Ultrasound diagnostic device, medical image processing device, and correction program

Abstract

To correct speckle noise with a correction method according to variation in luminance.SOLUTION: An ultrasonic diagnostic device includes an acquisition part and a correction part. The acquisition part acquires ultrasonic luminance data. The correction part corrects a luminance value of original data according to a luminance difference between a luminance value of the original data and a reference luminance value based on luminance values of surrounding multiple data for each of the ultrasonic luminance data.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The embodiments disclosed in this specification and the drawings relate to an ultrasound diagnostic apparatus, a medical image processing apparatus, and a correction program. [Background technology]

[0002] It is known that ultrasonic images, in principle, contain speckle noise (mottled noise). Speckle noise is generated by the interference of scattered waves caused by reflectors that are sufficiently smaller than the wavelength of ultrasonic waves. Speckle noise appears in ultrasonic images as black or white pixels. For this reason, tissue regions depicted in ultrasonic images can be difficult to observe due to the influence of black or white pixels.

[0003] As a method for correcting such black or white pixels, there is a correction method in which each pixel of the ultrasound image is replaced by the median or average value of the surrounding pixels. By applying this type of correction method to the ultrasound image, it is possible to reduce speckle noise.

[0004] Incidentally, the intensity of the echo signal from the subject varies depending on the region. The variation in the intensity of the echo signal varies depending on the intensity of the echo signal. Therefore, the variation in the brightness of the region depicted in the ultrasound image varies from region to region. However, a correction method suitable for low brightness and low brightness variance is often inappropriate for high brightness and high brightness variance. For example, even if a correction method suitable for a region with low brightness variance is applied to a region with high brightness variance, speckle noise may remain, making it difficult to observe the region. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2000-262520 A Summary of the Invention [Problem to be solved by the invention]

[0006] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to reduce speckle noise using a correction method according to the variation in luminance. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0007] An ultrasound diagnostic device according to an embodiment includes an acquisition unit and a correction unit. The acquisition unit acquires ultrasound brightness data. The correction unit corrects the brightness value of the original data according to a brightness difference between the brightness value of the original data and a reference brightness value based on brightness values ​​of multiple surrounding data, for each of the ultrasound brightness data. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to an embodiment. [Diagram 2] FIG. 2 is an explanatory diagram showing an example of the configuration of a processing circuit according to the embodiment; [Diagram 3] 6A to 6C are diagrams for explaining the first speckle noise reduction process when black pixels are corrected. [Figure 4] 11A and 11B are diagrams for explaining the second speckle noise reduction process when black pixels are corrected. [Diagram 5] 11A to 11C are diagrams for explaining the third speckle noise reduction process in the case where black pixels are corrected. [Figure 6] 11A and 11B are diagrams for explaining the third speckle noise reduction process in the case where whiteout pixels are corrected. [Figure 7] FIG. 2A is an explanatory diagram showing an example of an ultrasound image after conventional speckle noise reduction processing using settings suitable for liver parenchyma, and FIG. 2B is an explanatory diagram showing an example of an ultrasound image after speckle noise reduction processing according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, embodiments of an ultrasonic diagnostic apparatus, a medical image processing apparatus, and a correction program will be described in detail with reference to the drawings.

[0010] The ultrasonic diagnostic device, medical image processing device, and correction program according to the present embodiment reduce speckle noise using a correction method according to luminance variation. Here, the "correction method according to luminance variation" refers to a method of varying the strength of correction of the luminance value of an original pixel according to the luminance difference between the luminance value of the original pixel to be corrected and a reference luminance value based on the luminance values ​​of multiple pixels surrounding the original pixel.

[0011] FIG. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 10 according to an embodiment.

[0012] The ultrasonic diagnostic device 10 can be used by being connected to an ultrasonic probe 20, an input interface 21, and a display 22. The ultrasonic diagnostic device 10 may include at least one of the ultrasonic probe 20, the input interface 21, and the display 22. The ultrasonic diagnostic device 10 may be a tablet type or a smartphone type.

[0013] As shown in FIG. 1, the ultrasound diagnostic apparatus 10 includes a transmission / reception circuitry 11, a B-mode processing circuitry 12, a Doppler processing circuitry 13, an image generating circuitry 14, an image memory 15, a storage circuitry 16, a network connection circuitry 17, and a processing circuitry 18.

[0014] The transmission / reception circuit 11 has a transmission circuit and a reception circuit. The transmission / reception circuit 11 is controlled by the processing circuit 18 to control the transmission directivity and reception directivity in transmitting and receiving ultrasonic waves. Note that, although an example in which the transmission / reception circuit 11 is provided in the ultrasonic diagnostic device 10 is shown in FIG. 1, the transmission / reception circuit 11 may be provided in the ultrasonic probe 20, or may be provided in both the ultrasonic diagnostic device 10 and the ultrasonic probe 20.

[0015] The transmission circuit has a pulse generator, a transmission delay circuit, a pulsar circuit, etc., and supplies a drive signal to the ultrasonic transducer. The pulse generator repeatedly generates rate pulses for forming a transmission ultrasonic wave at a predetermined rate frequency. The transmission delay circuit provides each rate pulse generated by the pulse generator with a delay time for each piezoelectric transducer required to focus the ultrasonic waves generated from the ultrasonic transducer into a beam shape and determine the transmission directivity. In addition, the pulsar circuit applies a drive pulse to the ultrasonic transducer at a timing based on the rate pulse. The transmission delay circuit arbitrarily adjusts the transmission direction of the ultrasonic beam transmitted from the piezoelectric transducer surface by changing the delay time provided to each rate pulse.

[0016] The receiving circuit has an amplifier circuit, an A / D converter, an adder, etc., and receives the echo signal received by the ultrasonic transducer and performs various processing on this echo signal to generate echo data. The amplifier circuit amplifies the echo signal for each channel and performs gain correction processing. The A / D converter A / D converts the gain-corrected echo signal and gives the digital data a delay time required to determine the reception directivity. The adder performs addition processing of the echo signals processed by the A / D converter to generate echo data. The addition processing by the adder emphasizes the reflection components from the direction corresponding to the reception directivity of the echo signal.

[0017] The B-mode processing circuit 12 receives the echo data from the receiving circuit, and performs logarithmic amplification, envelope detection processing, etc. to generate data (B-mode data) in which the signal intensity is expressed as luminance brightness.

[0018] The Doppler processing circuit 13 performs frequency analysis on the velocity information from the echo data received from the receiving circuit, extracts blood flow, tissue, and contrast agent echo components due to the Doppler effect, and generates data (Doppler data) that extracts mobility information such as average velocity, variance, and power for multiple points.

[0019] The image generating circuit 14 generates ultrasound image data based on the echo signal received by the ultrasound probe 20. For example, the image generating circuit 14 generates two-dimensional B-mode image data in which the intensity of the reflected wave is expressed by brightness from the two-dimensional B-mode data generated by the B-mode processing circuit 12. The image generating circuit 14 also generates image data of an average velocity image, a variance image, a power image, or a two-dimensional color Doppler image as a combination image thereof, which represents the locomotion information, from the two-dimensional Doppler data generated by the Doppler processing circuit 13. The image generating circuit 14 may also store the generated image data in the image server 40.

[0020] The image memory 15 is a memory that stores an image generated by the processing circuit 18. The storage circuit 16 has a configuration including a processor-readable recording medium, such as a magnetic or optical recording medium or a semiconductor memory.

[0021] A part or all of the programs and data in the storage medium of the storage circuitry 16 may be downloaded by communication via the network 100, or may be provided to the storage circuitry 16 via a portable storage medium such as an optical disk. Note that a part or all of the information stored in the storage circuitry 16 may be distributed and stored in at least one of the storage media, such as an external storage circuit or a storage circuit (not shown) of the ultrasound probe 20, or may be copied and stored.

[0022] The storage circuit 16 includes a processor-readable storage medium, such as a magnetic or optical storage medium or a semiconductor memory. A part or all of the programs and data in the storage medium of the storage circuit 16 may be downloaded by communication via an electronic network, or may be provided to the storage circuit 16 via a portable storage medium, such as an optical disk. Note that a part or all of the information stored in the storage circuit 16 may be distributed and stored in at least one of storage media, such as an external storage circuit or a storage circuit (not shown) of the ultrasound probe 20, or may be copied and stored.

[0023] The network connection circuit 17 implements various information communication protocols according to the form of the network 100. The network connection circuit 17 connects the ultrasound diagnostic apparatus 10 to other electrical devices in accordance with these various protocols. For this connection, an electrical connection via an electronic network can be applied. Here, the electronic network means information and communication networks in general that utilize electrical communication technology, and includes wireless / wired LANs such as hospital backbone LANs (Local Area Networks) and the Internet, as well as telephone communication line networks, optical fiber communication networks, cable communication networks, and satellite communication networks.

[0024] The processing circuitry 18 realizes a function of overall control of the ultrasonic diagnostic apparatus 10. The details of the configuration and operation of the processing circuitry 18 will be described later with reference to FIGS. 2-7.

[0025] The ultrasonic probe 20 is detachably connected to the ultrasonic diagnostic device 10 via a cable. The ultrasonic probe 20 may be connected to the ultrasonic diagnostic device 10 wirelessly.

[0026] A two-dimensional array probe in which a plurality of ultrasonic transducers are arranged in the scan direction (azimuth direction) and a plurality of elements are also arranged in the lens direction (elevation direction) can be used as the ultrasonic probe 20. As this type of two-dimensional array probe, for example, a 1.5D array probe, a 1.75D array probe, a 2D array probe, etc. can be used.

[0027] The ultrasonic probe 20 may be configured to acquire volume data. In this case, the subject may be scanned three-dimensionally by the ultrasonic probe 20, which is a two-dimensional array probe, or the subject may be scanned two-dimensionally by the ultrasonic probe 20, which is a one-dimensional ultrasonic probe in which a plurality of piezoelectric transducers are arranged in a row, or the subject may be scanned three-dimensionally by rotating the plurality of ultrasonic transducers, or the plurality of piezoelectric transducers of the one-dimensional ultrasonic probe may be mechanically oscillated.

[0028] When the ultrasound probe 20 is capable of acquiring volume data, the user can select either a two-dimensional display mode (2D mode) in which any of a plurality of two-dimensional ultrasound images is displayed as a real-time moving image or as a still image, or a four-dimensional display mode (4D mode) in which a three-dimensional ultrasound image acquired in real time is displayed as a moving image.

[0029] The input interface 21 is realized by a general input device such as a trackball, a switch, a button, a mouse, a keyboard, a touch pad that performs an input operation by touching an operation surface, a non-contact input circuit using an optical sensor, a voice input circuit, and the like, and outputs an operation input signal corresponding to a user's operation to the processing circuit 18. The input interface 21 may be configured as an operation panel. In this case, the operation panel functions as a touch command screen and has, for example, a display, a touch input circuit provided near the display, and hard keys.

[0030] The display 22 is configured with a general display output device such as a liquid crystal display or an OLED (Organic Light Emitting Diode) display, and displays various information under the control of the processing circuit 18.

[0031] Furthermore, when the ultrasonic diagnostic device 10 is a tablet or smartphone type ultrasonic diagnostic device 10, the input interface 21 and the display 22 may be integrated to form a touch panel.

[0032] Furthermore, the ultrasound diagnostic apparatus 10 may be connected to a medical image processing apparatus 30 and an image server 40 via a network 100 so as to be able to transmit and receive data to and from each other.

[0033] FIG. 2 is an explanatory diagram showing an example of the configuration of the processing circuit 18 according to the present embodiment.

[0034] The processing circuitry 18 is a processor that executes a process for reducing speckle noise using a correction method according to the variation in brightness (hereinafter referred to as speckle noise reduction process) by reading and executing a correction program stored in the memory circuitry 16.

[0035] 2, the processor of the processing circuitry 18 realizes an image acquisition function 31, a correction function 32, and an image generation function 33. Each of these functions 31-33 is stored in the form of a program in the storage circuitry 16. The processing circuitry 18 may perform the speckle noise correction process in a post-process, or may perform the speckle noise correction process in real time every time an ultrasound image is acquired.

[0036] The image acquisition function 31 acquires ultrasonic brightness data in real time from the image memory 15. The image acquisition function 31 may also acquire ultrasonic brightness data from the image server 40 in post-processing. The image acquisition function 31 is an example of an acquisition unit. The two-dimensional B-mode image data (ultrasound image data) and the two-dimensional B-mode data generated by the B-mode processing circuit 12 are each an example of ultrasonic brightness data.

[0037] The correction function 32 corrects the luminance value of the original data for each pixel of the ultrasonic luminance data according to the luminance difference between the luminance value of the original data and a reference luminance value based on the luminance values ​​of multiple surrounding data. In other words, the correction function 32 varies the correction strength of the luminance value of the original data according to the luminance difference between the luminance value of the original data and a reference luminance value based on the luminance values ​​of multiple surrounding data. The correction function 32 is an example of a correction unit.

[0038] Examples of reference luminance values ​​that can be used include the average and median luminance values ​​of multiple adjacent data, and the luminance value among the luminance values ​​of each data of multiple surrounding pixels that has the largest difference from the luminance value of the original data (hereinafter referred to as the luminance value with the maximum difference).

[0039] The speckle noise reduction process may be applied to the two-dimensional B-mode image data, or may be applied to the two-dimensional B-mode data generated by the B-mode processing circuit 12. When the speckle noise reduction process is applied to the two-dimensional B-mode data generated by the B-mode processing circuit 12, it is preferable that the image generating circuit 14 generates two-dimensional B-mode image data based on the processed data.

[0040] In the following description, an example of performing speckle noise reduction processing on two-dimensional B-mode image data will be described. In this case, the correction function 32 corrects the luminance value of each pixel of the two-dimensional B-mode image (ultrasound image) according to the luminance difference between the luminance value of the original pixel and a reference luminance value based on the luminance values ​​of multiple surrounding pixels.

[0041] The multiple surrounding pixels include, for example, 2 to 8 pixels adjacent to the original pixel. The multiple surrounding pixels may include pixels that are not adjacent to the original pixel. The number of the multiple surrounding pixels and the positions of the multiple surrounding pixels relative to the original pixel (the distance from the original pixel) may be set by the user via the input interface 21.

[0042] A black pixel has a significantly smaller luminance value than the surrounding pixels. Therefore, when correcting a black pixel, the maximum luminance value of the surrounding pixels is used as the luminance value of the maximum difference. On the other hand, a white pixel has a significantly larger luminance value than the surrounding pixels. Therefore, when correcting a white pixel, the minimum luminance value of the surrounding pixels is used as the luminance value of the maximum difference.

[0043] The image generating function 33 generates an ultrasound image after the speckle noise reduction processing by the correction function 32 and displays it on the display 22.

[0044] The functions 31-33 of the processing circuitry 18 may be realized by a processor of the medical image processing device 30. In this case, the medical image processing device 30 acquires an ultrasound image from the ultrasound diagnostic device 10 or the image server 40. The medical image processing device 30 is an example of a medical image processing device.

[0045] As described above, the "correction method according to the luminance variation" refers to a method of varying the correction strength of the luminance value of an original pixel according to the luminance difference between the luminance value of the original pixel to be corrected and a reference luminance value based on the luminance values ​​of multiple surrounding pixels. The speckle noise reduction process (processing for reducing speckle noise by a correction method according to the luminance variation) executed by the processing circuit 18 can be roughly classified into the following three types:

[0046] Fig. 3 is a diagram for explaining the first speckle noise reduction process when correcting a black pixel. Fig. 3 shows an example of correcting a black pixel, that is, when the luminance value of the original pixel is smaller than the luminance values ​​of the surrounding pixels.

[0047] In the first speckle noise reduction process, the correction function 32 corrects the luminance value of the original data by weighted averaging of the reference luminance value and the luminance value of the original data, and changes the weight according to the luminance difference dL between the luminance value of the original data and the reference luminance value. For example, in an example of performing speckle noise reduction process on two-dimensional B-mode image data shown in this embodiment, the correction function 32 corrects the luminance value of the original pixel by weighted averaging of at least one of the average value and median value of the luminance values ​​of multiple surrounding pixels and the luminance value of the maximum difference (the luminance value of the luminance values ​​of each pixel of the multiple surrounding pixels that has the maximum difference from the luminance value of the original pixel) and the luminance value of the original pixel, and changes the weight according to the luminance difference dL between the luminance value of the original pixel and the reference luminance value.

[0048] FIG. 3 shows an example in which the average weight approaches 1 from 0 as the luminance difference dL between the original pixel luminance value and the reference luminance value becomes larger between a first threshold dLth1 and a second threshold dLth2 of the luminance difference dL.

[0049] In the example shown in FIG. 3, when the luminance difference dL is equal to or less than the first threshold dLth1, the luminance value of the original pixel is not corrected. In this case, when the luminance difference dL is equal to or less than the first threshold dLth1, the correction function 32 may not perform the speckle noise reduction process. In this case, it can be said that the correction function 32 adaptively determines whether or not to perform the speckle reduction process based on the first threshold dLth1. Also, when the luminance difference dL is equal to or less than the first threshold dLth1, the correction function 32 may perform the speckle noise reduction process by the weighted averaging in which the weight of the average value is fixed to 0. The same applies to the second and third speckle noise reduction processes described later, with regard to whether or not to perform the speckle reduction process when the luminance difference dL is equal to or less than the first threshold dLth1.

[0050] On the other hand, if it is greater than the second threshold dLth2, the correction function 32 replaces the luminance value of the original pixel with the average value, or performs the weighted averaging with the weight of the average value fixed at 1.

[0051] The first speckle noise reduction process can change the weighting according to the luminance difference dL between the luminance value of the original pixel and the reference luminance value. Therefore, according to the first speckle noise reduction process, the strength of the correction can be increased as the luminance difference dL between the luminance value of the original pixel and the reference luminance value increases. Therefore, according to the first speckle noise reduction process, even if the region (such as the liver parenchyma) has a small luminance variation and a small luminance difference between the pixel affected by the speckle noise and the surrounding pixels, or the region (such as the diaphragm) has a large luminance variation and a large luminance difference between the pixel affected by the speckle noise and the surrounding pixels, a correction method suitable for each region can be applied. Therefore, according to the first speckle noise reduction process, even if the ultrasound image includes both a region with a small luminance variation and a region with a large luminance variation, an image with speckle noise reduced easily and suitably can be obtained.

[0052] FIG. 4 is a diagram for explaining the second speckle noise reduction process in the case where black pixels are corrected.

[0053] In the second speckle noise reduction process, the correction function 32 replaces the luminance value of the original data with one of a plurality of reference luminance values ​​based on the luminance values ​​of a plurality of surrounding data, and changes which of the plurality of reference luminance values ​​is to be replaced with the luminance value of the original data according to the luminance difference dL between the luminance value of the original data and the reference luminance value. For example, in an example of performing speckle noise reduction process on two-dimensional B-mode image data shown in this embodiment, the correction function 32 replaces the luminance value of the original pixel for each pixel with one of two or more values ​​selected from the average value and median value of the luminance values ​​of a plurality of surrounding pixels and the luminance value of the maximum difference, and changes which of the two or more selected values ​​is to be replaced with the luminance value of the original pixel according to the luminance difference dL between the luminance value of the original pixel and the reference luminance value.

[0054] 4 shows an example in which the correction function 32 selects the average value and the maximum difference luminance value as replacement candidate luminance values. In the example in which a black pixel is corrected as shown in FIG. 4, the maximum difference luminance value is the maximum value among the luminance values ​​of multiple surrounding pixels.

[0055] In the example shown in FIG. 4, when the luminance difference dL between the luminance value of the original pixel and the reference luminance value is greater than the first threshold dLth1 and equal to or less than the second threshold dLth2, the luminance value of the original pixel is replaced with the average value. When the luminance difference dL is greater than the second threshold dLth2, the luminance value of the original pixel is replaced with the maximum value (the luminance value of the maximum difference). When the luminance difference dL is equal to or less than the first threshold dLth1, whether or not to perform the speckle reduction process is the same as in the first speckle noise reduction process. Furthermore, at least one of the first threshold dLth1 and the second threshold dLth2 may be different between the first speckle reduction process and the second speckle reduction process.

[0056] The second speckle reduction process can change the luminance value to be replaced according to the luminance difference dL between the luminance value of the original pixel and the reference luminance value. Therefore, the second speckle noise reduction process can also increase the strength of correction as the luminance difference dL between the luminance value of the original pixel and the reference luminance value increases.

[0057] FIG. 5 is a diagram for explaining the third speckle noise reduction process in the case where black pixels are corrected.

[0058] In the third speckle noise reduction process, when the luminance difference dL between the luminance value of the original pixel and the reference luminance value is greater than a first threshold dLth1 and less than or equal to a second threshold dLth2, the correction function 32 corrects the luminance value of the original pixel by performing a weighted average of the average or median of the luminance values ​​of multiple surrounding pixels and the luminance value of the original pixel, with a weight corresponding to the luminance difference dL.

[0059] Furthermore, when the luminance difference dL is greater than the second threshold dLth2 and equal to or less than the third threshold dLth3, the correction function 32 corrects the luminance value of the original pixel by taking a weighted average of the luminance value of the maximum difference and the average or median of the luminance values ​​of the multiple surrounding pixels with a weight according to the luminance difference dL. Furthermore, when the luminance difference dL is greater than the third threshold dLth3, the correction function 32 replaces the luminance value of the original pixel with the luminance value of the maximum difference.

[0060] In the example shown in FIG. 5, when the luminance difference dL is greater than the first threshold dLth1 and equal to or less than the second threshold dLth2, the luminance value of the original pixel is corrected by performing a weighted averaging of the average value and the luminance value of the original pixel so that the weight of the average value approaches 0 to 1 as the luminance difference dL increases. When the luminance difference dL is greater than the second threshold dLth2 and equal to or less than the third threshold dLth3, the luminance value of the maximum difference and the average value are weighted and averaged so that the weight of the luminance value of the maximum difference approaches 0 to 1 as the luminance difference dL increases, and the luminance value of the original pixel is corrected. When the luminance difference dL is equal to or less than the first threshold dLth1, the speckle reduction process is performed in the same manner as in the first speckle noise reduction process. At least one of the first threshold dLth1 and the second threshold dLth2 of the third speckle reduction process may be different from the values ​​of the first speckle reduction process and the second speckle reduction process.

[0061] The third speckle reduction process can also increase the strength of correction as the luminance difference dL between the luminance value of the original pixel and the reference luminance value increases.

[0062] FIG. 6 is a diagram for explaining the third speckle noise reduction process shown in FIG. 5 in the case where blown-out white pixels are corrected.

[0063] In the example of correcting a blown-out pixel shown in FIG. 6, the brightness value of the blown-out pixel is much larger than the brightness values ​​of the surrounding pixels. Therefore, the brightness value of the maximum difference is the minimum value among the brightness values ​​of the multiple surrounding pixels. Even when correcting a blown-out pixel, the first to third speckle noise reduction processes can be applied in the same way as when correcting a black pixel.

[0064] The correction function 32 may apply different speckle noise reduction methods to whiteout pixels and blackout pixels. Even if the same speckle noise reduction method (e.g., the third speckle noise reduction process) is used for whiteout pixels and blackout pixels, different threshold values ​​or different replacement values ​​may be used for whiteout pixels and blackout pixels.

[0065] FIG. 7(a) is an explanatory diagram showing an example of an ultrasound image after conventional speckle noise reduction processing using settings suitable for liver parenchyma, and (b) is an explanatory diagram showing an example of an ultrasound image after speckle noise reduction processing according to this embodiment.

[0066] The liver parenchyma is a region with small luminance variations and small differences in luminance between pixels affected by speckle noise and surrounding pixels, whereas the diaphragm is a region with large luminance variations and large differences in luminance between pixels affected by speckle noise and surrounding pixels.

[0067] In the conventional speckle noise reduction process, when a suitable setting is made for the liver parenchyma as shown in FIG. 7(a), for example, the speckle noise of the liver parenchyma can be reduced (see a partial region 51 of the liver parenchyma in FIG. 7(a)), but it is difficult to reduce the speckle noise of the diaphragm (see a partial region 52 of the diaphragm in FIG. 7(a)). Similarly, it is difficult to appropriately reduce the speckle noise of the liver parenchyma with a suitable setting for the diaphragm. For this reason, in the conventional speckle noise reduction process, with a suitable setting for the diaphragm, the image of the liver parenchyma becomes a blurred image with little undulation. In this way, in the conventional speckle noise reduction process, when focusing on an area with small luminance variation such as the liver parenchyma, the speckle noise of an area with large luminance variation such as the diaphragm cannot be successfully reduced, and vice versa.

[0068] In this regard, the speckle noise reduction process according to the present embodiment can increase the correction strength as the luminance difference dL between the luminance value of the original pixel and the reference luminance value increases. Therefore, as shown in FIG. 7(b), the speckle noise of both the liver parenchyma and the diaphragm can be easily and appropriately reduced. For example, in the image of the liver parenchyma, it is possible to leave undulations of a suitable depth that is not too deep and does not lose resolution, and in the image of the diaphragm, it is possible to suitably erase blackened pixels.

[0069] The first to third speckle noise reduction processes may be applied to the entire ultrasound image, or may be applied only to one or more regions of interest set by a user or automatically. In the above embodiment, an example in which speckle noise reduction processes are performed on two-dimensional B-mode image data has been shown, but after the speckle noise reduction processes are performed on the two-dimensional B-mode data generated by the B-mode processing circuitry 12, the image generating circuitry 14 may generate two-dimensional B-mode image data.

[0070] According to at least one of the embodiments described above, speckle noise can be corrected using a correction method according to the variation in luminance.

[0071] In the above embodiment, the term "processor" refers to a circuit such as a dedicated or general-purpose CPU (Central Processing Unit), GPU (Graphics Processing Unit), or an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). When the processor is a CPU, for example, the processor realizes various functions by reading and executing a program stored in a memory circuit. When the processor is an ASIC, for example, instead of storing a program in a memory circuit, a function corresponding to the program is directly built into the processor circuit as a logic circuit. In this case, the processor realizes various functions by hardware processing that reads and executes the program built into the circuit. Alternatively, the processor can realize various functions by combining software processing and hardware processing.

[0072] In the above embodiment, an example was shown in which a single processor of the processing circuit realizes each function, but a processing circuit may be configured by combining multiple independent processors, and each processor may realize each function. In addition, when multiple processors are provided, a memory circuit for storing a program may be provided for each processor, or one memory circuit may collectively store programs corresponding to the functions of all the processors.

[0073] Although some embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and spirit of the invention. [Explanation of symbols]

[0074] 10. Ultrasound diagnostic equipment 30 Medical image processing device 31 Image acquisition function 32 Correction function dL is the luminance difference between the original pixel luminance value and the reference luminance value.

Claims

1. An acquisition unit that acquires ultrasonic intensity data for each pixel; A correction unit that corrects the luminance value of the original data according to a luminance difference between a luminance value of the original data as a luminance value of a pixel to be corrected and a reference luminance value based on luminance values ​​of a plurality of surrounding data as luminance values ​​of a plurality of pixels surrounding the pixel to be corrected, for each of the ultrasonic luminance data of each pixel; Equipped with The correction unit is Applying different correction methods to white and black pixels, or applying the same correction method but using different thresholds or different replacement values; The correction unit further comprises: replacing the luminance value of the original data with one of a plurality of reference luminance values ​​based on the luminance values ​​of the plurality of surrounding data, and changing which of the plurality of reference luminance values ​​is to be replaced with the luminance value of the original data according to the luminance difference; Ultrasound diagnostic equipment.

2. An acquisition unit that acquires ultrasonic brightness data for each pixel; A correction unit that corrects the luminance value of the original data according to a luminance difference between a luminance value of the original data as a luminance value of a pixel to be corrected and a reference luminance value based on luminance values ​​of a plurality of surrounding data as luminance values ​​of a plurality of pixels surrounding the pixel to be corrected, for each of the ultrasonic luminance data of each pixel; Equipped with The correction unit is Applying different correction methods to white and black pixels, or applying the same correction method but using different thresholds or different replacement values; The correction unit further comprises: when the luminance difference is greater than a first threshold value and is equal to or less than a second threshold value, a weighted average of the first reference luminance value and the luminance value of the original data is calculated with a weight corresponding to the luminance difference, thereby correcting the luminance value; when the luminance difference is greater than a second threshold value and is equal to or smaller than a third threshold value, a weighted average of the first reference luminance value and the second reference luminance value is calculated with a weight corresponding to the luminance difference, thereby correcting the luminance value of the original data; When the luminance difference is greater than the third threshold, replacing the luminance value of the original data with the second reference luminance value. Ultrasound diagnostic equipment.

3. The correction unit is As the reference luminance value based on the luminance values ​​of the plurality of surrounding data, one of an average value and a median value of the luminance values ​​of the plurality of surrounding data, and a luminance value among the luminance values ​​of the plurality of surrounding data that has a maximum difference from the luminance value of the original data is used.

3. The ultrasonic diagnostic apparatus according to claim 1.

4. An acquisition unit that acquires ultrasonic brightness data for each pixel; A correction unit that corrects the luminance value of the original data according to a luminance difference between a luminance value of the original data as a luminance value of a pixel to be corrected and a reference luminance value based on luminance values ​​of a plurality of surrounding data as luminance values ​​of a plurality of pixels surrounding the pixel to be corrected, for each of the ultrasonic luminance data of each pixel; Equipped with The correction unit is Applying different correction methods to white and black pixels, or applying the same correction method but using different thresholds or different replacement values; The correction unit further comprises: replacing the luminance value of the original data with one of a plurality of reference luminance values ​​based on the luminance values ​​of the plurality of surrounding data, and changing which of the plurality of reference luminance values ​​is to be replaced with the luminance value of the original data according to the luminance difference; Medical imaging equipment.

5. On the computer, acquiring ultrasound intensity data for each pixel; A step of correcting the luminance value of the original data for each of the ultrasonic luminance data of each pixel according to a luminance difference between a luminance value of the original data as a luminance value of a pixel to be corrected and a reference luminance value based on luminance values ​​of a plurality of surrounding data as luminance values ​​of a plurality of pixels surrounding the pixel to be corrected; A program for executing The correcting step includes: applying different correction methods to white pixels and black pixels, or applying the same correction method but using different thresholds or different replacement values; The correcting step further comprises: a step of replacing the luminance value of the original data with one of a plurality of reference luminance values ​​based on the luminance values ​​of the plurality of surrounding data, and changing which of the plurality of reference luminance values ​​is to be replaced with the luminance value of the original data according to the luminance difference; Correction program.

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