WO2021018103A1 - 超声信号处理方法、装置、设备及存储介质 - Google Patents

超声信号处理方法、装置、设备及存储介质 Download PDF

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WO2021018103A1
WO2021018103A1 PCT/CN2020/105010 CN2020105010W WO2021018103A1 WO 2021018103 A1 WO2021018103 A1 WO 2021018103A1 CN 2020105010 W CN2020105010 W CN 2020105010W WO 2021018103 A1 WO2021018103 A1 WO 2021018103A1
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signal
target tissue
target
ultrasound
frequency
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PCT/CN2020/105010
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English (en)
French (fr)
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何琼
邵金华
孙锦
段后利
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无锡海斯凯尔医学技术有限公司
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0858—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving measuring tissue layers, e.g. skin, interfaces
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5207—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of raw data to produce diagnostic data, e.g. for generating an image
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data

Definitions

  • This application relates to the field of ultrasound technology, and in particular to an ultrasound signal processing method, device, equipment and storage medium.
  • Quantitative ultrasound can provide clinicians with a very intuitive Quantitative evaluation, such as elasticity, blood flow, etc.
  • This application provides an ultrasonic signal processing method, device, equipment and storage medium to solve the defects of the prior art such as inaccurate judgment of the state of the target tissue.
  • the first aspect of this application provides an ultrasonic signal processing method, including:
  • the target tissue is evaluated.
  • a second aspect of the present application provides an ultrasonic signal processing device, including:
  • the acquisition module is used to acquire the dynamic broadband target ultrasound signal corresponding to the target tissue
  • a determining module configured to determine the attenuation characteristic of the target tissue according to the target ultrasound signal
  • the processing module is used for evaluating the target tissue according to the attenuation characteristics of the target tissue.
  • a third aspect of the present application provides a computer device, including: at least one processor and a memory;
  • the memory stores a computer program; the at least one processor executes the computer program stored in the memory to implement the method provided in the first aspect.
  • a fourth aspect of the present application provides a computer-readable storage medium in which a computer program is stored, and when the computer program is executed, the method provided in the first aspect is implemented.
  • the ultrasonic signal processing method, device, equipment and storage medium provided in this application determine the attenuation characteristics of the target tissue based on the dynamic broadband target ultrasonic signal, and evaluate and process the target tissue according to the attenuation characteristics of the target tissue.
  • the ultrasound signals of the tissue at multiple frequencies make the signal components rich and diverse, and improve the accuracy of the evaluation of the target tissue.
  • FIG. 1 is a schematic flowchart of an ultrasonic signal processing method provided by an embodiment of this application
  • FIG. 2 is a schematic flowchart of an ultrasonic signal processing method provided by another embodiment of the application.
  • FIG. 3 is a schematic structural diagram of an ultrasonic signal processing device provided by an embodiment of the application.
  • Fig. 4 is a schematic structural diagram of a computer device provided by an embodiment of the application.
  • the ultrasonic signal processing method provided by the embodiments of the application is suitable for a scene where a dynamic broadband probe is used to detect a target tissue, to obtain a dynamic broadband ultrasonic signal of the target tissue, and to determine the state of the target tissue based on the dynamic broadband ultrasonic signal of the target tissue.
  • the target tissue may be liver tissue, muscle tissue, adipose tissue, breast tissue, thyroid tissue, and other tissues, etc., which are not specifically limited.
  • the state of the target tissue can be a normal state or a diseased state, and if it is a diseased state, it can also include the type of the disease and the corresponding disease level.
  • liver tissue the diseased state includes fatty liver, tumor, etc.
  • fatty liver can include mild fatty liver, moderate fatty liver, severe fatty liver, and so on.
  • the specific lesion level can be set according to actual needs, which is not limited in the embodiment of this application.
  • This embodiment provides an ultrasonic signal processing method for processing a dynamic broadband ultrasonic signal to determine the state of the target tissue.
  • the execution body of this embodiment is an ultrasonic signal processing device, which can be set in a computer device.
  • FIG. 1 it is a schematic flowchart of the ultrasonic signal processing method provided by this embodiment, and the method includes:
  • Step 101 Acquire a dynamic broadband target ultrasound signal corresponding to the target tissue.
  • a dynamic broadband ultrasound probe can be used to detect the target tissue, obtain a dynamic broadband original ultrasound signal, and perform certain processing on the original ultrasound signal to obtain a dynamic broadband target ultrasound signal corresponding to the target tissue.
  • dynamic broadband means that the ultrasonic probe can work with a relatively wide range of signal bandwidth, and the center frequency of the probe is dynamically adjustable.
  • the wide frequency generally refers to that the ratio of the working signal frequency of the ultrasonic probe to the center frequency is greater than or equal to 60%.
  • the dynamic broadband target ultrasound signal refers to the ultrasound signal obtained by using a broadband probe to detect the target tissue under different center frequency excitation.
  • the ratio of the bandwidth of the ultrasound probe to the center frequency is greater than 60%, and the signal frequency involved is 0.1MHz-100MHz.
  • the frequency includes 20Hz-0.5MHz.
  • the bandwidth of the ultrasonic probe is 9MHz.
  • the target tissue may be human or animal tissues such as liver tissue, muscle tissue, adipose tissue, breast tissue, or thyroid tissue, and may also be air or geological tissue, which is not limited in this embodiment.
  • the ultrasound probe is connected with the ultrasound imaging device to collect the ultrasound echo signal or the transmitted wave signal of the target tissue, which is referred to as the original ultrasound signal in the embodiment of the present application.
  • the original ultrasound signal can be one-dimensional, two-dimensional, three-dimensional, etc., which are specifically set according to actual needs.
  • the ultrasound imaging device may include a transmitting device, a receiving device, an imaging processing device, and the like. Because it is a dynamic broadband ultrasonic probe, the acquired original ultrasonic signal includes at least one frequency signal, that is, it may include multiple frequency signals.
  • data calibration can be performed on the original ultrasound signal, and processing such as extraction of components of interest can be performed to obtain the target ultrasound signal.
  • Data calibration is due to the directivity of the ultrasound probe itself, the focus configuration or setting of the probe, the sensitivity of the probe, the gain of the system and other signal processing methods that affect the acquired original ultrasound signal.
  • the original ultrasound signal needs to be calibrated to restore the original
  • the specific data calibration process can be set according to the hardware, software and algorithm process of the ultrasound equipment.
  • Extracting the components of interest specifically refers to extracting the information of interest from the original ultrasound signal.
  • the original ultrasound signal obtained may include the ultrasound signal of the subcutaneous tissue and the ultrasound signal of the liver tissue.
  • the ultrasonic signal is extracted from the original ultrasonic signal.
  • the original ultrasound signal includes the frequency range of 1-20MHz. According to actual experience, the frequency is too high to reach the target tissue and has been seriously attenuated, so it cannot be effective.
  • the 1-5MHz range can be extracted from the original ultrasound signal.
  • a dynamic broadband target ultrasound signal corresponding to the target tissue can be obtained through certain processing.
  • frequency filtering or wavelet decomposition may also be used to obtain signals of different frequencies of the original ultrasound signal.
  • Step 102 Determine the attenuation characteristics of the target tissue according to the target ultrasound signal.
  • the attenuation characteristics of the target tissue can be determined according to the target ultrasound signal.
  • the target ultrasonic signal can be segmented along the depth, and the signal energy at multiple segments can be calculated (for each segment, such as the sum of the amplitude of the signal of each frequency, the sum of the square of the amplitude, and the corresponding amplitude The sum of decibel values, etc.) to determine the attenuation characteristics of the target tissue.
  • the decibel value corresponding to the amplitude refers to the DB value obtained by performing logarithmic compression processing on the amplitude.
  • each segment is divided into n segments along the depth, n ⁇ 2, center depth d1, d2,..., dn, each segment length is ⁇ l, and the depth interval is ⁇ d.
  • Each segment contains signals of multiple frequencies.
  • the signal energy of each segment is obtained, the signal energy of multiple segments is linearly fitted, and the fitted slope is obtained.
  • the slope is divided by the center frequency to obtain the attenuation characteristics corresponding to the target tissue.
  • the center frequency can be obtained through frequency analysis, such as Fourier transform, wavelet transform, etc.
  • the obtained center frequency is the frequency of the signal with the largest amplitude corresponding to each frequency signal.
  • one-dimensional linear fitting can be used for one dimension
  • least square fitting can be used for two dimensions
  • cubic spline fitting can be used for three dimensions, etc.
  • the specific fitting method is the prior art. Repeat it again.
  • the attenuation characteristics of the target tissue at each frequency can also be calculated separately.
  • the center frequency is the frequency.
  • the center frequency is 3MHz; for multiple frequencies, the center frequency is the frequency of the signal with the largest amplitude, for example, frequency There are five frequencies of 1MHz, 2MHz, 3MHz, 4MHz, and 5MHz.
  • the signal frequency with the largest amplitude is 4MHz, and the center frequency is 4MHz.
  • Step 103 Perform evaluation processing on the target tissue according to the attenuation characteristics of the target tissue.
  • the target tissue can be evaluated and processed according to the attenuation characteristics of the target tissue.
  • the state of the target tissue can be judged according to the attenuation characteristics of the target tissue.
  • the state may include a normal state and an abnormal state.
  • the abnormal state may include the abnormality type and the corresponding abnormality level.
  • the target tissue is liver tissue as an example.
  • the reference attenuation feature or reference attenuation feature range corresponding to the normal state of liver tissue, the reference attenuation feature or reference attenuation feature range corresponding to different lesion levels under different lesion types can be obtained in advance, and the target The tissue attenuation feature is compared with the preset reference attenuation feature range.
  • the reference attenuation feature range corresponding to the attenuation feature of the target tissue determines which situation the target tissue belongs to.
  • the attenuation feature of the target liver tissue corresponds to a normal liver.
  • the target tissue is determined to be mild fatty liver, and so on.
  • the abnormal level reflects the degree of tissue lesions.
  • the type of lesion indicates what kind of abnormality has occurred in the tissue.
  • the abnormal types of liver tissue include fatty liver, tumor, etc.
  • the abnormal grades corresponding to fatty liver include mild fatty liver, moderate fatty liver, severe fatty liver, and so on.
  • the specific abnormality type and abnormality level can be set according to the actual situation of different organizations, which is not limited in this embodiment.
  • the ultrasonic signal processing method provided in this embodiment determines the attenuation characteristics of the target tissue based on the dynamic broadband target ultrasonic signal, and evaluates the target tissue according to the attenuation characteristics of the target tissue. Because the target tissue is integrated at multiple frequencies Ultrasound signal, which makes the signal components rich and diverse, improves the accuracy of the evaluation of the target tissue.
  • This embodiment further supplements the method provided in the first embodiment.
  • FIG. 2 it is a schematic flowchart of the ultrasonic signal processing method provided by this embodiment.
  • the target ultrasound signal includes a signal of at least one frequency.
  • Step 102 specifically includes:
  • Step 1021 Perform segmentation processing on the target ultrasound signal along the depth direction to obtain at least two segments of ultrasound signals.
  • Step 1022 Calculate and obtain the signal energy of each segment of the ultrasonic signal.
  • Step 1023 Determine the attenuation characteristics of the target tissue according to the signal energy of each segment of the ultrasound signal.
  • the target ultrasound signal can be segmented along the depth, and the signal energy at multiple segments (for each segment, such as the amplitude of the signal at each frequency)
  • the sum of the values, the sum of the squares of the amplitudes, and the sum of the decibel values corresponding to the amplitudes are used to determine the attenuation characteristics of the target tissue.
  • each segment is divided into n segments along the depth, n ⁇ 2, center depth d1, d2,..., dn, each segment length is ⁇ l, and the depth interval is ⁇ d.
  • Each segment contains signals of multiple frequencies.
  • the signal energy of each segment is obtained, the signal energy of multiple segments is linearly fitted, and the fitted slope is obtained.
  • the slope is divided by the center frequency to obtain the attenuation characteristics corresponding to the target tissue.
  • the center frequency can be obtained through frequency analysis, such as Fourier transform, wavelet transform, etc.
  • the obtained center frequency is the frequency of the signal with the largest amplitude corresponding to each frequency signal.
  • a one-dimensional signal it can be segmented according to depth lines; for two-dimensional, it can be divided into multiple lines and segmented by lines, for example, each column of pixels is a line, and there are multiple lines.
  • Compose a two-dimensional ultrasound signal which can also be segmented according to small pieces of the ultrasound signal map; for three-dimensional, it can be divided into multiple lines, segmented by lines, or divided according to the volume of the ultrasound signal map
  • the segment can be specifically set according to actual needs, and is not limited in this embodiment.
  • the attenuation characteristics of the target tissue at each frequency can also be calculated separately.
  • the center frequency is the frequency.
  • the center frequency is 3MHz; for multiple frequencies, the center frequency is the frequency of the signal with the largest amplitude, for example, frequency There are five frequencies of 1MHz, 2MHz, 3MHz, 4MHz, and 5MHz.
  • the signal frequency with the largest amplitude is 4MHz, and the center frequency is 4MHz.
  • calculating and obtaining the signal energy of each segment of the ultrasonic signal includes:
  • Step 2011 For each ultrasonic signal, calculate the sub-signal energy of the signal of each frequency therein.
  • step 2012 the sum of the energy of each sub-signal is used as the signal energy of the ultrasonic signal.
  • calculating and obtaining the signal energy of each segment of the ultrasonic signal includes:
  • step 2021 the signal energy of each segment of the ultrasound signal is obtained in a time domain manner.
  • calculating and obtaining the signal energy of each segment of the ultrasonic signal includes:
  • Step 2031 Obtain the signal energy of each segment of the ultrasound signal in the frequency domain.
  • the overall process of acquiring the signal energy of each segment of the ultrasound signal in the time domain method and the frequency domain method is the same as the above process.
  • the difference is that in the frequency domain method, short-time Fourier transform of the target ultrasound signal is required. Calculate the signal energy at multiple segments, and the other parts are the same, so I won't repeat them here.
  • determining the attenuation characteristics of the target tissue according to the signal energy of each segment of the ultrasound signal includes:
  • Step 2041 Perform linear fitting processing on the signal energy of each segment of the ultrasonic signal to obtain the slope after fitting.
  • Step 2042 Divide the fitted slope by the center frequency of the target ultrasound signal to obtain the attenuation characteristics of the target tissue.
  • the center frequency is the frequency of the signal with the largest amplitude among the signals of each frequency.
  • the center frequency can be obtained through frequency analysis, such as Fourier transform, wavelet transform, etc.
  • the obtained center frequency is the frequency of the signal with the largest amplitude corresponding to each frequency signal.
  • the attenuation characteristics of the target tissue at each frequency can also be calculated separately.
  • the center frequency is the frequency.
  • the center frequency is 3MHz; for multiple frequencies, the center frequency is the frequency of the signal with the largest amplitude, for example, frequency There are five frequencies of 1MHz, 2MHz, 3MHz, 4MHz, and 5MHz.
  • the signal frequency with the largest amplitude is 4MHz, and the center frequency is 4MHz.
  • obtaining a dynamic broadband target ultrasound signal corresponding to the target tissue may specifically include:
  • Step 1011 Obtain a dynamic broadband original ultrasound signal.
  • Step 1012 Perform data calibration processing on the original ultrasound signal to obtain a calibrated signal.
  • Step 1013 Extract the component of interest based on the calibrated signal and use it as the target ultrasound signal.
  • a dynamic broadband ultrasound probe can be used to detect the target tissue, obtain a dynamic broadband original ultrasound signal, and perform certain processing on the original ultrasound signal to obtain a dynamic broadband target ultrasound signal corresponding to the target tissue.
  • the bandwidth of the ultrasound probe is 60%-200%, and the related signal frequency is 0.5MHz-50MHz.
  • the related signal frequency is not limited to ultrasound probes in this frequency range, but can also be ultrasound probes in other ranges, such as for aerial or geological purposes.
  • the reviews include 20Hz-0.5MHz.
  • the ultrasound probe is connected with the ultrasound imaging device to collect the ultrasound echo signal or the transmitted wave signal of the target tissue, which is referred to as the original ultrasound signal in the embodiment of the present application.
  • the original ultrasound signal can be one-dimensional, two-dimensional, three-dimensional, etc., which are specifically set according to actual needs.
  • the ultrasound imaging device may include a transmitting device, a receiving device, an imaging processing device, and the like. Because it is a dynamic broadband ultrasound probe, the acquired original ultrasound signal includes signals of at least two frequencies.
  • data calibration can be performed on the original ultrasound signal, and processing such as extraction of components of interest can be performed to obtain the target ultrasound signal.
  • Data calibration is due to the directivity of the ultrasound probe itself, the focus configuration or setting of the probe, the sensitivity of the probe, the gain of the system and other signal processing methods that affect the acquired original ultrasound signal.
  • the original ultrasound signal needs to be calibrated to restore the original
  • the specific data calibration process can be set according to the hardware, software and algorithm process of the ultrasound equipment.
  • Extracting the components of interest specifically refers to extracting the information of interest from the original ultrasound signal.
  • the original ultrasound signal obtained may include the ultrasound signal of the subcutaneous tissue and the ultrasound signal of the liver tissue.
  • the ultrasonic signal is extracted from the original ultrasonic signal.
  • the original ultrasound signal includes the frequency range of 1-20MHz. According to actual experience, the frequency is too high to reach the target tissue and has been seriously attenuated, so it cannot be effective.
  • the 1-5MHz range can be extracted from the original ultrasound signal.
  • a dynamic broadband target ultrasound signal corresponding to the target tissue can be obtained through certain processing.
  • frequency filtering or wavelet decomposition may also be used to obtain signals of different frequencies of the original ultrasound signal.
  • evaluating the target tissue according to the attenuation characteristics of the target tissue may specifically include:
  • Step 1031 Determine the state of the target tissue, the normal state and the abnormal state according to the attenuation characteristics of the target tissue.
  • the target tissue can be evaluated and processed according to the attenuation characteristics of the target tissue.
  • the state of the target tissue can be judged according to the attenuation characteristics of the target tissue.
  • the state may include a normal state and an abnormal state.
  • the abnormal state may include the abnormality type and the corresponding abnormality level.
  • the target tissue is liver tissue
  • the reference attenuation feature or reference attenuation feature range corresponding to the normal state of liver tissue can be obtained in advance, and the reference attenuation feature or reference attenuation feature corresponding to different lesion levels under different lesion types Range, compare the attenuation characteristic of the target tissue with the preset reference attenuation characteristic range.
  • the reference attenuation characteristic range corresponding to the attenuation characteristic of the target tissue is determined by the target tissue, such as the attenuation characteristic of the target liver tissue. If it belongs to the reference attenuation characteristic range corresponding to the normal liver, the target tissue is determined to be in a normal state.
  • the target tissue is determined to be mild fatty liver, etc. Wait.
  • the specific status and level can be set according to the actual situation of different organizations, which is not limited in this embodiment.
  • the abnormal level reflects the degree of tissue lesions.
  • the type of lesion indicates what kind of abnormality has occurred in the tissue.
  • the abnormal types of liver tissue include fatty liver, tumor, etc.
  • the abnormal grades corresponding to fatty liver include mild fatty liver, moderate fatty liver, severe fatty liver, and so on.
  • the specific abnormality type and abnormality level can be set according to the actual situation of different organizations, which is not limited in this embodiment.
  • display processing may be performed, which specifically may be displaying the value or displaying the value in a pseudo-color map, which may be specifically set according to actual requirements, which is not limited in this embodiment.
  • the ultrasonic signal processing method provided in this embodiment determines the attenuation characteristics of the target tissue based on the dynamic broadband target ultrasonic signal, and evaluates the target tissue according to the attenuation characteristics of the target tissue. Because the target tissue is integrated at multiple frequencies Ultrasound signal, which makes the signal components rich and diverse, improves the accuracy of the evaluation of the target tissue.
  • This embodiment provides an ultrasonic signal processing device for executing the method in the first embodiment.
  • the ultrasonic signal processing device 30 includes an acquisition module 31, a determination module 32 and a processing module 33.
  • the acquisition module 31 is used to acquire the dynamic broadband target ultrasound signal corresponding to the target tissue; the determination module 32 is used to determine the attenuation characteristics of the target tissue according to the target ultrasound signal; the processing module 33 is used to determine the attenuation characteristics of the target tissue according to the attenuation characteristics of the target tissue Organize the evaluation process.
  • the attenuation characteristics of the target tissue are determined based on the dynamic broadband target ultrasonic signal, and the target tissue is evaluated and processed according to the attenuation characteristics of the target tissue.
  • the ultrasound signal under the signal makes the signal components rich and diverse and improves the accuracy of the evaluation of the target tissue.
  • This embodiment further supplements the device provided in the third embodiment to implement the method provided in the second embodiment.
  • the target ultrasonic signal includes a signal of at least one frequency
  • the attenuation characteristics of the target tissue are determined.
  • determine the module specifically for:
  • the sum of the energy of each sub-signal is regarded as the signal energy of the ultrasonic signal.
  • determine the module specifically for:
  • the frequency domain method is used to obtain the signal energy of each segment of the ultrasonic signal.
  • determine the module specifically for:
  • the fitted slope is divided by the center frequency of the target ultrasound signal to obtain the attenuation characteristics of the target tissue.
  • the center frequency is the frequency of the signal with the largest amplitude among the signals of each frequency.
  • the acquisition module is specifically used for:
  • the components of interest are extracted to obtain the target ultrasound signal.
  • the processing module is specifically used for:
  • the state of the target tissue is determined.
  • the state includes normal state and abnormal state.
  • the attenuation characteristics of the target tissue are determined based on the dynamic broadband target ultrasonic signal, and the target tissue is evaluated and processed according to the attenuation characteristics of the target tissue. Because the target tissue is integrated at multiple frequencies Ultrasound signal, which makes the signal components rich and diverse, improves the accuracy of the evaluation of the target tissue.
  • This embodiment provides a computer device for executing the method provided in the foregoing embodiment.
  • the computer device 50 includes: at least one processor 51 and a memory 52;
  • the memory stores a computer program; at least one processor executes the computer program stored in the memory to implement the methods provided in the foregoing embodiments.
  • the attenuation characteristics of the target tissue are determined based on the dynamic broadband target ultrasound signal, and the target tissue is evaluated according to the attenuation characteristics of the target tissue. Because the ultrasonic waves of the target tissue at multiple frequencies are integrated The signal makes the signal components rich and diverse and improves the accuracy of the evaluation of the target organization.
  • This embodiment provides a computer-readable storage medium in which a computer program is stored, and when the computer program is executed, the method provided in any of the above-mentioned embodiments is implemented.
  • the attenuation characteristics of the target tissue are determined according to the dynamic broadband target ultrasound signal, and the target tissue is evaluated according to the attenuation characteristics of the target tissue.
  • the ultrasound signal under the signal makes the signal components rich and diverse and improves the accuracy of the evaluation of the target tissue.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or It can be integrated into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit may be implemented in the form of hardware, or may be implemented in the form of hardware plus software functional units.
  • the above-mentioned integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium.
  • the above-mentioned software functional unit is stored in a storage medium and includes several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor execute the method described in the various embodiments of the present application. Part of the steps.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code .

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Abstract

一种超声信号处理方法、装置（30）、计算机设备（50）及存储介质。该方法包括：获取目标组织对应的动态宽频的目标超声信号（101）；根据目标超声信号，确定目标组织的衰减特征（102）；根据目标组织的衰减特征，对目标组织进行评价处理（103）。通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分多样，提高了对目标组织评价的准确性。

Description

超声信号处理方法、装置、设备及存储介质 技术领域
本申请涉及超声技术领域，尤其涉及一种超声信号处理方法、装置、设备及存储介质。
背景技术
随着科技的进步，超声成像技术在各领域广泛被应用，并且因其具有实时、廉价、非侵入性和非电离辐射等优点而广泛应用与临床诊断，定量超声可以为临床医生提供非常直观的定量评价，比如弹性、血流等。
但是，定量超声与超声本身的信号特性相关，并且容易受到组织中或周围其他信号的干扰。因此，如何采用超声技术准确地判断目标组织的状态，成为亟需解决的技术问题。
发明内容
本申请提供一种超声信号处理方法、装置、设备及存储介质，以解决现有技术对目标组织的状态判断不准确等缺陷。
本申请第一个方面提供一种超声信号处理方法，包括：
获取目标组织对应的动态宽频的目标超声信号；
根据所述目标超声信号，确定所述目标组织的衰减特征；
根据所述目标组织的衰减特征，对所述目标组织进行评价处理。
本申请第二个方面提供一种超声信号处理装置，包括：
获取模块，用于获取目标组织对应的动态宽频的目标超声信号；
确定模块，用于根据所述目标超声信号，确定所述目标组织的衰减特征；
处理模块，用于根据所述目标组织的衰减特征，对所述目标组织进行评价处理。
本申请第三个方面提供一种计算机设备，包括：至少一个处理器和存储器；
所述存储器存储计算机程序；所述至少一个处理器执行所述存储器存储的计算机程序，以实现第一个方面提供的方法。
本申请第四个方面提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，所述计算机程序被执行时实现第一个方面提供的方法。
本申请提供的超声信号处理方法、装置、设备及存储介质，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本申请一实施例提供的超声信号处理方法的流程示意图；
图2为本申请另一实施例提供的超声信号处理方法的流程示意图；
图3为本申请一实施例提供的超声信号处理装置的结构示意图；
图4为本申请一实施例提供的计算机设备的结构示意图。
通过上述附图，已示出本申请明确的实施例，后文中将有更详细的描述。这些附图和文字描述并不是为了通过任何方式限制本公开构思的范围，而是通过参考特定实施例为本领域技术人员说明本申请的概念。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例提供的超声信号处理方法，适用于采用动态宽频探头探测目标组织，获得目标组织的动态宽频的超声信号，并基于目标组织的动态宽频的超声信号，判断目标组织的状态的场景。目标组织可以为肝脏组织、肌 肉组织、脂肪组织、乳腺组织、甲状腺组织以及其他组织等等，具体不做限定。目标组织的状态可以为正常状态或病变状态，若为病变状态还可以包括病变类型及对应的病变等级。比如肝脏组织，病变状态包括脂肪肝、肿瘤等，脂肪肝可以包括轻度脂肪肝、中度脂肪肝、重度脂肪肝等等。具体病变等级可以根据实际需求设置，本申请实施例不做限定。
此外，术语“第一”、“第二”等仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。在以下各实施例的描述中，“多个”的含义是两个以上，除非另有明确具体的限定。
下面这几个具体的实施例可以相互结合，对于相同或相似的概念或过程可能在某些实施例中不再赘述。下面将结合附图，对本发明的实施例进行描述。
实施例一
本实施例提供一种超声信号处理方法，用于对动态宽频的超声信号进行处理，以判断目标组织的状态。本实施例的执行主体为超声信号处理装置，该装置可以设置在计算机设备中。
如图1所示，为本实施例提供的超声信号处理方法的流程示意图，该方法包括：
步骤101，获取目标组织对应的动态宽频的目标超声信号。
具体的，可以通过动态宽频超声探头来探测目标组织，获得动态宽频的原始超声信号，并对原始超声信号进行一定的处理，获得目标组织对应的动态宽频的目标超声信号。
其中，动态宽频是指超声探头可工作的信号带宽范围比较宽，探头的中心频率动态可调。具体的，所述宽频通常是指超声探头可工作的信号频率与中心频率的比值大于等于60％。相应的，动态宽频的目标超声信号是指采用宽频的探头在不同的中心频率激励下探测目标组织获得的超声信号。
示例性的，在医疗领域中，超声探头带宽与中心频率的比值大于60％，涉及信号频率为0.1MHz-100MHz，当然，不限于这种频率范围的超声探头，也可以是其他范围的超声探头，比如对于空中或地质方面，则频率包括20Hz-0.5MHz。比如超声探头的频率范围为1MHz-10MHz，则超声探头的带宽 为9MHz，若中心频率为5MHz，则该超声探头带宽与中心频率的比值为9/5*100％＝180％。
目标组织可以为肝脏组织、肌肉组织、脂肪组织、乳腺组织或甲状腺组织等人体或动物组织，也可以是空中或地质等方面的组织，本实施例不做限定。
超声探头与超声成像装置连接，实现采集目标组织的超声回波信号或透射波信号，本申请实施例称为原始超声信号。原始超声信号可以是一维、二维、三维等，具体根据实际需求设置。超声成像装置可以包括发射装置、接收装置、成像处理装置等。因为是动态宽频超声探头，采集获得的原始超声信号包括至少一种频率的信号，即可以包括多种频率的信号。
可选地，可以对原始超声信号进行数据校准，以及对感兴趣成分的提取等处理，来获得目标超声信号。数据校准是由于超声探头本身具有指向性、探头的聚焦配置或设置、探头灵敏度、系统增益及其他信号处理手段等对采集的原始超声信号的影响，需要对原始超声信号进行校准，用于恢复原始的超声信号，具体的数据校准处理过程可以根据超声设备的硬件、软件及算法处理过程进行设置。
提取感兴趣成分具体是指对原始超声信号提取出感兴趣的信息，比如在对肝脏组织进行探测时，获得的原始超声信号可能包括皮下组织的超声信号和肝脏组织的超声信号，需要将肝脏组织的超声信号从原始超声信号中提取出来。再比如，原始超声信号，包括1-20MHz的频率范围，根据实际经验，频率太高到达目标组织时已衰减严重，因此起不到有效作用，可以从原始超声信号中提取出1-5MHz范围的超声信号，作为目标超声信号，等等。具体可以根据实际情况处理，本实施例不做限定。
采集获得原始超声信号后，通过一定的处理即可获得目标组织对应的动态宽频的目标超声信号。
可选地，在获得原始超声信号后，还可以采用频率滤波或小波分解等方式获得原始超声信号的不同频率的信号。
步骤102，根据目标超声信号，确定目标组织的衰减特征。
具体的，在获取到目标组织对应的动态宽频的目标超声信号后，则可以根据目标超声信号，确定目标组织的衰减特征。
可选地，可以对目标超声信号沿深度进行分段，通过计算多段处的信号能量(对于每段来说，比如各频率的信号的幅值的和、幅值的平方和、幅值对应的分贝值的和等等)，来确定目标组织的衰减特征。其中，幅值对应的分贝值是指对幅值进行对数压缩处理获得的分贝DB值。
示例性的，沿深度分为n段，n≥2，中心深度d1,d2,…,dn，每段长度为△l，深度间隔为△d。每段都包含多种频率的信号。
在获得每段的信号能量后，将多段的信号能量进行线性拟合，并获得拟合后的斜率，将斜率除以中心频率，即获得目标组织对应的衰减特征。其中，中心频率可以通过频率分析获得，比如傅里叶变换、小波变换等方式。获得的中心频率为各频率信号对应的幅值最大的信号的频率。
示例性的，对于一维可以采用一维线性拟合，对于二维可以采用最小二乘拟合，对于三维可以采用三次样条拟合等等，具体拟合方式为现有技术，在此不再赘述。
可选地，也可以分别计算目标组织在每种频率下的衰减特征。对于单频率情况，中心频率即为该频率，比如只计算目标组织在3MHz下的衰减特征，则中心频率即为3MHz；对于多频率情况，中心频率为幅值最大的信号的频率，比如，频率包括1MHz、2MHz、3MHz、4MHz、5MHz五种频率，其中幅值最大的信号频率为4MHz，则中心频率为4MHz。
步骤103，根据目标组织的衰减特征，对目标组织进行评价处理。
具体的，在确定了目标组织的衰减特征后，则可以根据目标组织的衰减特征对目标组织进行评价处理。
示例性的，可以根据目标组织的衰减特征，判断目标组织的状态。该状态可以包括正常状态和异常状态。
可选地，其中，异常状态可以包括异常类型和对应的异常等级。
示例性的，目标组织以肝脏组织为例，可以预先获得肝脏组织正常状态对应的参考衰减特征或参考衰减特征范围、不同病变类型下不同病变等级对应的参考衰减特征或参考衰减特征范围，将目标组织的衰减特征与预设的参考衰减特征范围进行比对，目标组织的衰减特征处于哪种情况对应的参考衰减特征范围则确定目标组织属于哪种情况，比如目标肝脏组织衰减特征属于正常肝脏对应的参考衰减特征范围，则确定目标组织为正常状态，若属于脂 肪肝病变类型下的轻度脂肪肝病变等级对应的参考衰减特征范围，则确定目标组织为轻度脂肪肝，等等。这里只是示例性说明，具体的状态和等级可以根据不同组织的实际情况进行设置，本实施例不做限定。其中，异常等级体现了组织的病变的程度。病变类型表示组织产生了哪类异常，比如肝脏组织的异常类型有脂肪肝、肿瘤等，脂肪肝对应的异常等级包括轻度脂肪肝、中度脂肪肝、重度脂肪肝等等。具体异常类型和异常等级可以根据不同组织的实际情况来设置，本实施例不做限定。
本实施例提供的超声信号处理方法，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
实施例二
本实施例对实施例一提供的方法做进一步补充说明。
如图2所示，为本实施例提供的超声信号处理方法的流程示意图。
作为一种可实施的方式，在上述实施例一的基础上，可选地，目标超声信号包括至少一种频率的信号。步骤102具体包括：
步骤1021，沿深度方向将目标超声信号进行分段处理，获得至少两段超声信号。
步骤1022，计算获得各段超声信号的信号能量。
步骤1023，根据各段超声信号的信号能量，确定目标组织的衰减特征。
具体的，在获取到目标组织对应的动态宽频的目标超声信号后，可以对目标超声信号沿深度进行分段，通过计算多段处的信号能量(对于每段来说，比如各频率的信号的幅值的和、幅值的平方和、幅值对应的分贝值的和等待)，来确定目标组织的衰减特征。
示例性的，沿深度分为n段，n≥2，中心深度d1,d2,…,dn，每段长度为△l，深度间隔为△d。每段都包含多种频率的信号。
在获得每段的信号能量后，将多段的信号能量进行线性拟合，并获得拟合后的斜率，将斜率除以中心频率，即获得目标组织对应的衰减特征。其中，中心频率可以通过频率分析获得，比如傅里叶变换、小波变换等方式。获得 的中心频率为各频率信号对应的幅值最大的信号的频率。
可选地，对于一维的信号，可以是按照深度线进行分段；对于二维，可以划分为多条线，按线进行分段，比如按照像素的每一列为一条线，由多条线组成了二维的超声信号，也可以是按超声信号图的小块进行分段；对于三维，可以是划分为多条线，按线进行分段，也可以是按照超声信号图的体积进行分段，具体可以根据实际需求设置，本实施例不做限定。
可选地，也可以分别计算目标组织在每种频率下的衰减特征。对于单频率情况，中心频率即为该频率，比如只计算目标组织在3MHz下的衰减特征，则中心频率即为3MHz；对于多频率情况，中心频率为幅值最大的信号的频率，比如，频率包括1MHz、2MHz、3MHz、4MHz、5MHz五种频率，其中幅值最大的信号频率为4MHz，则中心频率为4MHz。
示例性的，n＝5，在d1＝1cm处的信号能量为500、d2＝2cm处为400、d3＝3cm处为300、d4＝4cm处为200、d5＝5cm处为100，则进行线性拟合，获得斜率为100/cm，获得的中心频率为4MHz，则斜率除以中心频率获得的衰减特征为25/cm/MHz。这里只是示例性说明，并非对其限定。
可选地，计算获得各段超声信号的信号能量，包括：
步骤2011，对于每段超声信号，计算其中各频率的信号的子信号能量。
步骤2012，将各子信号能量之和作为该段超声信号的的信号能量。
可选地，计算获得各段超声信号的信号能量，包括：
步骤2021，采用时域方式获取各段超声信号的信号能量。
可选地，计算获得各段超声信号的信号能量，包括：
步骤2031，采用频域方式获取各段超声信号的信号能量。
具体的，时域方式和频域方式获取各段超声信号的信号能量的整体过程与上述过程一致，不同之处在于，频域方式下，需要对目标超声信号进行短时傅里叶变换，来计算多段处的信号能量，其他部分一致，在此不再赘述。
可选地，根据各段超声信号的信号能量，确定目标组织的衰减特征，包括：
步骤2041，对各段超声信号的信号能量进行线性拟合处理，获得拟合后的斜率。
步骤2042，将拟合后的斜率除以目标超声信号的中心频率，获得目标组 织的衰减特征。
其中，中心频率为各频率的信号中幅值最大的信号的频率。
具体的，在获得每段的信号能量后，将多段的信号能量进行线性拟合，并获得拟合后的斜率，将斜率除以中心频率，即获得目标组织对应的衰减特征。其中，中心频率可以通过频率分析获得，比如傅里叶变换、小波变换等方式。获得的中心频率为各频率信号对应的幅值最大的信号的频率。
可选地，也可以分别计算目标组织在每种频率下的衰减特征。对于单频率情况，中心频率即为该频率，比如只计算目标组织在3MHz下的衰减特征，则中心频率即为3MHz；对于多频率情况，中心频率为幅值最大的信号的频率，比如，频率包括1MHz、2MHz、3MHz、4MHz、5MHz五种频率，其中幅值最大的信号频率为4MHz，则中心频率为4MHz。
示例性的，n＝5，在d1＝1cm处的信号能量为500、d2＝2cm处为400、d3＝3cm处为300、d4＝4cm处为200、d5＝5cm处为100，则进行线性拟合，获得斜率为100/cm，获得的中心频率为4MHz，则斜率除以中心频率获得的衰减特征为25/cm/MHz。这里只是示例性说明，并非对其限定。
作为另一种可实施的方式，在上述实施例一的基础上，可选地，获取目标组织对应的动态宽频的目标超声信号，具体可以包括：
步骤1011，获取动态宽频的原始超声信号。
步骤1012，对原始超声信号进行数据校准处理，获得校准后的信号。
步骤1013，根据校准后的信号，提取感兴趣成分，作为目标超声信号。
具体的，可以通过动态宽频超声探头来探测目标组织，获得动态宽频的原始超声信号，并对原始超声信号进行一定的处理，获得目标组织对应的动态宽频的目标超声信号。
示例性的，超声探头带宽为60％-200％，涉及信号频率为0.5MHz-50MHz，当然，不限于这种频率范围的超声探头，也可以是其他范围的超声探头，比如对于空中或地质方面，则评论包括20Hz-0.5MHz。
超声探头与超声成像装置连接，实现采集目标组织的超声回波信号或透射波信号，本申请实施例称为原始超声信号。原始超声信号可以是一维、二维、三维等，具体根据实际需求设置。超声成像装置可以包括发射装置、接收装置、成像处理装置等。因为是动态宽频超声探头，采集获得的原始超声 信号包括至少两种频率的信号。
可选地，可以对原始超声信号进行数据校准，以及对感兴趣成分的提取等处理，来获得目标超声信号。数据校准是由于超声探头本身具有指向性、探头的聚焦配置或设置、探头灵敏度、系统增益及其他信号处理手段等对采集的原始超声信号的影响，需要对原始超声信号进行校准，用于恢复原始的超声信号，具体的数据校准处理过程可以根据超声设备的硬件、软件及算法处理过程进行设置。
提取感兴趣成分具体是指对原始超声信号提取出感兴趣的信息，比如在对肝脏组织进行探测时，获得的原始超声信号可能包括皮下组织的超声信号和肝脏组织的超声信号，需要将肝脏组织的超声信号从原始超声信号中提取出来。再比如，原始超声信号，包括1-20MHz的频率范围，根据实际经验，频率太高到达目标组织时已衰减严重，因此起不到有效作用，可以从原始超声信号中提取出1-5MHz范围的超声信号，作为目标超声信号，等等。具体可以根据实际情况处理，本实施例不做限定。
采集获得原始超声信号后，通过一定的处理即可获得目标组织对应的动态宽频的目标超声信号。
可选地，在获得原始超声信号后，还可以采用频率滤波或小波分解等方式获得原始超声信号的不同频率的信号。
可选地，根据目标组织的衰减特征，对目标组织进行评价处理，具体可以包括：
步骤1031，根据目标组织的衰减特征，确定目标组织的状态，状态正常状态和异常状态。
具体的，在确定了目标组织的衰减特征后，则可以根据目标组织的衰减特征对目标组织进行评价处理。可以根据目标组织的衰减特征，判断目标组织的状态。该状态可以包括正常状态和异常状态。
可选地，其中，异常状态可以包括异常类型和对应的异常等级。
示例性的，示例性的，目标组织以肝脏组织为例，可以预先获得肝脏组织正常状态对应的参考衰减特征或参考衰减特征范围、不同病变类型下不同病变等级对应的参考衰减特征或参考衰减特征范围，将目标组织的衰减特征与预设的参考衰减特征范围进行比对，目标组织的衰减特征处于哪种情况对 应的参考衰减特征范围则确定目标组织属于哪种情况，比如目标肝脏组织衰减特征属于正常肝脏对应的参考衰减特征范围，则确定目标组织为正常状态，若属于脂肪肝病变类型下的轻度脂肪肝病变等级对应的参考衰减特征范围，则确定目标组织为轻度脂肪肝，等等。这里只是示例性说明，具体的状态和等级可以根据不同组织的实际情况进行设置，本实施例不做限定。其中，异常等级体现了组织的病变的程度。病变类型表示组织产生了哪类异常，比如肝脏组织的异常类型有脂肪肝、肿瘤等，脂肪肝对应的异常等级包括轻度脂肪肝、中度脂肪肝、重度脂肪肝等等。具体异常类型和异常等级可以根据不同组织的实际情况来设置，本实施例不做限定。
可选地，在获得目标组织的衰减特征后，可以进行显示处理，具体可以是显示数值或者把数值用伪彩图显示，具体可以根据实际需求设置，本实施例不做限定。
需要说明的是，本实施例中各可实施的方式可以单独实施，也可以在不冲突的情况下以任意组合方式结合实施本申请不做限定。
本实施例提供的超声信号处理方法，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
实施例三
本实施例提供一种超声信号处理装置，用于执行上述实施例一的方法。
如图3所示，为本实施例提供的超声信号处理装置的结构示意图。该超声信号处理装置30包括获取模块31、确定模块32和处理模块33。
其中，获取模块31用于获取目标组织对应的动态宽频的目标超声信号；确定模块32用于根据目标超声信号，确定目标组织的衰减特征；处理模块33用于根据目标组织的衰减特征，对目标组织进行评价处理。
关于本实施例中的装置，其中各个模块执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。
根据本实施例提供的超声信号处理装置，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进 行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
实施例四
本实施例对上述实施例三提供的装置做进一步补充说明，以执行上述实施例二提供的方法。
作为一种可实施的方式，在上述实施例三的基础上，可选地，目标超声信号包括至少一种频率的信号；
确定模块，具体用于：
沿深度方向将目标超声信号进行分段处理，获得至少两段超声信号；
计算获得各段超声信号的信号能量；
根据各段超声信号的信号能量，确定目标组织的衰减特征。
可选地，确定模块，具体用于：
对于每段超声信号，计算其中各频率的信号的子信号能量；
将各子信号能量的和作为该段超声信号的的信号能量。
可选地，确定模块，具体用于：
采用时域方式获取各段超声信号的信号能量；或者，
采用频域方式获取各段超声信号的信号能量。
可选地，确定模块，具体用于：
对各段超声信号的信号能量进行线性拟合处理，获得拟合后的斜率；
将拟合后的斜率除以目标超声信号的中心频率，获得目标组织的衰减特征，中心频率为各频率的信号中幅值最大的信号的频率。
作为另一种可实施的方式，在上述实施例三的基础上，可选地，获取模块，具体用于：
获取动态宽频的原始超声信号；
对原始超声信号进行数据校准处理，获得校准后的信号；
根据校准后的信号，提取感兴趣成分，获得目标超声信号。
作为另一种可实施的方式，在上述实施例三的基础上，可选地，处理模块，具体用于：
根据目标组织的衰减特征，确定目标组织的状态，状态包括正常状态和 异常状态。
关于本实施例中的装置，其中各个模块执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。
需要说明的是，本实施例中各可实施的方式可以单独实施，也可以在不冲突的情况下以任意组合方式结合实施本申请不做限定。
根据本实施例的超声信号处理装置，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
实施例五
本实施例提供一种计算机设备，用于执行上述实施例提供的方法。
如图4所示，为本实施例提供的计算机设备的结构示意图。该计算机设备50包括：至少一个处理器51和存储器52；
存储器存储计算机程序；至少一个处理器执行存储器存储的计算机程序，以实现上述实施例提供的方法。
根据本实施例的计算机设备，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
实施例六
本实施例提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，计算机程序被执行时实现上述任一实施例提供的方法。
根据本实施例的计算机可读存储介质，通过根据动态宽频的目标超声信号，确定目标组织的衰减特征，并根据目标组织的衰减特征对目标组织进行评价处理，由于综合了目标组织在多个频率下的超声信号，使得信号成分丰富多样，提高了对目标组织评价的准确性。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的， 例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元，可以存储在一个计算机可读取存储介质中。上述软件功能单元存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本申请各个实施例所述方法的部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的装置的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
最后应说明的是：以上各实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述各实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的范围。

Claims (16)

  1. 一种超声信号处理方法，其特征在于，包括：
    获取目标组织对应的动态宽频的目标超声信号；
    根据所述目标超声信号，确定所述目标组织的衰减特征；
    根据所述目标组织的衰减特征，对所述目标组织进行评价处理。
  2. 根据权利要求1所述的方法，其特征在于，所述目标超声信号包括至少一种频率的信号；
    所述根据所述目标超声信号，确定所述目标组织的衰减特征，包括：
    沿深度方向将所述目标超声信号进行分段处理，获得至少两段超声信号；
    计算获得各段超声信号的信号能量；
    根据各段超声信号的信号能量，确定所述目标组织的衰减特征。
  3. 根据权利要求2所述的方法，其特征在于，所述计算获得各段超声信号的信号能量，包括：
    对于每段超声信号，计算其中各频率的信号的子信号能量；
    将各子信号能量之和作为该段超声信号的信号能量。
  4. 根据权利要求2所述的方法，其特征在于，所述计算获得各段超声信号的信号能量，包括：
    采用时域方式获取各段超声信号的信号能量；或者，
    采用频域方式获取各段超声信号的信号能量。
  5. 根据权利要求2所述的方法，其特征在于，所述根据各段超声信号的信号能量，确定所述目标组织的衰减特征，包括：
    对各段超声信号的信号能量进行线性拟合处理，获得拟合后的斜率；
    将所述拟合后的斜率除以所述目标超声信号的中心频率，获得所述目标组织的衰减特征，所述中心频率为各频率的信号中幅值最大的信号的频率。
  6. 根据权利要求1所述的方法，其特征在于，所述获取目标组织对应的动态宽频的目标超声信号，包括：
    获取动态宽频的原始超声信号；
    对所述原始超声信号进行数据校准处理，获得校准后的信号；
    根据所述校准后的信号，提取感兴趣成分，作为所述目标超声信号。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，所述根据所述目 标组织的衰减特征，对所述目标组织进行评价处理，包括：
    根据所述目标组织的衰减特征，确定所述目标组织的状态，所述状态包括正常状态和异常状态。
  8. 一种超声信号处理装置，其特征在于，包括：
    获取模块，用于获取目标组织对应的动态宽频的目标超声信号；
    确定模块，用于根据所述目标超声信号，确定所述目标组织的衰减特征；
    处理模块，用于根据所述目标组织的衰减特征，对所述目标组织进行评价处理。
  9. 根据权利要求8所述的装置，其特征在于，所述目标超声信号包括至少一种频率的信号；
    所述确定模块，具体用于：
    沿深度方向将所述目标超声信号进行分段处理，获得至少两段超声信号；
    计算获得各段超声信号的信号能量；
    根据各段超声信号的信号能量，确定所述目标组织的衰减特征。
  10. 根据权利要求9所述的装置，其特征在于，所述确定模块，具体用于：
    对于每段超声信号，计算其中各频率的信号的子信号能量；
    将各子信号能量之和作为该段超声信号的的信号能量。
  11. 根据权利要求9所述的装置，其特征在于，所述确定模块，具体用于：
    采用时域方式获取各段超声信号的信号能量；或者，
    采用频域方式获取各段超声信号的信号能量。
  12. 根据权利要求9所述的装置，其特征在于，所述确定模块，具体用于：
    对各段超声信号的信号能量进行线性拟合处理，获得拟合后的斜率；
    将所述拟合后的斜率除以所述目标超声信号的中心频率，获得所述目标组织的衰减特征，所述中心频率为各频率的信号中幅值最大的信号的频率。
  13. 根据权利要求8所述的装置，其特征在于，所述获取模块，具体用于：
    获取动态宽频的原始超声信号；
    对所述原始超声信号进行数据校准处理，获得校准后的信号；
    根据所述校准后的信号，提取感兴趣成分，作为所述目标超声信号。
  14. 根据权利要求8-13任一项所述的装置，其特征在于，所述处理模块，具体用于：
    根据所述目标组织的衰减特征，确定所述目标组织的状态，所述状态包括正常状态和异常状态。
  15. 一种计算机设备，其特征在于，包括：至少一个处理器和存储器；
    所述存储器存储计算机程序；所述至少一个处理器执行所述存储器存储的计算机程序，以实现权利要求1-7中任一项所述的方法。
  16. 一种计算机可读存储介质，其特征在于，该计算机可读存储介质中存储有计算机程序，所述计算机程序被执行时实现权利要求1-7中任一项所述的方法。
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