JP2009213565A - Apparatus, method, and program for ultrasonic image processing - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately extract a speckle noise without depending on the shape or echo level in the periphery of the speckle. <P>SOLUTION: The ultrasonic image processing apparatus includes: an ultrasonic transmitting/receiving section for transmitting ultrasonic waves toward a subject and receiving the ultrasonic waves reflected from the subject; a speckle component extracting section for extracting speckle components from phase components of ultrasonic signals received by the ultrasonic transmitting/receiving section; and a speckle component processing section for processing the speckle components included in the ultrasonic image data based on the extracted speckle components. The ultrasonic image processing apparatus with the above structure is provided. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an ultrasonic image processing apparatus, method, and program, and more particularly to a technique for removing speckle noise from image data of an ultrasonic diagnostic apparatus by using phase information included in the data.

  Conventionally, it has been widely performed to obtain a tomographic image of a subject using ultrasonic waves and used for medical diagnosis, but in image data of an ultrasonic diagnostic apparatus, called speckle noise (speckle), There is low echo information generated by random interference of reflected ultrasonic waves from a plurality of reflectors in the subject. Since this speckle noise hinders image diagnosis, it is required to reduce speckle noise from an ultrasonic diagnostic image.

  As a method for reducing speckle noise, a compound scanning method and a filtering method are conventionally known. The compound scanning method is further classified into a spatial compound method and a frequency compound method as described in Patent Document 1, for example, and the spatial compound method performs ultrasonic transmission / reception from a plurality of different directions with respect to the same part of the subject. This is a method for generating image data for display by adding and synthesizing a plurality of obtained image data. On the other hand, the frequency compound method uses a plurality of images with different ultrasonic frequencies for the same part of a subject. Image data is collected, and these image data are added and synthesized to generate display image data.

Further, the filtering method simply filters image data to reduce speckle noise, but there are various types of filtering methods. For example, speckle noise is discriminated by threshold processing for the high-frequency component after wavelet transform and the low-frequency component for the amplitude component that is the basic information of the image data, and speckle noise removal and edge enhancement are performed (for example, , Patent document 1 etc.), or speckles are discriminated from the results of a directional secondary differential filter and a smoothing filter to perform speckle removal and edge enhancement (for example, see patent document 2 etc.) Etc. are known.
JP 2005-296331 A JP 2007-222264 A

  However, in the compound scanning method using a plurality of data, there is a problem that the temporal resolution is lowered in the case of the spatial compound method and the spatial resolution is lowered in the case of the frequency compound method. Further, in the case of the filling method using a simple filter, there is a problem that the sharpness of the image data is deteriorated, and it is necessary to accurately determine the speckle and the structure.

  In addition, in the filtering methods described in the above patent documents, the shape of speckle noise is very complicated, and the echo level of speckle changes depending on the surrounding echo level. There is a problem that it is difficult to design a corresponding threshold or filter.

  The present invention has been made in view of such circumstances, and provides an ultrasonic image processing apparatus, method, and program that enable accurate speckle noise removal independent of speckle shape and surrounding echo levels. For the purpose.

  In order to achieve the above object, the invention according to claim 1 includes an ultrasonic transmission / reception unit that transmits ultrasonic waves toward a subject and receives ultrasonic waves reflected from the subject; Speckle component extraction means for extracting a speckle component from the phase component of the ultrasonic signal received by the ultrasonic wave transmission / reception means, and processes the speckle component included in the ultrasonic image data based on the extracted speckle component. An ultrasonic image processing apparatus comprising: speckle component processing means.

  As a result, it may be difficult to distinguish speckle noise depending on the shape and echo level of speckle using only amplitude information, but by using phase information, it does not depend on the shape of speckle or the surrounding echo level. Processing of speckle components such as accurate speckle noise removal becomes possible.

  According to a second aspect of the present invention, the ultrasonic image processing apparatus according to the first aspect further includes display means for displaying a result obtained by processing the speckle component.

  By displaying the result of processing the speckle component in this way, utilization for diagnosis is promoted.

  In addition, according to a third aspect of the present invention, in the ultrasonic image processing apparatus according to the first or second aspect, the speckle component extraction unit uses the phase component change amount to change the phase component of the ultrasonic signal. It is characterized by extracting speckle components from.

  Thus, speckles can be extracted more accurately by using the amount of change in the phase component.

  According to a fourth aspect of the present invention, in the ultrasonic image processing apparatus according to the first or second aspect, the speckle component extraction unit uses a change amount of at least two directions of the phase component. It is characterized by.

  In this manner, the speckle extraction accuracy can be increased by using the amount of change in a plurality of directions.

  Further, as shown in claim 5, in the ultrasonic image processing device according to any one of claims 1 to 4, the speckle component extraction means uses a discriminant function for discriminating speckle. Features.

  Thereby, a discriminant function according to the purpose of speckle extraction can be used.

  Further, as shown in claim 6, the ultrasonic image processing apparatus according to any one of claims 1 to 4, wherein the speckle component extraction means compares the amount of change of the phase component with speckle. It is characterized by using a threshold value for discriminating.

  This facilitates speckle extraction when speckle can be determined by comparison with a threshold value.

  The ultrasonic image processing apparatus according to claim 5, wherein the discriminant function is a feature amount generated from a phase component whose positions of speckle and non-speckle are known. It is characterized by being set by.

  Thereby, a discriminant function can be created using the feature amount according to the speckle extraction process.

  In addition, as shown in claim 8, the ultrasonic image processing apparatus according to any one of claims 1 to 7, wherein the speckle component processing means removes speckle noise from image data. And

  Moreover, as shown in claim 9, in the ultrasonic image processing apparatus according to any one of claims 1 to 7, the speckle component processing means reduces speckle noise in image data. And

  Thus, by removing or reducing speckles based on the speckle extraction result, it is possible to further improve the accuracy of ultrasonic image diagnosis.

  According to a tenth aspect of the present invention, in the ultrasonic image processing apparatus according to the eighth or ninth aspect, the speckle component processing means emphasizes a tissue boundary.

  As a result, the tissue can be accurately recognized, and ultrasonic image diagnosis is facilitated.

  Similarly, in order to achieve the object, the invention according to claim 11 is an ultrasonic transmission / reception means for transmitting an ultrasonic wave toward a subject and receiving an ultrasonic wave reflected from the subject. And, based on the extracted speckle component, speckle component extraction means for extracting a speckle component from a combination of an amplitude component or an envelope component and a phase component of an ultrasonic signal received by the ultrasonic transmission / reception means, There is provided an ultrasonic image processing apparatus comprising: speckle component processing means for processing a speckle component included in ultrasonic image data.

  Thus, speckle extraction accuracy can be further improved by further combining amplitude information with phase information.

  The ultrasonic image processing apparatus according to any one of claims 1 to 11, wherein the phase component is a resolution of data in a direction perpendicular to a traveling direction of the ultrasonic signal. Is more than the arrangement interval of the elements for transmitting and receiving the ultrasonic signals with the ultrasonic receiving means.

  According to this, the resolution is improved and the speckle extraction accuracy is further improved.

  Similarly, in order to achieve the object, the invention according to claim 13 transmits an ultrasonic wave toward the subject, receives an ultrasonic wave reflected from the subject, and receives the received ultrasonic wave. Provided is an ultrasonic image processing method that extracts a speckle component from a phase component of a sound wave signal and processes the speckle component included in ultrasonic image data based on the extracted speckle component. .

  As a result, it may be difficult to distinguish speckle noise depending on the shape and echo level of speckle using only amplitude information, but by using phase information, it does not depend on the shape of speckle or the surrounding echo level. Processing of speckle components such as accurate speckle noise removal becomes possible.

  Similarly, in order to achieve the above object, the invention according to claim 14 includes a function of transmitting an ultrasonic wave toward the subject and receiving an ultrasonic wave reflected from the subject, A computer having a function of extracting a speckle component from a phase component of an ultrasonic signal and a function of processing a speckle component included in ultrasonic image data based on the extracted speckle component An ultrasonic image processing program is provided.

  Thus, by using the phase information, it is possible to process speckle components such as accurate speckle noise removal without depending on the shape of speckle and the surrounding echo level.

  As described above, according to the present invention, by using the phase information, it is possible to remove speckle noise accurately without depending on the shape of speckle and the surrounding echo level.

  Hereinafter, an ultrasonic image processing apparatus, method, and program according to the present invention will be described in detail with reference to the accompanying drawings.

  FIG. 1 is a block diagram showing a schematic configuration of an embodiment of an ultrasonic diagnostic apparatus including an ultrasonic image processing apparatus according to the present invention. This ultrasonic diagnostic apparatus captures and displays an ultrasonic image of a diagnostic region of a subject using ultrasonic waves, and mainly includes an ultrasonic probe 10, a signal processing unit 20, and image processing. The unit 30 and the display unit 40 are included.

  The ultrasonic probe 10 transmits ultrasonic waves toward a diagnosis site in the body of the subject and receives ultrasonic waves reflected in the body of the subject. In other words, since the ultrasonic waves are reflected at the boundary between regions having different acoustic impedances, such as the boundary between structures, an ultrasonic beam is transmitted into a subject such as a human body and an ultrasonic echo generated within the subject is received. The contour of the structure existing in the subject can be detected by obtaining the reflection point and reflection intensity at which the ultrasonic echo is generated.

  The ultrasonic probe 10 includes, for example, a plurality of ultrasonic transducers constituting a one-dimensional ultrasonic transducer array, and each ultrasonic transducer is formed by a vibrator in which electrodes are formed at both ends of a piezoelectric element such as PZT. Although configured, it is not particularly limited. For example, in addition to a linear array probe in which a plurality of ultrasonic transducers are arranged in one dimension in this way, a sector probe that scans the inside of a subject in a fan shape, a convex array probe in which a plurality of ultrasonic transducers are arranged on a convex surface, Alternatively, a two-dimensional array probe in which a plurality of ultrasonic transducers are two-dimensionally arranged may be used. Alternatively, it may be a mechanical radial probe that performs radial scanning in an ultrasonic endoscope.

  The ultrasound probe 10 transmits an ultrasound beam to the subject under the control of a control unit (not shown), and is scanned by a scanning method such as linear scanning, sector scanning, convex scanning, or radial scanning. Scan the examiner. The ultrasonic waves generated by the ultrasonic probe 10 are reflected by a reflector present in the body of the subject, and the reflected ultrasonic waves are received by the ultrasonic probe 10. The ultrasonic reception signal received by the ultrasonic probe 10 is converted into an electric signal and then delivered to the signal processing unit 20 via a transmission / reception unit (not shown).

  The signal processing unit 20 performs predetermined signal processing on the input received signal, phase matching addition for adding a plurality of received data with delay from the received ultrasonic received signal, and the received data as IQ data (complex Signal) to generate IQ data and output it to the image processing unit 30.

  Note that the amplitude A and phase θ of the received data are calculated from the IQ data by the following equations.

A = √ (I ² + Q ² ), θ = arctan (Q / I)
Here, the symbol √ (X) represents the square root of X. When the envelope of the waveform of the received data is taken, the amplitude must be doubled to the value 2√ (I ² + Q ² ).

  The signal processing unit 20 may use a method of generating data for each line. For example, as described in Japanese Patent Application Laid-Open No. 2003-180688, the reception data of all elements is stored in a memory, A method of generating data by processing may be used. With this method, the azimuth resolution (element direction resolution) can be further improved. For example, high-resolution phase information is used in the direction perpendicular to the traveling direction of the ultrasonic signal so that the resolution of the phase information is higher than the element interval in the direction perpendicular to the traveling direction of the ultrasonic signal. , Speckle random phase changes can be more accurately distinguished.

  Further, in a general ultrasonic B-mode image, an image is generated from amplitude and phase information is not used. Therefore, ultrasonic image data in the existing ultrasonic image processing technique (B mode) indicates amplitude data.

  Next, the relationship between signal interference and phase will be described with reference to the drawings. Interference includes constructive interference and canceling interference. Constructive interference occurs when the phase difference between the waves is small, and destructive interference occurs when the phase difference is close to π.

  FIG. 2 shows an example of constructive interference. FIG. 2A shows the state before interference, and three waves with small phase differences of 0.2 (rad), 0.4 (rad), and 0.6 (rad) are used for the reference wave. To interfere. FIG. 2B shows the state after interference, and the interference wave is represented by a solid line with respect to the reference wave represented by a broken line. When the phase difference is small in this way, an intensifying interference wave is obtained. As can be seen from FIG. 2B, the peak of the peak of the interference wave is close to the peak of the peak of the reference wave, and the interference wave having a small phase difference has a small phase difference from the reference wave even after the interference.

  FIG. 3 shows an example of destructive interference. FIG. 3A shows the state before interference. In this case, a phase difference of 3.0 (rad) and a phase difference of 3.2 (rad) in addition to the phase difference of 0.2 (rad) with respect to the reference wave. Is close to π (rad), causing large waves to interfere. At this time, as shown in FIG. 3B, a destructive interference wave is obtained as represented by a solid line with respect to a reference wave represented by a broken line. When waves having such a large phase difference are caused to interfere with each other, destructive interference waves are obtained. As can be seen from FIG. 3B, the peak of the peak of the interference wave is separated from the peak of the peak of the reference wave, and the interference wave having a large phase difference has a large phase difference from the reference wave even after the interference. .

  Previously, speckle noise was said to be caused by random interference of reflected ultrasonic waves from a plurality of reflectors in the subject, but interference with a large phase difference as shown in FIG. 3 generates speckle noise. Interference.

  Further, the phase obtained from the IQ data represents the phase difference between the wave after interference and the wave after detection. Since the phase of IQ detection includes an error, it is a result of interference having a large phase difference from the wave after interference. In order to confirm whether the result is small interference, it is only necessary to look at a continuous phase change of IQ data (for example, a difference between adjacent pixels). This is because when a wave having a small phase difference continues, the phase change is small, and when the speckle noise portion is reached, the phase changes suddenly and the phase change increases.

  In this way, speckle noise can be determined by using the feature that the phase changes suddenly.

  The image processing unit 30 performs image processing on the IQ data obtained by the signal processing unit 20 and displays the IQ data on the display unit 40. The center of processing in the image processing unit 30 is to extract phase information from the IQ data of the signal processing unit 20 to discriminate speckles, extract speckles, and extract speckles from amplitude image data based on the speckle extraction results. This is to create a display image from which speckles have been removed. Therefore, the image processing unit 30 includes a speckle extraction unit, a speckle removal unit, and the like as will be described later.

  FIG. 4 shows the flow of speckle extraction processing using phase information in the image processing unit 30.

  As illustrated in FIG. 4, the image processing unit 30 includes a speckle extraction unit 35 including a phase change amount extraction unit 32 and a speckle determination unit 34.

  Phase data is input to the phase change amount extraction unit 32 from the IQ data obtained by the signal processing unit 20. As described above, the phase is given by the equation θ = arctan (Q / I). The phase change amount extraction unit 32 extracts the phase change amount from the phase data. The extracted phase change amount data is input to the speckle determination unit 34. The speckle determination unit 34 extracts speckles using the phase change amount data and outputs a speckle extraction result.

  FIG. 5 shows an example of processing in the phase change amount extraction unit 32.

  When the phase change amount extraction unit 32 obtains the phase data, first, the phase change amount in the azimuth direction (lateral direction) and the phase change amount in the distance direction (depth direction), that is, the pixel difference (azimuth direction difference) in each direction. And the distance direction difference).

  In the case of a two-dimensional B-mode image, it is desirable to determine the amount of phase change in the azimuth direction and the distance direction in this way. This is because when speckle noise exists parallel to either the azimuth direction or the distance direction, the phase change is small in that direction, but the phase change is large in the direction orthogonal thereto.

  Next, a certain amount of phase change due to detection deviation is removed. Note that the speckle phase change changes abruptly compared to other parts, so only the components that increase the amount of change, such as differential data from the filter (low-pass filter, median filter) and secondary differentiation of the phase data, are extracted. By doing so, it is possible to obtain data having characteristics that make it easier to discriminate speckle.

  Then, a component whose phase changes suddenly in each direction is extracted, and phase change amount data in each direction is calculated. The amount of change is obtained from the difference between pixels in each direction. At this time, it is most preferable to use a difference between adjacent pixels, but a difference between pixels thinned out as appropriate may be used.

  In this manner, speckle / signal determination can be performed based on information obtained by removing a fixed amount of phase change in each of the vertical and horizontal directions.

  Note that the phase change amount is not limited to this information, and a difference average of a plurality of pixels or a difference in an oblique direction may be used. Furthermore, instead of separate change amounts, the data may be converted into one data such as a vector component.

  In the speckle discrimination unit 34, the obtained phase change data is subjected to binary discrimination as to whether it is speckle noise or multi-level discrimination as to how much speckle noise is included. Results are output according to purpose. Of course, the phase change amount itself may be output as data indicating speckle-likeness.

  The azimuth direction phase change amount data and the distance direction phase change amount data extracted by the phase change amount extraction unit 32 are input to the speckle determination unit 34. The speckle discriminating unit 34 discriminates speckles based on these phase information data.

  FIG. 6 shows a configuration example of the speckle determination unit 34.

  As shown in FIG. 6, the speckle discrimination unit 34 includes a discrimination function creation unit 341. The discriminant function creating unit 341 creates a discriminant function for discriminating whether or not speckle noise is generated from the phase change amount data.

  The discriminant function creating unit 341 prepares in advance phase data in which the speckle or non-speckle position is known in the amplitude image, and creates a discriminant function based on the feature amount created from the phase change amount. That is, a predetermined feature amount is calculated in the feature amount conversion unit 342 from the phase change amount data 344a known to be speckle and the phase change amount data 344b known to be non-speckle, From this, a speckle discriminant function is created.

  Here, the feature amount may be a single pixel of phase change amount data. However, in the case of a single pixel, when the phase change amount is obtained by taking the difference, a slight pixel shift occurs. When the phase change amount is obtained from the vertical and horizontal directions, the phase of the center of the crossing portion is obtained. Since there is a problem that the change does not increase, it is desirable to use a plurality of data such as the value of the neighboring pixel of the target pixel and the calculation result with the neighboring pixel. At this time, since a plurality of data are multidimensional, the dimension may be lowered by performing PCA (principal component analysis) or the like so that the threshold value can be easily designed.

  FIG. 9 shows an example of the speckle discriminant function.

  Here, the vertical direction phase change amount and the horizontal direction phase change amount are defined as a feature amount (1) and a feature amount (2), respectively, non-speckle noise is represented by ◯, and speckle noise is represented by x. In the example shown in FIG. 9, the discriminant function is set as a straight line that separates the non-speckle noise O and speckle noise x regions. A function (or threshold) for discriminating between speckle noise and non-speckle noise is designed based on the result converted into the feature quantity in this way. The discriminant function is not limited to such a linear function.

  The discriminant function setting method is not particularly limited. For example, a statistical method using known data (learning data) such as SVM (support vector machine) (for example, Nero Christianini as a reference). And a linear or non-linear discriminant function used for known classification such as “Introduction to Support Vector Machine” by John Taylor, etc.). Of course, speckle may be determined only by the threshold value if it can be determined only by giving a threshold value for each feature amount. In addition, a discrimination function may be set with data representing a phase change, such as pixels of continuous phase data, as a feature quantity without being converted into a phase change amount.

  FIG. 7 shows an example of a speckle extraction discriminant function generation process in the feature quantity conversion unit 342 using SVM (support vector machine).

  As shown in FIG. 7, first, the speckle part and the non-speckle part are manually labeled from the phantom image to create known data for creating a speckle discriminant function. When labeling speckles and non-speckle parts, it is not necessary to perform labeling for ambiguous parts. Next, a feature amount used for discrimination of speckle is extracted from the speckle portion and the non-speckle portion of the known data.

  Here, as a feature amount, as shown in FIG. 8, a central pixel c of 3 × 3 pixels is set as a target pixel, and the target pixel c and four neighboring pixels a, b, d, and e above, below, left, and right are vertically A total of ten feature quantities, ie, (distance) direction phase change and lateral (azimuth) direction phase change are used.

  Next, a discriminant function (speckle discrimination) is applied by applying SVM (support vector machine) with the phase change amount of a total of 10 positions of the labeled pixels (the target pixel and its vicinity) in the vertical direction and the horizontal direction as feature amounts. Generator). Of course, the data and feature quantities used for labeling may be changed so that the discrimination result is optimal.

  In this manner, the discriminant function creation unit 341 creates a speckle discriminant function by extracting feature amounts from known data that are known to be speckle and non-speckle in advance. In actual ultrasonic diagnosis, speckle extraction is performed based on phase information obtained from IQ data generated by the signal processing unit 20 from data obtained by scanning the ultrasonic probe 10.

  That is, in FIG. 6, when the azimuth (transverse) direction phase change amount data 346a and the distance (vertical) direction phase change amount data 346b are input, the feature amount conversion unit 343 converts them into feature amounts used for speckle discrimination. Then, using the speckle discriminant function 347 created in advance by the discriminant function creating unit 341, it is discriminated whether it is speckle, and speckle extraction is performed. Then, a speckle extraction result 348 is output.

  The discrimination result may not only indicate whether the speckle is binary, but also output the difference from the threshold as speckle-likeness indicating how much speckle noise is included in multiple values. . In the case of multi-value output, the value may be further adjusted using a LUT (Look Up Table) or the like.

  Note that the speckle discriminant function changes depending on the condition of ultrasonic transmission / reception, and therefore, in the case of an actual apparatus, it is desirable to set the discriminant function for each condition.

  As described above, in this embodiment, speckles are extracted using phase information instead of amplitude information. However, it is difficult to distinguish speckles depending on the shape of speckles and the echo level. In some cases, however, speckles cannot be accurately extracted, but by using phase information, speckles can be extracted independent of speckle shape and surrounding echo levels.

  Thus, speckles can be extracted only by phase information, but speckles are extracted by combining amplitude information (amplitude component or its envelope component) and phase information, such as adding amplitude information to a feature quantity. It may be. In this case, for example, in FIG. 6, phase information (azimuth direction phase change data 346a and distance direction phase change data 346b) is input to the feature value conversion unit 343. Speckle extraction may be performed by inputting to the conversion unit 343 and adding the amplitude information (pixel value) to increase the dimension of the feature amount (two dimensions in the example shown in FIG. 9).

  Thus, speckle extraction using both amplitude information and phase information enables more accurate speckle extraction.

  Next, the image processing unit 30 removes speckles from the amplitude image (amplitude data) based on the speckle extraction result.

  FIG. 10 shows a flow of speckle removal processing in the image processing unit 30. That is, here, speckle extraction is performed using the phase data, speckle removal is performed from the amplitude data based on the speckle extraction result, and display image data is created from the data from which the speckle has been removed.

  As illustrated in FIG. 10, the image processing unit 30 includes a speckle extraction unit 35 and a speckle removal unit 37. As shown in FIG. 4, the speckle extraction unit 35 includes a phase change amount extraction unit 32 and a speckle determination unit 34.

  IQ data input from the signal processing unit 20 is divided into phase data and amplitude data. The phase data is input to the speckle extraction unit 35 and the amplitude data is input to the speckle removal unit 37.

  In the speckle extraction unit 35, speckle is extracted using the phase data as described above. The speckle extraction result is input to the speckle removal unit 37.

  The speckle removal unit 37 applies speckle removal based on the speckle extraction result to the amplitude data. At this time, not only speckle removal but also enhancement of tissue boundaries may be performed. In addition, speckle removal may be applied to data obtained by extracting an envelope from received waveform data (RF data) instead of amplitude data obtained from IQ data.

  FIG. 11 shows an example of the speckle extraction result.

  What is shown on the left side of FIG. 11 is the amplitude data 352, and a speckle extraction result is obtained for each pixel as in a region 354 extracted from a part thereof and enlarged on the right side. This region 354 is now composed of 7 × 7 pixels, but the number of pixels is not limited to this. The pixel 354a painted black in the center is a pixel of interest, the pixel 354b represented by gray arranged on the diagonal line is speckle, and the other pixel 354c represented by white is information other than speckle, that is, a living body. Represents organizational information.

  Various methods can be considered for the speckle removal method. For example, the following method is exemplified.

  In other words, if the target pixel is speckle, create a speckle-removed image by interpolating with only the tissue part data, or by weighting the pixel according to the speckle discrimination result. Depending on the speckle extraction result, there is a method of replacing the original image, a method of weighted addition, or a method of processing IQ data instead of amplitude data by the method just described. Conceivable. Further, not only speckle removal but also processing for enhancing the structure boundary may be performed simultaneously or after speckle removal. For example, it may be possible to statistically analyze the amplitude information of only the tissue part from the speckle extraction result and apply a smoothing process in such a direction that the boundary becomes clear. I do not care.

  The speckle removal data that has been subjected to speckle removal by the speckle removal unit 37 is input from the speckle removal unit 37 to the scan converter 39. The scan converter 39 forms image data to be displayed on the display unit 40 from the input speckle removal data.

  In the scan converter 39, processing similar to that of a conventional apparatus such as DR (dynamic range) compression, gain, STC (depth weighting) adjustment, or gradation processing is performed.

  The amplitude data is finally subjected to logarithmic compression, but logarithmic compression may be performed either before or after speckle removal.

  The image data output from the scan converter 39 is displayed on the display unit 40.

  As described above, in this embodiment, after speckle is extracted from the phase data, speckle is removed from the amplitude data based on the speckle extraction result and displayed. Depending on the speckle shape and echo level, it may be difficult to distinguish speckle noise in amplitude, and it may not be possible to accurately extract speckle noise. Accurate speckle noise removal independent of the shape and surrounding echo level is possible.

  Further, the ultrasonic image processing apparatus of the present embodiment is controlled by an ultrasonic image processing program stored in a memory attached to a control unit (not shown). That is, an ultrasonic image processing program is read from the memory by the control unit, and according to the ultrasonic image processing program, an ultrasonic wave is transmitted toward the subject and an ultrasonic wave reflected from the subject is examined. Function, a function to extract a speckle component from the phase component of the received ultrasonic signal, and the removal of speckle noise in the image data, reduction of speckle noise, or tissue boundary based on the extracted speckle component A function of processing the speckle component included in the ultrasonic image data such as emphasizing is executed.

  Note that the ultrasonic image processing program is not limited to the one stored in the memory attached to the control unit in this way, and the ultrasonic image processing program is an ultrasonic image processing apparatus such as a PC card or a CD-ROM. It may be recorded in a memory medium (removable medium) configured to be detachable and read into the apparatus via an interface corresponding to the removable medium.

  Although the ultrasonic image processing apparatus, method, and program of the present invention have been described in detail above, the present invention is not limited to the above examples, and various improvements and modifications can be made without departing from the spirit of the present invention. Of course you can go.

1 is a block diagram showing a schematic configuration of an embodiment of an ultrasonic diagnostic apparatus including an ultrasonic image processing apparatus according to the present invention. It is a graph which shows the example of constructive interference, (a) represents before interference, (b) represents after interference. It is a graph which shows the example of the destructive interference, (a) represents before interference, (b) represents after interference. It is a block diagram which shows the flow of the speckle extraction process using the phase information in an image process part. It is a block diagram which shows an example of the process in a phase change amount extraction part. It is a block diagram which shows the example of 1 structure of a speckle discrimination | determination part. It is a block diagram which shows an example of the discriminant function production | generation process of the speckle extraction using SVM (support vector machine) in a feature-value conversion part. It is explanatory drawing which shows the example of the pixel used as a feature-value. It is explanatory drawing which shows the example of a speckle discriminant function. It is a block diagram which shows the flow of the speckle removal process in an image process part. It is explanatory drawing which shows an example of a speckle extraction result.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 ... Probe for ultrasonic waves, 20 ... Signal processing part, 30 ... Image processing part, 40 ... Display part, 32 ... Phase change amount extraction part, 34 ... Speckle discrimination | determination part, 35 ... Speckle extraction part, 37 ... Speckle removing unit, 39 ... scan converter, 341 ... discriminant function creating unit, 342, 343 ... feature amount converting unit

Claims (14)

Ultrasonic wave transmitting and receiving means for transmitting ultrasonic waves toward the subject and receiving ultrasonic waves reflected from the subject;
Speckle component extraction means for extracting a speckle component from a phase component of an ultrasonic signal received by the ultrasonic transmission / reception means;
Speckle component processing means for processing the speckle component included in the ultrasonic image data based on the extracted speckle component;
An ultrasonic image processing apparatus comprising:   2. The ultrasonic image processing apparatus according to claim 1, further comprising display means for displaying a result of processing the speckle component.   3. The ultrasonic image processing apparatus according to claim 1, wherein the speckle component extraction unit extracts a speckle component from the phase component of the ultrasonic signal using a change amount of the phase component. An ultrasonic image processing apparatus.   3. The ultrasonic image processing apparatus according to claim 1, wherein the speckle component extraction unit uses a change amount of at least two directions of the phase component. 4.   5. The ultrasonic image processing apparatus according to claim 1, wherein the speckle component extraction unit uses a discriminant function for discriminating speckles. 6.   5. The ultrasonic image processing apparatus according to claim 1, wherein the speckle component extraction unit uses a threshold value for discriminating speckle in comparison with a change amount of the phase component. An ultrasonic image processing apparatus.   6. The ultrasonic image processing apparatus according to claim 5, wherein the discriminant function is set by a feature amount generated from a phase component whose positions of speckle and non-speckle are known. Sonic image processing device.   The ultrasonic image processing apparatus according to claim 1, wherein the speckle component processing means removes speckle noise from image data.   The ultrasonic image processing apparatus according to claim 1, wherein the speckle component processing unit reduces speckle noise in image data.   The ultrasonic image processing apparatus according to claim 8, wherein the speckle component processing unit emphasizes a boundary of a tissue. Ultrasonic wave transmitting and receiving means for transmitting ultrasonic waves toward the subject and receiving ultrasonic waves reflected from the subject;
Speckle component extraction means for extracting a speckle component from a combination of an amplitude component or an envelope component and a phase component of an ultrasonic signal received by the ultrasonic transmission / reception means;
Speckle component processing means for processing the speckle component included in the ultrasonic image data based on the extracted speckle component;
An ultrasonic image processing apparatus comprising:   12. The ultrasonic image processing apparatus according to claim 1, wherein the phase component has data resolution in a direction perpendicular to a traveling direction of the ultrasonic signal, and the ultrasonic receiving unit and the ultrasonic wave An ultrasonic image processing apparatus characterized by being at least an arrangement interval of elements for transmitting and receiving a sound wave signal. While sending ultrasonic waves toward the subject, receiving the ultrasonic waves reflected from the subject,
Extract speckle component from phase component of received ultrasonic signal,
An ultrasonic image processing method comprising processing a speckle component included in ultrasonic image data based on the extracted speckle component. A function of transmitting ultrasonic waves toward the subject and receiving ultrasonic waves reflected from the subject;
A function to extract speckle components from the phase component of the ultrasound signal that has been examined,
Based on the extracted speckle component, a function of processing the speckle component included in the ultrasound image data,
An ultrasonic image processing program characterized in that a computer is realized.

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