JP5222067B2 - Ultrasonic data processor - Google Patents

Description

  The present invention relates to an ultrasonic data processing apparatus, and more particularly to a technique for tracing a contour of a target tissue.

  An ultrasonic data processing apparatus such as an ultrasonic diagnostic apparatus has a function of measuring the area and volume of a target tissue based on ultrasonic data. The target tissue is, for example, the left ventricle, placenta, tumor, and the like. The area calculation is executed based on two-dimensional ultrasonic data (tomographic data), and the volume calculation is usually executed based on three-dimensional ultrasonic data (volume data). In order to measure the area and volume of the target tissue, it is necessary to trace the contour of the target tissue. In the area calculation, the outer shape of the target tissue is specified, and in the volume calculation, the surface of the target tissue is specified.

  Manual tracing and automatic tracing are known as trace methods. According to manual tracing, although it is possible to trace relatively accurately even for a structural part where there is not much difference in luminance based on visual judgment based on empirical rules, it can be pointed out that it is cumbersome and burdensome. It is also quite difficult to trace the entire target tissue surface. According to the automatic trace, there is no burden on the user, but in many cases, it is not possible to accurately trace a structural portion with a small luminance difference. Patent Documents 1 and 2 describe tissue tracing or tissue extraction.

JP 2002-291750 A JP-A-7-184892

  Manual tracing and automatic tracing are in a trade-off relationship as described above. In this case, if the user decides which method to select, the result must be intuitive. As a result, there are cases where the advantages of each method cannot be used effectively. Therefore, an objective judgment index is required.

  An object of the present invention is to obtain an objective index when selecting manual tracing and automatic tracing. Another object of the present invention is to increase the reliability of the objective index.

  The present invention relates to an ultrasonic data processing apparatus for processing ultrasonic data acquired from a two-dimensional or three-dimensional in-vivo space, and in the data space corresponding to the in-vivo space, an outer reference unit is provided outside a target tissue. Setting and setting means for setting an inner reference portion inside the target region, and the ultrasonic wave based on a mutual relationship between an outer luminance distribution for the outer reference portion and an inner luminance distribution for the inner reference portion The present invention relates to an ultrasonic data processing apparatus including a determination unit that determines automatic trace processing or manual trace processing as a trace method for data.

  According to the above configuration, the outer reference portion having a two-dimensional or three-dimensional shape is set exclusively outside the target tissue, and similarly, the outer reference portion has a two-dimensional or three-dimensional shape exclusively inside the target tissue. An inner reference part is set. It is desirable that the outer reference portion is set completely outside the target tissue, but a partial protrusion may occur. Similarly, it is desirable that the inner reference portion is set completely inside the target tissue, but partial protrusion may occur. The allowance for the amount of protrusion is determined in consideration of the required trace method determination accuracy. The mutual relationship between the outer luminance distribution and the inner luminance distribution indicates how close they are on the luminance axis or how separated they are from each other. If the two luminance distributions are sufficiently separated from each other, automatic tracing should be possible with high accuracy. In that case, automatic tracing is recommended. On the other hand, if the two luminance distributions are close to each other, it can be inferred that automatic tracing is difficult. In that case, manual tracing is recommended. As described above, in the present invention, the tendency of the luminance difference is grasped from the comparison of the luminance distribution inside and outside the target region, and is used in the determination of the trace method. Although it is desirable that the tracing method is uniformly determined over the entire periphery of the target region, the tracing method can be determined for each partial region. It is also possible to determine the trace method in units of frames or volumes. The trace method can also be determined in units of ultrasonic diagnosis (examination). Or you may make it utilize the said method in determination of which surface is made into a representative slice surface among several slice surfaces. The ultrasonic data processing apparatus may be an ultrasonic diagnostic apparatus or an information processing apparatus that processes ultrasonic data.

  Preferably, the interrelationship is a degree of overlap between the outer luminance distribution and the inner luminance distribution. Various methods can be cited as specific methods for determining the degree of overlap. In any case, it is desirable to adopt a method that can provide an indicator of whether the difference in brightness between the inside and outside is large or small. Preferably, an outer luminance distribution unit that creates the outer luminance distribution by referring to the outer reference unit, an inner luminance distribution unit that creates the inner luminance distribution by referring to the inner reference unit, the outer luminance distribution, and the inner luminance distribution unit. Normalization processing means for normalizing one or both of the luminance distributions, and the determination means performs automatic trace processing or manual operation based on the overlap between the outer luminance distribution and the inner luminance distribution after the normalization processing. Determine trace processing. When the number of pixels (or the number of voxels) constituting each of the outer reference portion and the inner reference portion is different, it is desirable to apply this normalization processing. However, the trace method can be selected based on the absolute amount of the overlapping portion. In that case, normalization processing becomes unnecessary. Usually, in automatic trace processing, binarization processing of ultrasonic data is applied. That is, since the value of each pixel or the value of each voxel (that is, the luminance corresponding to the echo intensity) is compared with a predetermined threshold value, it is reasonable to use the luminance information in determining the trace method.

  Preferably, the determination means calculates a portion belonging to the overlapping section in the outer luminance distribution, and means for specifying an overlapping section of the outer luminance distribution and the inner luminance distribution after the normalization processing on the luminance axis. Means for calculating the degree of overlap based on a ratio of the overlapping section portion to the entire inner luminance distribution, and the automatic trace processing based on a comparison result between the degree of overlap and a predetermined reference value, or Means for determining a manual trace process.

  Preferably, the setting unit generates a tomographic image representing a representative cross section of the target tissue based on the ultrasound data, and performs user designation of a two-dimensional closed loop as the outer reference unit on the tomographic image. Means for receiving, and means for receiving a user designation of a two-dimensional closed loop as the inner reference portion on the tomographic image. Preferably, the setting means generates a plurality of tomographic images representing a plurality of cross sections of the target tissue based on the ultrasound data, and a tertiary as the outer reference unit on the plurality of tomographic images. Means for accepting user designation of the original spherical surface, and means for accepting user designation of the three-dimensional spherical surface as the inner reference portion on the plurality of tomographic images.

  Further, the present invention provides an ultrasonic data processing apparatus for processing ultrasonic data acquired from a two-dimensional or three-dimensional in-vivo space, and an external reference outside the target tissue in the data space corresponding to the in-vivo space. The ultrasonic data based on a setting means for setting a portion and setting an inner reference portion inside the target tissue, an outer luminance distribution for the outer reference portion, and an inner luminance distribution for the inner reference portion Determination means for determining automatic trace processing or manual trace processing as a tracing method for the external luminance distribution creating means for creating the outer luminance distribution by referring to the external reference unit; An inner luminance distribution creating means for creating the inner luminance distribution by referring to a reference unit; and the outer luminance distribution and the inner luminance distribution on the luminance axis. Processing method determination means for determining automatic trace processing or manual trace processing based on the degree of overlap obtained using the effective overlap range, and the processing method determination means includes the outer luminance distribution and the inner luminance distribution. The effective overlapping range is determined by excluding the base portion of at least one of the two.

  According to the above configuration, when determining the trace method, it is possible to determine an overlapping section (effective overlapping section) by excluding at least one base portion of the outer luminance distribution and the inner luminance distribution from the calculation target. It is possible to cope with the problem that the overlapping section determined by the extended portion is overestimated. In general, the cut of the skirt portion can be applied to both sides of the outer luminance portion and both sides of the inner luminance portion. However, if attention is paid to the overlapping section of two luminance distributions, it is desirable that the exclusion process is applied on the low luminance side of the outer luminance distribution and the high luminance side of the inner luminance distribution, and in particular, the exclusion process is applied to the latter. Is desirable.

  Preferably, the skirt portion is a portion on the high luminance side in the inner luminance distribution and a portion below a predetermined level. Preferably, the base portion is a portion on the high luminance side in the inner luminance distribution and is determined based on a statistical index indicating a degree of variation of the inner luminance distribution. As a result, it is possible to adopt a method other than the above as long as it is a process in which the base portion is excluded.

  Preferably, the processing method determination means determines the effective overlapping section by excluding the skirt portion of the inner luminance portion, the main portion after excluding the skirt portion in the inner luminance distribution, Means for calculating a ratio of the portion belonging to the effective overlap section in the outer luminance distribution as the degree of overlap, and means for determining the automatic trace process or the manual trace process by comparing the ratio with a constant value; ,including. Various structures within the target tissue are reflected in the inner luminance distribution and often spread, and noise waveforms are likely to occur on the high luminance side due to the influence of high luminance noise. Is preferably excluded from the calculation.

  As described above, according to the present invention, the advantages of both manual tracing and automatic tracing can be achieved. In particular, an objective index for selecting them can be obtained.

  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 data processing apparatus according to the present invention, and FIG. 1 is a block diagram showing the overall configuration thereof. This ultrasonic data processing apparatus is constituted by an ultrasonic diagnostic apparatus in the present embodiment. However, all or part of the configuration shown in FIG. 1 may be configured by an information processing device (computer).

  The 3D probe 10 is a transducer that transmits and receives ultrasonic waves to and from a three-dimensional space in a living body. In this embodiment, the 3D probe 10 has a 2D array transducer. The 2D array transducer is constituted by a plurality of vibration elements arranged two-dimensionally. Thereby, an ultrasonic beam is formed, and the ultrasonic beam is electronically two-dimensionally scanned. As a result, a three-dimensional data capturing space is formed. As electronic scanning methods, electronic sector scanning, electronic linear scanning, and the like are known. Instead of the 2D array transducer, a 1D array transducer and a mechanism for mechanically scanning the 1D array transducer may be provided.

  The transmission / reception unit 12 functions as a transmission beamformer and a reception beamformer. That is, at the time of transmission, a plurality of transmission signals are supplied from the transmission / reception unit 12 to the 2D array transducer. As a result, a transmission beam is formed. At the time of reception, the reflected wave from the living body is received by the 2D array transducer, whereby a plurality of received signals are output from the 2D array transducer to the transmission / reception unit 12. The transmission / reception unit 12 performs phasing addition processing on a plurality of reception signals, and thereby outputs a reception signal (beam data) after phasing addition. The beam data is stored in the 3D memory 14.

  The 3D memory 14 has a data space corresponding to the three-dimensional space in the living body, and a plurality of input beam data are stored in the 3D memory 14. Coordinate conversion from the transmission / reception coordinate system to the data coordinate system is executed when the data is stored or when data is read. The beam data is composed of a plurality of voxel data arranged along the ultrasonic beam. In the present embodiment, each voxel data is mapped to an address corresponding to the voxel data at the time of writing to the 3D memory 14. Prior to writing to each voxel data in the 3D memory 14, signal processing is executed as necessary. The signal processing may include, for example, binarization processing.

  The data processing unit 16 is a module that executes various types of data processing based on a plurality of beam data (volume data) stored in the 3D memory 14. In this embodiment, the data processing unit 16 includes an image forming unit 40, an automatic tracing unit 42, and a volume / area calculating unit 44. The image forming unit 40 is a unit that applies a process such as a volume rendering method based on volume data, thereby forming a three-dimensional ultrasonic image. The image forming unit 40 also has a function of forming three tomographic images corresponding to three cut planes set in a three-dimensional space as so-called triplane images. Further, the image forming unit 40 has a function of forming an arbitrary tomographic image corresponding to a cutting plane arbitrarily set by the user. Those image data are output to the display unit 20 via the display processing unit 18.

  The automatic trace unit 42 is a unit that executes auto-trace processing for slice planes for which automatic tracing is determined when performing trace processing on a plurality of slice planes set in a three-dimensional space. Prior to the trace processing, binarization processing for volume data or slice data is executed. The auto trace process can be realized based on a so-called edge detection method or the like. Various methods have been proposed as the auto-trace method. On the other hand, in the present embodiment, manual trace processing can also be performed on each slice plane. The manual trace process manually traces the contour of the target tissue on the tomographic image using a pointing device on the operation panel 38 described later. The coordinate data is given to the data processing unit 16, and the data processing unit 16 executes measurement processing described below using the coordinate data. Automatic trace processing or manual trace processing may be set uniformly for target tissues that exist three-dimensionally, or automatic trace processing or manual trace processing is switched and applied to each slice plane or tomographic plane. Also good. Further, the selection of the tracing method may be performed in units of ultrasonic diagnosis, that is, examination.

  The volume / area calculation unit 44 has a function of calculating the area of the target tissue based on the result of the automatic trace process and / or the result of the manual trace process, and calculating the volume. For example, if the target tissue is the left ventricle, loop-shaped trace lines are formed on a plurality of slice planes crossing the left ventricle, and the area on each slice plane is calculated, and then a certain thickness is given to them. The volume of the left ventricle is calculated by adding while giving. It is also possible to measure a fetus or placenta. The calculation result of the volume / area calculation unit 44 is sent to the display unit 20 via the display processing unit 18, and the calculation result is displayed on the screen as a numerical value or as a graph. The trace result may be displayed on the screen of the display unit 20. Further, on the screen of the display unit 20, a tomographic image and a graphic representing each ROI are displayed as necessary when setting an outer ROI (region of interest) and an inner ROI, which will be described later.

  Next, the trace method determination unit 22 will be described. In this embodiment, the trace method determination unit 22 includes histogram creation units 24 and 26, normalization units 28 and 30, a duplicate measurement unit 32, and a determination unit 34.

  The histogram creation unit 24 is a unit that creates a histogram based on a plurality of voxel data corresponding to the surface of the outer ROI when an outer ROI is set by the user outside the target tissue. Similarly, the histogram creation unit 26 is a unit that creates a histogram based on a plurality of voxel data corresponding to the surface when an inner ROI is set by the user inside the target tissue. The outer ROI only needs to be set outside the target tissue, and similarly, the inner ROI only needs to be set inside the target tissue. That is, even if partial protrusion occurs, such partial protrusion is not a problem as long as a certain accuracy can be obtained in the determination of the final trace method. Therefore, each ROI may be set automatically. Each ROI can be set as a two-dimensional shape or a three-dimensional shape. In that case, each ROI may be set using a shape such as an ellipse or an elliptic sphere. In the setting, a tomographic image corresponding to the slice plane of interest may be displayed on the display unit 20, or each ROI may be set using a so-called triplane image. . Furthermore, the ROI may be set three-dimensionally on the three-dimensional ultrasonic image. However, since it is difficult to immediately set a three-dimensional ROI on a three-dimensional ultrasound image, for example, by specifying the major axis and minor axis of an elliptical sphere using two of the triplane images. A histogram may be created based on the voxel group in the surface layer portion of each ROI instead of the voxel group on the display of each ROI for setting the ROI.

  In this embodiment, the surface or contour of the ROI is used. That is, a plurality of voxel data existing on a three-dimensional surface or a two-dimensional contour is referred to, and an outer histogram and an inner histogram are created based on the value of each voxel data. Specific examples will be described later. The normalization unit 27 is composed of two normalization units 28 and 30. The normalization unit 27 performs preprocessing for measuring the relationship between the two histograms by applying a normalization process to at least one of the two generated histograms. In the present embodiment, the respective histograms are standardized, that is, the areas on the histograms are the same.

  The overlap measurement unit 32 is a unit that specifies an overlap portion that is an overlap portion between the outer histogram and the inner histogram created as described above, and calculates this as a determination criterion. When there is little overlap between the two histograms, it can be inferred that the inside and outside separation of the target tissue is good. On the other hand, when the two histograms have a large overlap, the inside and outside of the target tissue are close to each other. It can be inferred that it is in a state. Therefore, in this embodiment, based on such a physical situation or empirical rule, the overlapping portion is used as an index, and the trace method is determined based on the overlapping portion. Specifically, the determination is performed in the determination unit 34. A method for calculating the degree of overlap and a specific determination method will be described in detail later. In any case, the determination unit 34 selects an appropriate trace method based on the overlapping relationship between the two histograms. Specifically, it is determined depending on the situation whether manual tracing is appropriate or automatic tracing is appropriate. The determination result is sent to the data processing unit 16.

  The data processing unit 16 determines whether to execute automatic tracing for a target slice plane or to accept manual trace input according to the determination result of the determination unit. When the determination result of the determination unit 34 indicates a manual trace, the data processing unit 16 displays on the display screen a prompt for manual tracing. In response to the display, the user performs manual tracing on the displayed target image. The data processing unit 16 recognizes the coordinate data input at that time. However, the user's will is respected at this stage, and the actual trace may be executed according to the method selected by the user. In that case, it is only necessary to provide information on a determination method to be recommended to the user.

  The control unit 36 includes a CPU and an operation program, and performs operation control of each configuration illustrated in FIG. An operation panel 38 is connected to the control unit 36. The operation panel 38 is composed of a keyboard, a trackball, and the like. Using the operation panel 38, the user can set the outer ROI and the inner ROI, can perform manual tracing, and can specify the input of the threshold value α to be input to the determination unit 34 as necessary. .

  Next, a tracing method determination method according to the present embodiment will be described in detail with reference to FIGS.

  A tomographic image 50 is shown in FIG. The tomographic image 50 includes a target tissue (more precisely, a cross section of the target tissue) 52. Reference numeral 52 </ b> A represents the contour of the target tissue 52. An outer ROI 54 is set by the user outside the contour 52A. Similarly, the inner ROI 56 is set by the user inside the contour 52A. These ROIs 54 and 56 may have a two-dimensional planar shape or a solid in a three-dimensional space. For example, the ROIs 54 and 56 may be set by designating the major axis, minor axis, and center coordinates of the ellipse. Further, by specifying another major axis, each ROI can be defined as an elliptical sphere. In the present embodiment, an ellipse or an elliptic sphere is used, but various shapes can be adopted as the shape of the ROI.

  FIG. 3 shows a histogram 100 composed of a plurality of voxel values existing on the surface of the outer ROI. The horizontal axis represents the luminance, that is, the voxel value, and the vertical axis represents the frequency after normalization. That is, the histogram 100 is a normalized histogram. The histogram 100 is distributed within the range indicated by reference numeral 109 from the luminance indicated by reference numeral 108. On the other hand, FIG. 4 shows a histogram 102 composed of a plurality of voxel values existing on the surface of the inner ROI. This histogram 102 is also a normalized histogram, which is distributed between the luminance indicated by reference numeral 104 and the luminance indicated by reference numeral 106.

  FIG. 5 shows the mutual relationship between the two histograms 100 and 102. That is, the histograms 100 and 102 are represented on the same luminance axis. Here, A indicates a range in which the histogram 102 is distributed. S 1 represents the area of the histogram 100, and S 2 represents the area of the histogram 102. In the histogram 100, the area of the portion belonging to the section A is represented by ΔS1.

  In the present embodiment, ΔS1 / S2 is used as an index ε representing the degree of overlap in order to evaluate the overlapping relationship between the two histograms 100 and 102. That is, the ratio ε of the area ΔS1 of the overlapping portion in the outer histogram to the area S2 corresponding to the inner histogram is used. If the ratio ε is large, it can be inferred that the two histograms 100 and 102 are largely overlapped. On the other hand, if the ratio ε is small, it can be inferred that the two histograms are well separated. Therefore, by comparing the ratio ε with the above-described predetermined threshold value α, it is predicted that automatic tracing is difficult if the index ε is larger than α, so that manual tracing is determined. If ε is smaller than α, it can be inferred that the brightness difference is clear inside and outside the target region, and therefore automatic tracing is determined. The determination method described above is an example, and in any case, the determination method may be determined so that the mutual relationship between the two histograms is quantified.

  Another example is shown in FIG. 6 and FIG. The same determination method is used. A tissue 62 exists on the tomographic image 60, and the tissue 62 includes a target tissue 62A and a tissue 62B connected to the target tissue 62A. For example, this situation is observed in the relationship between the placenta and the fetus. In such a case, the outer ROI 64 is set outside the contour 63 of the target tissue 62A, and the inner ROI 66 is set inside thereof. However, in this example, the outer ROI 64 penetrates to the tissue 62B that is not originally a measurement target. In such a case, when two histograms are created, the result is as shown in FIG. That is, the outer histogram 110 and the inner histogram 112 are formed, and both are substantially overlapped. Two peaks are observed in the outer histogram 110, and the lower peak is located in the inner histogram 112.

  In this case, when the same determination method as described above is applied, a section between the luminance 114 and the luminance 116 where the inner histogram 112 exists is specified as the section A. On the other hand, in the range from the luminance 118 to the luminance 119 in the outer histogram 110, the area of the portion belonging to A is specified as ΔS10. The area of the inner histogram 112 is S12. Under such a premise, ΔS10 / S12 is obtained as the ratio ε, and the ratio ε is compared with a predetermined threshold value α. In this case, since there is a considerable overlap, ε is larger than α, and as a result, it is determined that manual tracing is more suitable than automatic tracing. α can be set in advance by the user, or can be set adaptively, that is, automatically according to the state of the image.

  Various methods can be employed as a method for analyzing the relationship between the two histograms. For example, in a situation where two histograms 120 and 122 are formed as shown in FIG. 8, the peak luminances P1 and P2 of the histograms 120 and 122 and the histogram widths σ1 and σ2 of the histograms 120 and 122 are used. You may make it evaluate the duplication relation of two histograms. However, since it may not always be possible to directly determine the size of the overlap portion according to these parameters, it is desirable to evaluate the overlap portions in the two histograms 120 and 122 more directly. For example, the overlapping area ΔS ′ in the two histograms 120 and 122 may be obtained and used absolutely for the discrimination of the trace method. Alternatively, the overlapping relationship may be evaluated using the ratio between the interval ΔB ′ where the overlapping portion is generated and the width B of one histogram. In this case, ΔB ′ may be used alone to evaluate the size of the overlapping relationship. In any case, by quantitatively evaluating the size of the intersection of the two histograms, it is possible to objectively determine the trace method from the evaluation result.

  FIG. 9 shows a modification of the method described with reference to FIG. The method described using FIG. 9 is different from the method described using FIG. 5 in determining the section. In FIG. 9, the same components as those shown in FIG.

  In FIG. 9, the normalized outer histogram 100 exists between the luminance 108 and the luminance 109, and the normalized inner histogram 102 exists between the luminance 104 and the luminance 106. In the inner histogram 102, due to the structure of the target tissue, high luminance noise, and the like, a low level skirt portion 102A is generated on the high luminance side, which is considerably difficult to insert in the outer histogram 100. In such a case, if the method described with reference to FIG. 5 is applied as it is, there arises a problem that an overlapping portion is excessively estimated. Therefore, it is desirable to define an effective overlapping section by excluding all or part of the base portion 102A.

  Specifically, the predetermined value (frequency) C1 is fixedly or adaptively determined, and a portion having a lower level is excluded from the section determination targets. In the example shown in FIG. 9, the portion below C1 on the high luminance side (the portion on the right side of the point 102B and between the luminance 107 and the luminance 106) in the inner histogram 102 is regarded as the low level base portion. The section A2 excluding the section A3 from the entire section A1 of the inner histogram is regarded as an effective section, and the area S2 is calculated for the main part belonging to the section A2 in the inner histogram 102. On the other hand, also for the outer histogram 100, the effective overlapping section is a section from the luminance 108 to the luminance 107, and the area ΔS1 in the outer histogram 100 in the same section is calculated. Then, an appropriate trace policy is determined in the same manner as described above, with the ratio between the area S2 and the area ΔS1.

  The predetermined value C1 can be determined as a fixed value. Instead, the predetermined value C <b> 1 may be appropriately determined based on the calculation result (for example, variance, standard deviation, half width) of the statistical processing for the inner histogram 102. For example, the predetermined value C1 may be determined as a point that is lower than the peak level C by a certain percentage. This is indicated by D in FIG. Instead of determining the threshold level from the calculation result of the statistical processing, it is possible to determine the excluded portion based on the area ratio or the like. That is, a portion having a certain percentage of area may be recognized as a main portion that is an area calculation target, and at the same time, an effective overlapping section for the outer histogram 100 may be recognized from a portion having other areas.

  In the above description, the exclusion process is applied to the bottom part of the inner histogram 102 on the high frequency side, but the same exclusion process may be applied to the low frequency side of the inner histogram. Further, the same exclusion process as described above may be applied to the bottom portion on the high luminance side in the outer histogram 100. Furthermore, a process of excluding all portions below a certain level for one or both histograms may be applied. Even in such a case, a result of excluding the skirt portion can be obtained, so that the problem caused by the above-described skirt portion spreading on the luminance axis can be solved.

1 is a block diagram showing a preferred embodiment of an ultrasonic data processing apparatus according to the present invention. It is a figure for demonstrating the setting method of two ROI (region of interest). It is a figure which shows an outer side histogram. It is a figure which shows an inner side histogram. It is a figure which shows the duplication relationship of two histograms. It is a figure for demonstrating the setting of two ROI which concerns on another example. It is a figure which shows the duplication relationship of two histograms in the example shown in FIG. It is a figure for demonstrating the other determination method of duplication relationship. It is a figure for demonstrating the modification of the method shown in FIG.

Explanation of symbols

  10 3D probe, 12 transmission / reception unit, 14 3D memory, 16 data processing unit, 22 trace method determination unit, 24, 26 histogram creation unit, 28, 30 normalization unit, 32 overlap measurement unit, 34 determination unit, 40 image formation unit 42 Automatic trace section, 44 Volume / area calculation section.

Claims (10)

In an ultrasonic data processing apparatus for processing ultrasonic data acquired from a two-dimensional or three-dimensional in-vivo space,
In a data space corresponding to the in-vivo space, setting means for setting an outer reference portion outside a target tissue and setting an inner reference portion inside the target region;
Based on the correlation between the outer luminance distribution for the outer reference portion and the inner luminance distribution for the inner reference portion, as a tracing method for the ultrasonic data, a determination unit that determines automatic tracing processing or manual tracing processing;
An ultrasonic data processing apparatus comprising: The apparatus of claim 1.
The ultrasonic data processing apparatus according to claim 1, wherein the correlation is a degree of overlap between the outer luminance distribution and the inner luminance distribution. The apparatus of claim 2.
Outer luminance distribution means for creating the outer luminance distribution by referring to the outer reference section;
An inner luminance distribution means for creating the inner luminance distribution by referring to the inner reference portion;
Normalization processing means for normalizing one or both of the outer luminance distribution and the inner luminance distribution;
Including
The determination means determines automatic trace processing or manual trace processing based on the degree of overlap between the outer luminance distribution and the inner luminance distribution after the normalization processing.
An ultrasonic data processing apparatus. The apparatus of claim 3.
The determination means includes
Means for specifying an overlapping section of the outer luminance distribution and the inner luminance distribution after the normalization processing on the luminance axis;
Means for calculating a portion belonging to the overlapping section in the outer luminance distribution;
Means for calculating the degree of overlap based on a ratio of a portion belonging to the overlap section with respect to the entire inner luminance distribution;
Means for determining the automatic trace process or the manual trace process based on a comparison result between the degree of overlap and a predetermined reference value;
An ultrasonic data processing apparatus comprising: The apparatus of claim 1.
The setting means includes
Means for generating a tomographic image representing a representative cross section of the target tissue based on the ultrasound data;
On the tomographic image, means for receiving a user designation of a two-dimensional closed loop as the outer reference unit;
On the tomographic image, means for receiving a user designation of a two-dimensional closed loop as the inner reference portion;
An ultrasonic data processing apparatus comprising: The apparatus of claim 1.
The setting means includes
Means for generating a plurality of tomographic images representing a plurality of cross sections of the target tissue based on the ultrasound data;
On the plurality of tomographic images, means for accepting user designation of a three-dimensional spherical surface as the outer reference portion;
On the plurality of tomographic images, means for accepting user designation of a three-dimensional spherical surface as the inner reference portion;
An ultrasonic data processing apparatus comprising: In an ultrasonic data processing apparatus for processing ultrasonic data acquired from a two-dimensional or three-dimensional in-vivo space,
In a data space corresponding to the in-vivo space, a setting means for setting an external reference portion outside the target tissue and setting an inner reference portion inside the target tissue;
Based on the outer luminance distribution for the outer reference portion and the inner luminance distribution for the inner reference portion, as a tracing method for the ultrasonic data, a determination unit that determines automatic trace processing or manual trace processing;
Including
The determination means includes
An outer luminance distribution creating means for creating the outer luminance distribution by referring to the external reference unit;
An inner luminance distribution creating means for creating the inner luminance distribution by referring to the inner reference portion;
Processing method determination means for determining automatic trace processing or manual trace processing based on the degree of overlap obtained using the effective overlap range of the outer luminance distribution and the inner luminance distribution on the luminance axis;
Including
The ultrasonic data processing apparatus according to claim 1, wherein the processing method determination unit determines the effective overlapping range by excluding a tail portion of at least one of the outer luminance distribution and the inner luminance distribution. The apparatus of claim 7.
The ultrasonic data processing apparatus according to claim 1, wherein the base portion is a portion on a high luminance side in the inner luminance distribution and a portion below a predetermined level. The apparatus of claim 7.
The base portion is a portion on the high luminance side in the inner luminance distribution, and is a portion determined based on a statistical index indicating a variation degree of the inner luminance distribution. . The device according to any one of claims 7 to 9,
The processing method determination means includes
Means for determining the effective overlap section by excluding the skirt portion of the inner luminance portion;
Means for calculating, as the degree of overlap, a ratio between a main part after excluding the skirt part in the inner luminance distribution and a part belonging to the effective overlapping section in the outer luminance distribution;
Means for determining the automatic trace process or the manual trace process by comparing the ratio with a constant value;
An ultrasonic data processing apparatus comprising:

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