of an adjacent frame in the processor 74, and the thin halftone dots of the monitor 28 indicate pixels of the subject tissue, and the dark halftone dots are, for example, hard tissue Let the pixel be shown.

Here, in the elastography of the ultrasonic imaging apparatus incorporating the image analysis system of the present invention, the present frame data (time T = t−1 and T = t) stored in the memory 60 is compared with the present frame data. A processor 74 incorporating the inventive image analysis system performs the processing.
When each step of the image analysis method performed by the image analysis system 22 of the present invention is an image analysis program that can be executed by a computer, the processor 74 stores the image analysis program.
In the processor 74, in the displacement amount calculation unit 50 (displacement amount calculation step S12) of the elastic image generation unit 24, adjacent frame data are compared with each other, and image alignment, that is, a biological tissue site is associated with each pixel of the frame. By calculating the correspondence between adjacent frames, the displacement amount for each part is calculated.
Here, the obtained displacement amount may be further corrected. For example, various noise removal processes such as a median filter and a moving average may be performed, or the displacement amount may be corrected according to, for example, a pressure model.

By the way, conventionally, various processes have been performed after differentiating the obtained displacement amount and converting it into an elastic relation value. However, in the present invention, the accumulated value updating unit of the elastic image generating unit 24 is used. In 54 (cumulative value update step S16), the obtained displacement amount is accumulated to obtain a displacement amount accumulated value. At this time, for example, the update degree control unit 52 (update degree control step S14) of the elastic image generation unit 24 calculates the displacement cumulative value by varying the update degree using the method described in the first embodiment.
In the present invention, the S / N ratio of the output can be efficiently improved by accumulating the displacement amount before the post-stage differentiation that is easily influenced by noise. Further, by adopting adaptation based on the amount of displacement corresponding to the output quality, both stability and responsiveness can be achieved. It should be noted that by accumulating the displacement (velocity) sign limited to one side, a good accumulated displacement amount can be maintained even at the point where the probe motion is vertically inverted.

Next, if the obtained displacement amount accumulated value F is differentiated on each sound ray and normalized by an average value, data (strain) corresponding to the relative tissue elasticity between the parts can be obtained. The reason is that for a uniform compression, the differential amount of the displacement amount at the hard portion is relatively small, and the differential amount of the displacement amount at the soft portion is relatively large. It should be noted that, for example, some deformation can be considered for the elastic relationship value, such as taking the reciprocal or taking the logarithm after taking the ratio, but it is basically a value based on strain.
In elastography, generally, the image conversion unit 56 (image conversion step S18) of the elastic image generation unit 24 finally performs hue conversion on the elastic data and handles the elastic data as a color image. Therefore, in the image display step S20, the color image data generated on the memory 60 is transferred to the display unit 28, that is, a display device such as a monitor, and a visualized tissue elasticity image is displayed. Thus, the moving image of the elastic image that is sequentially generated is confirmed on the monitor.

  Here, as described above, as shown in FIG. 4A, the user makes the probe 12 contact the living body 72 and observes the image while gently shaking up and down. Conventionally, as shown in FIG. As shown in FIG. 4, even if it is thought that a good observation image is obtained on the monitor 28, the observation image is immediately replaced, or as shown in FIGS. 4B and 4C, the probe 12 is replaced. 4e and 4f, the image gradually attenuates or fades out. Therefore, the user temporarily operates the freeze button etc. of the device once to store the stored frame. It was necessary to reconfirm whether the image obtained by calling is appropriate.

  However, according to the present invention, as shown in FIG. 4A, the user can easily obtain a good observation image with high responsiveness as shown in FIG. 4G by shaking the probe 12. When the desired image is obtained, as shown in FIGS. 4 (b) and (c), the probe 12 is simply stopped, and the current monitor 28 is displayed as shown in FIGS. 4 (h) and (i). The displayed image is maintained. At this time, the image does not stop suddenly, but as the movement of the probe 12 slows down, as shown in FIGS. 4 (h) and (i), the change in the image can be gradually reduced. . In addition, the image is not actually frozen, and for example, the movement of the image with respect to breathing or pulsation can be reflected on the monitor 28, so it can be said that the image stops naturally.

Therefore, the user can observe an appropriate image naturally and slowly without the need for additional operation of the device or system. Of course, the desired image currently displayed on the monitor can also be preserve | saved by operating a freeze button etc. after that.
The elastography system 70 of the ultrasonic imaging apparatus incorporating the image analysis system of the present invention is basically configured as described above. For example, a user who is familiar with the conventional method does not want the elastography function. Needless to say, the function and configuration according to the present invention, that is, the elastic image generating unit 24 may be turned on / off.

In the image analysis method according to the present invention, as shown in FIG. 3, first, in the image data input step 10, a plurality of continuous images, preferably different in motion, are input.
Next, in the displacement amount calculation step S12, the displacement amount between adjacent images of the plurality of images input in the input step S10 is sequentially analyzed to calculate the displacement amount for each position of the object.
Next, in the update degree control step S14, the update degree of the displacement amount accumulated value updated in the subsequent displacement amount accumulation step S16 is controlled in accordance with the displacement amount calculated in the calculation step S12.

Next, in the displacement amount accumulation step S16, the displacement amount accumulation value is updated using the displacement amount calculated in the calculation step S12 and the update degree controlled in the control step S14.
Next, in the output step, the displacement amount accumulated value updated in the accumulation step S16 is output as it is or after being converted into an output image or another physical amount.
Specifically, in the image conversion step S18 of the output step, the displacement amount accumulated value updated in the accumulation step S16 is converted into a converted image, and in the image display step S20, the converted image converted in the image conversion step S18. Is displayed on the display unit 28 such as a monitor.
Thus, the image analysis method of the present invention can be implemented.

The algorithm of the image analysis method according to the present invention described above is described in a programming language, compiled as necessary, and the image analysis program is stored in a memory (recording medium) or the like and executed by other information processing means. Then, the same function as the image analysis system according to the present invention can be realized.
That is, the image analysis program of the present invention is a program for causing a computer to execute the following plurality of procedures for image analysis, and the plurality of procedures inputs a plurality of images, preferably continuous images of an object. The procedure, the procedure to calculate the displacement amount for each position of the object by sequentially analyzing the displacement between adjacent images of multiple images input in the input procedure, and the displacement amount according to the displacement amount calculated in the calculation procedure The procedure for controlling the update degree of the accumulated value, the procedure for updating the displacement amount accumulated value using the displacement amount and the update degree controlled by the control procedure, and the displacement amount accumulated value updated by the accumulation procedure as it is or output And a procedure for converting the image into another physical quantity and outputting it.
Needless to say, the present invention may be a computer-readable recording medium on which the image analysis program is recorded.

The image analysis system 22 and the ultrasonic diagnostic apparatus 10 of the present invention are controlled by an image analysis program stored in the memory 60 or a memory (not shown) attached to the control unit 30. That is, an image analysis program is read from the memory by the control unit, and a function of outputting the updated displacement amount accumulated value as it is or after converting it into an output image or another physical quantity is executed according to the image analysis program.
Note that the image analysis program is not limited to the one stored in the built-in memory or the memory attached to the control unit as described above, and the image analysis program is not limited to the image analysis system of the present invention, such as a CD-ROM. The information may be recorded in a memory medium (removable medium) configured to be detachable from the sonic diagnostic apparatus and read into the apparatus via an interface corresponding to the removable medium.

The image analysis system, the ultrasonic diagnostic apparatus incorporating the image analysis method, and the image analysis method according to the present invention have been described in detail above. However, the present invention is not limited to the various embodiments described above, and does not depart from the spirit of the present invention. Of course, various improvements and changes may be made.
For example, each component shown in FIGS. 1 and 2 may be configured as hardware, or may be configured as software executed by a computer or the like.

DESCRIPTION OF SYMBOLS 10 Ultrasonic diagnostic apparatus 12 Ultrasonic probe 14 Transmission part 16 Reception part 18 A / D conversion part 20 Tomographic image generation part 22 Image analysis system 24 Elastic image generation part 26 Output control part 28 Display part (monitor)
DESCRIPTION OF SYMBOLS 29 Printer 30 Control part 32 Operation part 34 Storage part 36 Probe 38 Phased addition part 40 Detection processing part 42 DSC
44 Image creation unit 46 Image memory 48 Image input unit 50 Displacement amount calculation unit 52 Update degree control unit 54 Cumulative value update unit 56 Image conversion unit 58 Output unit 60 Memory 62 Reliability evaluation unit 64 Continuity determination unit 66 Setting unit 68 Elasticity Relation calculation unit 70 Elastography system 72 Living body 74 Processor

Claims (16)

An image input unit for inputting a plurality of continuous images of the object;
A displacement amount calculation unit for sequentially analyzing displacements between adjacent images of the plurality of images input by the image input unit and calculating a displacement amount for each position of the object;
A cumulative value updater that updates a displacement cumulative value using the displacement calculated by the displacement calculator;
An output unit that outputs the displacement accumulated value updated by the accumulated value updating unit as it is or converted into an output image or other physical quantity; and
An image analysis system, comprising: an update degree control unit that controls an update degree of the displacement amount cumulative value according to the displacement amount.   The update degree control unit decreases the update degree of the displacement amount cumulative value when the displacement amount is small, and also increases the update degree of the displacement amount cumulative value when the displacement amount is large. The image analysis system according to claim 1, which is controlled as described above. The output unit is
A first image conversion unit for converting the accumulated displacement amount into the output image;
The image analysis system according to claim 1, further comprising: a display unit that displays the output image converted by the first image conversion unit. When a first threshold value of the displacement amount and a lower limit value of the update degree are set,
The image analysis system according to claim 1, wherein the update degree control unit sets the update degree to the lower limit value when the amount of displacement is smaller than the first threshold value.   The image analysis system according to claim 4, wherein the update degree control unit includes a first setting unit that sets the first threshold value of the displacement amount and the lower limit value of the update degree in advance. When the second threshold value of the displacement amount and the upper limit value of the update degree are set,
The image analysis system according to claim 1, wherein the update degree control unit sets the update degree to the upper limit value when the amount of displacement is larger than the second threshold value.   The image analysis system according to claim 6, wherein the update degree control unit includes a second setting unit that sets the second threshold value of the displacement amount and the upper limit value of the update degree in advance.   The image analysis system according to claim 1, wherein the cumulative value update unit uses the displacement amount having the same sign or the absolute value of the displacement amount when updating the displacement amount cumulative value. The displacement amount calculation unit further includes a reliability evaluation unit that evaluates the reliability of the displacement amount,
The image analysis system according to claim 1, wherein the update degree control unit adds the reliability of the displacement amount evaluated by the reliability evaluation unit to the update degree. The displacement amount calculation unit further includes a continuity determination unit that determines whether the adjacent images are in a continuous relationship,
The image analysis system according to claim 1, wherein the update degree control unit resets the displacement amount cumulative value when a determination result by the continuity determination unit is not a continuous relationship. The cumulative value update unit calculates a sum of a value obtained by multiplying the displacement amount cumulative value updated last time by a first coefficient and a value obtained by multiplying the displacement amount calculated this time by a second coefficient, as a new displacement amount cumulative value. Value,
The update degree control unit reduces the second coefficient relative to the first coefficient when the displacement amount is small, and sets the second coefficient as the first coefficient when the displacement amount is large. The image analysis system according to claim 1, wherein the image analysis system is relatively large and controls the second coefficient and the first coefficient according to the displacement amount. The update degree control unit further includes an elastic relationship value calculation unit that calculates strain or an elastic relationship value by differentiating the accumulated displacement value.
The output unit is
A second image conversion unit that converts the strain or elasticity relationship value calculated by the elasticity relationship value calculation unit into the output image;
The image analysis system according to claim 1, further comprising: a display unit that displays the output image converted by the second image conversion unit. An input step for inputting a plurality of continuous images of the object;
A calculation step of sequentially analyzing displacement between adjacent images of the plurality of images input in the input step to calculate a displacement amount for each position of the object;
A control step of controlling the update degree of the displacement amount cumulative value according to the displacement amount calculated in the calculation step;
A cumulative step of updating a displacement amount cumulative value using the displacement amount and an update degree of the displacement amount cumulative value controlled in the control step;
An image analysis method comprising: an output step of outputting the displacement amount accumulated value updated in the accumulation step as it is or after converting it into an output image or another physical quantity. A procedure for entering multiple consecutive images of the object;
A procedure for sequentially analyzing displacement between adjacent images of the plurality of images input in the input procedure to calculate a displacement amount for each position of the object;
A procedure for controlling the update degree of the displacement amount cumulative value according to the displacement amount calculated in the calculation procedure;
A procedure for updating a displacement amount cumulative value using the displacement amount and the update degree controlled by the control procedure;
An image analysis program for causing a computer to execute the procedure of outputting the displacement amount accumulated value updated in the accumulation procedure as it is or after converting it into an output image or another physical quantity.   A computer-readable recording medium on which the image analysis program according to claim 14 is recorded.   An ultrasonic diagnostic apparatus comprising the image analysis system according to claim 1 or the image analysis program according to claim 14.