JP5368873B2 - Ultrasonic diagnostic equipment - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To reduce a load on a user and also shorten an inspection time when performing each process constituting a routine inspection in an ultrasonic diagnostic apparatus. <P>SOLUTION: It is determined whether a process is the automatic optimizing process or not in S103. When the process is the automatic optimizing process, the automatic optimizing process is performed in S104. In the opposite case, manual setting reception processing is performed in S105. In the automatic optimizing process S104, the values of noted parameters are experimentally changed, while allowing a plurality of parameters to be the noted parameters respectively, and, then, a correlation value is calculated between a current image and a reference image through the change to thereby optimize the values of the noted parameters. Automatic freezing processing is performed at the stage of completion in optimizing or manual-setting concerning the whole parameters. Thus, a still image or an animation is preserved. <P>COPYRIGHT: (C)2011,JPO&amp;INPIT

Description

  The present invention relates to an ultrasonic diagnostic apparatus, and more particularly to a technique for supporting parameter setting necessary in each process constituting an inspection routine.

  An ultrasonic diagnostic apparatus is used in various medical subjects in hospitals. For example, in an ultrasonic examination of the heart, after initial setting or initial registration for an ultrasonic diagnostic apparatus, observation of a short-axis tomogram, observation of a long-axis tomogram, observation of a Doppler waveform, blood flow image (color flow mapping image) Alternatively, a plurality of processes such as observation of a color Doppler image) are executed in order. In general, a routine routine (examination flow) is determined for each examination type, and an examination engineer or an examination doctor sequentially performs a plurality of processes in accordance with the examination routine. In each process, parameters such as gain, contrast, range (observation depth), and focus depth are conventionally manually adjusted so that the image quality is optimal (usually, preset parameter values are manually adjusted). In addition, when recording an image, the freeze button is manually operated, and the displayed image at that time is stored based on the user's instruction. If necessary, the moving image on the cine memory is stored based on the user's instruction. Is equal.

  In the routine routine inspection as described above, in each process, many knobs and switches on the operation panel are operated by the inspector so that the image is optimized. In particular, in the case of an unskilled inspector, the burden on operation is large. There is a strong demand to reduce such a burden and shorten the inspection time as a whole. On the other hand, it is necessary for the examiner to pay attention to the entire state including the contact state of the probe and the facial expression of the subject, and it is particularly important to look at the image. There is a need to proceed with a series of routine inspections without frequently moving the control panel to the operation panel. Furthermore, shortening the examination time is also required from the viewpoint of reducing the burden on the subject.

JP 2000-325345 A JP 2004-290404 A

  Patent Document 1 discloses an ultrasonic diagnostic apparatus in which an operation sequence (operation flow) is registered in advance, and each inspection process is sequentially executed according to the registered operation sequence each time a specific switch unit is operated. It is disclosed. However, it seems that image quality adjustment is not automated in each process, that is, the method described in Patent Document 1 still requires many operations that were conventionally required in each inspection process. Patent Document 2 describes an ultrasonic diagnostic apparatus that displays a reference image and a real-time image side by side. In that case, the correlation coefficient between the reference image and each real-time image is calculated, and the real-time image with the highest correlation coefficient is displayed. However, in order to bring the content of the real-time image closer to the content of the reference image, it has not been done until both the images are compared and the operation parameters such as gain are automatically determined.

  An object of the present invention is to reduce the operation burden on an inspector. Alternatively, an object of the present invention is to shorten the inspection time.

  According to the present invention, in an ultrasonic diagnostic apparatus used in a routine inspection including a plurality of processes including at least one parameter automatic optimization process, the routine inspection is advanced while sequentially receiving next process execution commands input by an inspector. A control unit and a reference image storage unit that stores an image acquired in the past as a reference image in association with the parameter automatic optimization step, and the control unit is configured to perform the parameter automatic optimization step. Optimize at least one automatic optimization target parameter related to the generation of the current image by comparing the current image formed by ultrasonic transmission / reception with the reference image associated with the parameter automatic optimization step And in the parameter automatic optimization step, the parameter group including the parameters to be automatically optimized A storage processing unit that executes save processing of the current image generated after completion of the setting you are, characterized in that it comprises a.

  According to the above configuration, in the routine inspection using the ultrasonic diagnostic apparatus, the routine inspection includes at least one parameter automatic optimization step, in which the automatic optimization is performed by comparing the current image with the reference image. The target parameter is optimized. That is, the value given to the parameter is automatically optimized. Optimization means searching and determining values that satisfy a certain condition. In such parameter optimization, the user is not required to perform a special panel operation, so that the burden on the user can be reduced and the inspection time can be shortened. In addition, since the process of saving the current image can be automatically performed when the parameter group setting is completed, the burden on the user can be reduced and the inspection time can be shortened. Preferably, the current image generated by reflecting the temporary optimization target parameter while reflecting the automatic optimization target parameter is compared with the reference image, based on the similarity between both images, for example, based on the correlation value. The optimum value is searched. When there are a plurality of parameters to be automatically optimized, optimization can be performed sequentially or simultaneously. According to the above configuration, the user can proceed with each process simply by turning on the button for giving the next process execution instruction, so that the inspection time can be considerably shortened as a whole routine inspection. In addition to such buttons, it is desirable to prepare a small number of basic buttons such as a cancel (or return to previous) button and an end button. It is desirable that the reference image is an image determined to be the best acquired in the past. You may make it update it for every routine test | inspection. The reference image may be different for each subject.

  Preferably, the plurality of steps include a plurality of parameter automatic optimization steps, and the reference image storage unit stores a plurality of reference images associated with the plurality of parameter automatic optimization steps. In the parameter automatic optimization step, a plurality of automatic optimization target parameters related to the generation of the current image are optimized.

  Preferably, in each parameter automatic optimization step, among the parameter groups to be set in the step, the input value is preferentially set for the parameter whose value is input by the inspector, and the parameter is automatically optimized. Excluded. According to this configuration, it is possible to respect the user's intention and desire while using automatic processing as a principle. Parameters to be set by the user may be registered in advance, or parameters for which user interrupt processing has been performed may be excluded from the targets for automatic optimization.

  Preferably, a parameter table is provided for managing whether each parameter constituting the parameter group is an automatic optimization target parameter, and the optimization unit refers to the parameter table to refer to the parameter table. Identify the parameters to be optimized automatically from the group.

  Preferably, the storage processing unit includes means for determining a freeze when all the parameter groups are determined, and means for storing the current image in a storage medium when the freeze is determined. Preferably, the current image at the time when the freeze is determined is displayed as a still image on the screen, and the current image is stored when the user confirms the current image. The determination of freeze corresponds to the determination of an image capture instruction or a storage instruction, and the contents of the cine memory or the image memory may be frozen as they are. The current image at the time of freezing may be displayed on the screen as a still image. It is desirable that transmission / reception is stopped at the time of freezing. The freeze timing may be a point in time when the similarity between the current image and the reference image becomes the best, or may be a point in time after the reference time and when other conditions are satisfied. . In the saving process, a still image that is a freeze target may be saved, or a moving image that has been stored up to that point may be saved. It is desirable to register the presence / absence of image storage, the type of stored image (still image, moving image), etc., and to proceed with the processing accordingly.

  Preferably, the control unit advances the routine inspection by referring to a management table for managing a plurality of steps constituting the routine inspection, and the control table automatically freezes for each of the steps. To register a flag indicating whether or not to save the image.

  Preferably, the optimization unit repeatedly calculates a correlation value between the current image and the reference image while repeatedly performing temporary setting on the automatic optimization target parameter, and based on the calculation result, the automatic optimization Make this setting for the target parameter.

  According to the present invention, the operation burden on the inspector can be reduced. Alternatively, the inspection time can be shortened.

1 is a block diagram showing a preferred embodiment of an ultrasonic diagnostic apparatus according to the present invention. It is a schematic diagram which shows the layout of an operation panel. It is a figure which shows the specific structural example of the routine test | inspection control part shown in FIG. It is a figure which shows the specific example of the state management table shown in FIG. It is a figure which shows the specific example of the parameter table shown in FIG. It is a flowchart which shows the basic process which the routine test | inspection control part shown in FIG. 1 performs. It is a flowchart which shows the specific content of the automatic optimization process shown in FIG. It is a figure which shows the luminance distribution of a reference image, and the luminance distribution of the present image. It is a figure which shows two luminance distributions after a binarization process. It is a figure for demonstrating the shift of the luminance distribution by a range change. It is a figure which shows the histogram of a reference image, and the histogram of the present image. It is a figure which shows the change of the histogram by a gain variable. It is a figure which shows the histogram of a reference image, and the histogram of the present image. It is a figure which shows the change of the histogram by contrast adjustment.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described with reference to the drawings.

  FIG. 1 shows a preferred embodiment of an ultrasonic diagnostic apparatus according to the present invention, and FIG. 1 is a block diagram showing the overall configuration thereof. This ultrasonic diagnostic apparatus is used in the medical field and forms an ultrasonic image of a living body by transmitting and receiving ultrasonic waves.

  In FIG. 1, a probe 10 is an ultrasonic probe that is used in contact with the body surface and transmits and receives ultrasonic waves. The probe 10 has a 1D array transducer composed of a plurality of vibration elements. An ultrasonic beam is formed by the 1D array transducer, and the ultrasonic beam is electronically scanned. As the electronic scanning method, electronic linear scanning, electronic sector scanning, and the like are known. A 2D array transducer may be provided for the probe 10 to construct a three-dimensional data capture area.

  The transmission / reception unit 12 functions as a transmission beamformer and a reception beamformer. At the time of transmission, a plurality of transmission signals are supplied in parallel from the transmission / reception unit 12 to the 1D array transducer. Thereby, a transmission beam is formed in the 1D array transducer. The reflected wave from the living body is received by the 1D array transducer, and a plurality of received signals are output from the 1D array transducer to the transmitting / receiving unit 12 in parallel. At the time of such reception, the transmission / reception unit 12 performs phasing addition processing on a plurality of reception signals, and outputs a reception signal after phasing addition, that is, beam data.

  The signal processing unit 14 is a module that executes processing on the beam data. Specifically, the signal processing unit 14 executes various signal processing such as detection processing, logarithmic compression processing, and noise removal processing. Beam data output from the signal processing unit 14 is sent to the image forming unit 16. The beam data may be stored in the cine memory 15. The cine memory 15 is configured as a ring buffer having a capacity for storing moving images. It is also possible to provide a cine memory 15 after the image forming unit 16.

  The image forming unit 16 is configured by a digital scan converter (DSC) in the present embodiment, and an ultrasonic image is configured based on a plurality of beam data in the image forming unit 16. The ultrasonic image includes a B-mode image, an M-mode image, a two-dimensional blood flow image, a color Doppler image (color flow mapping image), and the like. Depending on the selected operation mode, transmission / reception of ultrasonic waves is executed, and as a result, an ultrasonic image corresponding to the mode is configured. The display processing unit 18 has an image composition function and the like, performs predetermined processing on the image data output from the image forming unit 16, and outputs the image data to the display unit 20. An ultrasonic image is displayed on the display unit 20. In the present embodiment, image data output from the image forming unit 16 is sent to the control unit 22, specifically, a routine inspection control unit 24 included in the control unit 22.

  The control unit 22 performs operation control of each configuration shown in FIG. 1, and the control unit 22 includes a CPU and an operation program. The control unit 22 functions as a routine examination control unit 24 as shown in the figure, and the routine examination control unit 24 operates in, for example, a routine examination of the heart, and sequentially performs a plurality of steps constituting the routine examination. Various controls are performed during execution. In particular, in this embodiment, in order to reduce the burden on the user or shorten the inspection time, the contents of each process are controlled to be processed automatically as much as possible. This will be described in detail later.

  The operation panel 26 is connected to the control unit 22. As will be described later, the operation panel 26 includes a trackball, a keyboard, various switches, and the like. In the routine inspection control, several switches in the operation panel function as an enter button 28, a cancel button 30, a freeze button 32, and an end button 34 as shown in the figure. Here, one of the universal buttons may be assigned as the enter button 28, or one of the universal buttons may be assigned as the cancel button 30. An existing freeze button may be used as it is as the freeze button 32. The same applies to the end button 34. As will be described later, any button may be displayed on the sub-display included in the operation panel 26. The sub display is configured as a touch panel.

  FIG. 2 schematically shows a top view of the operation panel 26. The operation panel has a trackball at the center thereof, and various other buttons and switches. These include a mode selection button, a gain button, and the like. Reference numeral 28 denotes an enter button, and reference numeral 30 denotes a cancel button. The enter button 28 is a button that is pressed by the user when a next process execution command is input. In executing the routine inspection, the enter button 28 is basically operated in executing each step. That is, the routine inspection control unit shown in FIG. 1 performs control so that each step is automatically executed only by operating the enter button 28.

  The cancel button 30 is operated when a command for canceling the current state is input, and the cancel button 30 may function as a previous button. The freeze button 32 is a button for setting a freeze state in a normal operation. In this embodiment, the freeze button 32 is operated when a freeze input is performed by the user even when a routine inspection is executed. The The end button 34 is configured as an icon on the sub-display 36 in the present embodiment. That is, the sub display 36 is configured as a touch screen panel that displays a menu screen and various icons, and an end button 34 is virtually displayed in the form of a button there. The user can forcibly end the current routine by touching the end button 34.

  It is possible to basically execute each process by operating only a few buttons defined in this way, in this embodiment, four buttons 28, 30, 32, and 34. According to this, since the burden on the user can be greatly reduced and the inspection time of the entire routine inspection can be shortened, there is an advantage that the burden on the subject can be reduced.

  FIG. 3 is a block diagram showing a configuration example of the routine inspection control unit 24 shown in FIG. Each block may be configured as a software function. As will be described later, the state management table 36 is configured as a table in which various types of information relating to a plurality of processes constituting the routine inspection are registered. The state controller 38 refers to the state management table 36 to determine an operation mode in each state, that is, each process, necessity of image storage, and the like. That is, the state controller 38 controls the operation of each process in the routine inspection. In the present embodiment, the state controller 38 functions as a parameter temporary setting unit and a parameter main setting unit. These functions will be described in detail later. The parameter table group 40 includes a plurality of parameter tables 42. That is, in the present embodiment, one parameter table 42 is prepared for each process, and parameters necessary for the process are managed there. A specific example thereof will be described later with reference to FIG. The values given to the parameters on the parameter table 42 are automatically set in this embodiment, that is, automatically optimized, and can be specified by the user as necessary. In the currently selected process, ultrasonic transmission / reception is performed using the temporarily set parameter values in the parameter table 42, and the ultrasonic image formed as a result is stored in the current image memory 44. On the other hand, ultrasonic images registered in advance are stored in the reference image memory 46. The reference image on the reference image memory 46 is an ideal image. In this embodiment, each parameter in the parameter table 42 is set so that the current ultrasonic image, that is, the current image is as close as possible to such a reference image. The value is changed on a trial basis.

  The correlation value calculation unit 48 performs a correlation calculation between the current image and the reference image, and outputs a correlation value as a result. The similarity determination unit 50 determines the similarity between two images based on the correlation value. In that case, the similarity between the two images may be determined based on the correlation values obtained for each of the R value, G value, and B value constituting the value of each pixel. Various methods can be employed for determining the similarity. Information indicating the similarity output from the similarity determination unit 50 is output to the state controller 38.

  The state controller 38 sets each parameter in the parameter table as a target parameter in order, and optimizes the target parameter by referring to the similarity while sequentially changing the value given to the target parameter. Then, after the optimization for a certain attention parameter is completed, the next attention parameter is optimized by referring to the similarity while changing the value of the next attention parameter on a trial basis. By repeating this, it is possible to determine values for a plurality of parameters to be set in the currently selected process. Of course, the optimization process may be applied again after the optimization for one or more parameters is performed on the parameter once optimized. Alternatively, in the process of performing optimization for a plurality of parameters in order, if the similarity becomes a predetermined value or more in the middle, the optimization process may be terminated at that stage. In other words, it is desirable to automatically advance necessary parameter settings in each process while performing individual evaluation in parameter units and comprehensive evaluation as a whole parameter group.

  FIG. 4 shows an example of the state management table. Here, the state number functions as an identifier of each process. However, state number 1 indicates the initial input process, and the final value of the state number, that is, n indicates the end stage. For each process from state numbers 2 to n-1 other than that, the operation mode executed in the process is designated, and the location of the reference image used in the process is registered. Also, parameter names for a plurality of parameters to be set in the process are registered. Further, a flag indicating ON or OFF as to whether or not to save an image by automatic freezing after all of a plurality of parameters are set in the process is registered. Of course, other information may be registered together.

  Examples of operation modes include B mode, M mode, and color Doppler mode. However, as indicated by state number 2 and state number 3 here, even in the same B mode, there is a difference between the case where a short-axis tomographic image of the heart is displayed and the case where a long-axis tomographic image of the heart is displayed. A state number is assigned. Similarly, the B mode is designated for the state number 4 as well, but the B mode is a B mode executed prior to the execution of the M mode, that is, executed when the line for displaying the M mode is designated as the M cursor. B mode. In these operation modes, it is necessary to set gain, contrast, range (diagnosis distance), focus (depth of transmission focus point), and the like as parameters. In the present embodiment, parameters that can be automatically set among such parameters are managed as automatic optimization target parameters, which will be described in detail below.

  FIG. 5 shows a parameter table group 40. As described above, the parameter table group 40 includes a plurality of parameter tables 42 corresponding to a plurality of processes. In the parameter table 42 illustrated in FIG. 5, a setting type and a value are registered for each parameter name. As the setting type, either AUTO or MANUAL is determined. The former indicates that it is a target of automatic optimization processing, and the latter indicates that it is a target of manual setting by the user. The value represents the numerical value assigned to the parameter. When optimizing the value for each parameter of interest while using each parameter as the parameter of interest, the initial value is given as the value of each parameter at the very beginning. By performing the similarity determination described above, the value is optimized for each parameter of interest. Incidentally, in the present embodiment, a plurality of parameter tables corresponding to a plurality of processes are prepared. However, a common table may be configured for some parameters, or one parameter table as a whole inspection routine. May be configured.

  Next, an operation example of the routine inspection control unit shown in FIG. 1 will be described with reference to FIGS. FIG. 6 shows the basic process, and FIG. 7 illustrates the specific contents of the step S104 shown in FIG.

  In FIG. 6, in S101, the initial input process corresponding to the state number 1 is executed according to the contents set in the state management table. Here, for example, the ID of the subject is input. In S102, it is determined whether or not an enter button set on the operation panel has been input. If there is an input from the enter button, it is determined in S103 whether or not the currently selected process is an automatic optimization process. Here, if at least one parameter to be automatically optimized is included in the process, S104 is executed, and if not, S105 is executed. In S104, an automatic optimization process described in detail with reference to FIG. 7 is executed. In S105, manual settings for parameters that need to be set in the process are accepted, as in the prior art. After the desired setting is completed, a freeze operation is performed by the user as necessary, and a process of registering or storing the frozen still image or moving image in the medium is executed. In S106, it is determined whether or not the currently selected process is the final process. If not, the processes from S102 are repeatedly executed. However, the user's input is requested in S102, and the user can proceed with each process in order simply by pressing the enter buttons in order. In particular, if automatic optimization and automatic freeze processing are performed for each parameter in S104, there is an advantage that the user can proceed with each step only by inputting an enter button.

  FIG. 7 is a flowchart showing a specific example of the process of S104 shown in FIG. In S201, a parameter table corresponding to the currently selected process is referred to. Then, the attention parameter is selected. The attention parameter means a parameter to be automatically optimized. In S202, the setting type on the parameter table is referred to, and it is determined whether or not the parameter of interest is subject to automatic optimization. If it is not the object of automatic optimization, that is, if it is an object of manual setting, in S203, manual setting of the parameter of interest is accepted. Then, an input value is determined for the parameter of interest. In S204, the parameter of interest is changed to the next parameter. However, parameters that are targets for manual setting or parameters that have already been determined are excluded from optimization targets.

  If it is determined in S202 that the parameter is an automatic optimization target parameter, a correlation value is calculated between the current ultrasonic image, that is, the current image, and the registered reference image in S205. The current image is an image generated based on a parameter table having contents temporarily set at present. As described above, the correlation value represents the similarity between images. In S206, it is determined whether or not there is a user input. That is, when an interrupt process is generated by the user, S206 is provided to execute a process corresponding to the interrupt process.

  In S207, it is determined whether or not they are similar based on the correlation value. Specifically, it is determined that both images are similar when the correlation value or similarity is equal to or greater than a predetermined value. If it is not determined to be similar, it is determined in S208 whether or not the parameter of interest has been optimized. Also in this case, a correlation value between two images may be calculated, or a correlation value for other information instead of an image may be calculated. Various methods can be used to determine whether to achieve optimization in units of attention parameters. If it is determined that the optimization for the parameter of interest has been completed, the process of S204 described above is executed. On the other hand, if it is determined that the optimization has not been completed, S209 is executed. In S209, the value for the parameter of interest is changed. And the process after S205 is repeatedly performed.

  As described above, by changing the content of the current image while changing the value of the parameter of interest and also changing the parameter of interest, the similarity between the current image and the reference image is finally obtained. As a result, it is determined that the two images are similar. As a result, S213 is executed, and in this process, the image storage flag associated with the process corresponding to the currently selected state number is referred to, and it is determined whether it is on or off. If it is on, freeze processing is executed in S214, specifically, transmission / reception is stopped and the image contents stored in each storage unit are frozen. In S215, the content of the still image displayed on the screen is confirmed by the user. In this case, if a cancel button is input, this process is terminated. On the other hand, if an enter button is input, the still image saving process is executed in S216. A moving image on the cine memory may be stored in place of the still image.

  On the other hand, if any input by the user is determined in S206, it is determined in S210 whether or not the freeze button has been operated. If the button has been operated, the freeze process is executed in S214. That is, a freeze process is performed by an explicit freeze input by the user. If it is determined in S211 that the end button has been operated, this processing ends as it is. If it is determined that the user has set a value for the other input, that is, the target parameter, the input value for the target parameter is determined as it is as the set value in S212. And the process after S204 is repeatedly performed.

  In such repeated execution, the setting type of the parameter whose value is directly determined by the user is changed from AUTO to MUNUAL. In other words, only the parameters that are subject to automatic optimization are repeatedly changed, and the parameter values are set on a trial basis until the two images are best. The parameter for which the optimization is determined in S208 may be searched for the optimum value again as the attention parameter as necessary.

  Note that the method shown in FIGS. 8 to 14 to be described later may be used for the optimization determination in S208 or the change of the target parameter value in S209.

  FIG. 8 shows a luminance distribution 100 in a specific beam direction in the current image and a luminance distribution 102 in a specific beam direction in the reference image. Here, the specific beam direction is, for example, the central beam direction. The horizontal axis in FIG. 8 represents the depth direction, and the vertical axis represents the magnitude of luminance. FIG. 9 shows the result of binarization processing using the predetermined threshold value 104 for such two luminance distributions 100 and 102. Here, reference numeral 106 represents the luminance distribution of the current image after binarization processing, and reference numeral 108 represents the luminance distribution of the reference image after binarization processing. After the two binarized waveforms 106 and 108 are obtained, if the range, that is, the diagnostic distance is changed to a shallower one as indicated by reference numeral 110 in FIG. 10, the binarized waveform 106 is aligned along the horizontal axis direction. As a result, the binarized waveform 108 is approached. Such a stretched waveform is indicated at 112. If the range is determined so that the correlation value between the two waveforms 108 and 112 after binarization is maximized, the range can be optimized. Alternatively, it is possible to determine whether or not the parameter is optimized by referring to the correlation value between the two waveforms.

  FIG. 11 shows a histogram 114 for the current image and a histogram 116 for the reference image. The horizontal axis in FIG. 11 represents the luminance value, and the vertical axis represents the frequency. The histogram may be generated from the entire image or may be generated from a specific region in the image. As indicated by reference numeral 118 in FIG. 12, if the gain is increased, the histogram 114 of the current image is shifted in the horizontal axis direction, and the histogram after the shift is indicated by 120. Here, by calculating a correlation value between the histogram 116 of the reference image and the histogram 120 after the shift of the current image, it can be determined whether or not the current gain is optimized, or how much the value is changed. Then, it is possible to determine whether the gain can be optimized.

  FIG. 13 shows a histogram 122 of the current image and a histogram 124 of the reference image. As shown by reference numeral 126 in FIG. 14, if the contrast of the current image is reduced, the width of the histogram 122 of the current image can be widened, that is, the variance value can be increased. The histogram after the contrast reduction is denoted by reference numeral 128. By calculating the correlation value between the histogram 128 of the current image and the histogram 124 of the reference image, it is possible to evaluate the degree of coincidence between them, that is, the degree of contrast optimization, or the correlation value is the best between the two. By obtaining the shift amount, it is possible to find the optimum amount of change in contrast.

  According to the embodiment described above, the parameter optimization process can be automatically executed only by registering the contents of each process, that is, each state in the state management table, and automatically when necessary. There is an advantage that the image storage process can be executed, and as a result, the number of operations that the user should be involved in can be greatly reduced, and the burden on the user can be reduced. This brings about shortening of the routine inspection time, and as a result, the advantage that the burden on the subject can be reduced is obtained. The threshold value 104 shown in FIG. 8 may be a fixed value or a variable value. The threshold value 104 may be determined adaptively by referring to the image. When a fixed value is adopted, for example, it is possible to set the value to half of the maximum luminance value.

  24 routine inspection control unit, 26 operation panel, 28 enter button, 30 cancel button, 32 freeze button, 34 end button, 36 state management table, 38 state controller, 40 parameter table group, 42 parameter table, 44 current image memory, 46 Reference image memory, 48 correlation value calculation unit, 50 similarity determination unit.

Claims (8)

In an ultrasonic diagnostic apparatus used in a routine inspection including a plurality of steps including at least one parameter automatic optimization step,
A control unit for proceeding with the routine inspection while sequentially receiving next process execution instructions input by an inspector;
In association with the parameter automatic optimization step, a reference image storage unit that stores an image acquired in the past as a reference image;
Including
The controller is
In the parameter automatic optimization step, at least one automatic operation related to the generation of the current image is performed by comparing the current image formed by transmitting and receiving ultrasonic waves with a reference image associated with the parameter automatic optimization step. An optimization unit for optimizing the parameters to be optimized;
In the parameter automatic optimization step, a storage processing unit that executes a storage process of the current image generated after the setting for the parameter group including the automatic optimization target parameter is completed;
Including
The optimization unit associates the current image sequentially generated by repeating the temporary setting of the automatic optimization target parameter while changing the value of the automatic optimization target parameter, and the automatic optimization target parameter. Optimizing the automatic optimization target parameter by comparing the reference image as an ideal image;
An ultrasonic diagnostic apparatus. The apparatus of claim 1.
The plurality of steps includes a plurality of parameter automatic optimization steps,
The reference image storage unit stores a plurality of reference images associated with the plurality of parameter automatic optimization steps,
In each of the parameter automatic optimization steps, a plurality of automatic optimization target parameters related to the generation of the current image are optimized.
An ultrasonic diagnostic apparatus. The apparatus of claim 2.
In each of the parameter automatic optimization steps, among the parameter groups to be set in the step, parameters whose values are input by the inspector are preferentially set and excluded from the targets for automatic optimization. The ultrasonic diagnostic apparatus characterized by the above-mentioned. The apparatus of claim 3.
A parameter table is provided for managing whether each parameter constituting the parameter group is an automatic optimization target parameter,
The optimization unit identifies an automatic optimization target parameter from the parameter group by referring to the parameter table;
An ultrasonic diagnostic apparatus. In an ultrasonic diagnostic apparatus used in a routine inspection including a plurality of steps including at least one parameter automatic optimization step,
A control unit for proceeding with the routine inspection while sequentially receiving next process execution instructions input by an inspector;
In association with the parameter automatic optimization step, a reference image storage unit that stores an image acquired in the past as a reference image;
Including
The controller is
In the parameter automatic optimization step, at least one automatic operation related to the generation of the current image is performed by comparing the current image formed by transmitting and receiving ultrasonic waves with a reference image associated with the parameter automatic optimization step. An optimization unit for optimizing the parameters to be optimized;
In the parameter automatic optimization step, a storage processing unit that executes a storage process of the current image generated after the setting for the parameter group including the automatic optimization target parameter is completed;
Including
The storage processing unit
Means for determining freeze when all of the parameter groups are determined;
Means for storing the current image in a storage medium if the freeze is determined;
An ultrasonic diagnostic apparatus comprising: The apparatus of claim 5.
The current image at the time when the freeze is determined is displayed as a still image on the screen, and the current image is stored when the user confirms the current image.
An ultrasonic diagnostic apparatus. In an ultrasonic diagnostic apparatus used in a routine inspection including a plurality of steps including at least one parameter automatic optimization step,
A control unit for proceeding with the routine inspection while sequentially receiving next process execution instructions input by an inspector;
In association with the parameter automatic optimization step, a reference image storage unit that stores an image acquired in the past as a reference image;
Including
The controller is
In the parameter automatic optimization step, at least one automatic operation related to the generation of the current image is performed by comparing the current image formed by transmitting and receiving ultrasonic waves with a reference image associated with the parameter automatic optimization step. An optimization unit for optimizing the parameters to be optimized;
In the parameter automatic optimization step, a storage processing unit that executes a storage process of the current image generated after the setting for the parameter group including the automatic optimization target parameter is completed;
Including
The control unit advances the routine inspection by referring to a management table for managing a plurality of steps constituting the routine inspection,
In the management table, a flag indicating whether or not to save an image by automatic freezing is registered for each process.
An ultrasonic diagnostic apparatus. The device according to any one of claims 1 to 7,
The optimization unit repeatedly calculates a correlation value between the current image and the reference image while repeatedly performing temporary setting on the automatic optimization target parameter, and based on the calculation result, Optimize the automatic optimization target parameter by performing this setting.
An ultrasonic diagnostic apparatus.

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