Detection probe and ultrasonic detection system

Abstract

The utility model discloses a kind of detection probe and ultrasonic detection system.The detection probe includes shell;Sound head, installation in the shell;Sensor pair, the sensor pair is installed in the shell or the shell outer wall, the sensor pair includes two pressure sensors, two the sensor is symmetrically distributed in the both sides of sound head, and the force part of the pressure sensor protrudes from the sound head.Detection probe when detecting to be measured area, the force part of pressure sensor can be directly contacted with to be measured area, avoid the influence of the structure in the detection probe to pressure sensor, improve the accuracy of detection result.

Description

Technical Field

[0001] This utility model relates to the field of medical equipment technology, and more specifically, to a detection probe and an ultrasonic detection system. Background Technology

[0002] In related technologies, ultrasound elastography equipment includes a detection probe. When elastography is applied clinically, a physician must hold the probe to perform the elastography scan. The detection probe typically includes an acoustic head and a pressure sensor. The acoustic head contacts and compresses the area being tested, transmitting force to the pressure sensor. The pressure sensor then transmits the sensed pressure data to the mainboard for pressure detection. However, current detection probes often contain internal electronic components (e.g., circuit boards or adapters) that can significantly interfere with the acoustic head, affecting the pressure data sensed by the pressure sensor and thus the detection results.

[0003] Therefore, a new technical solution is needed to solve the above-mentioned technical problems. Utility Model Content

[0004] One objective of this invention is to provide a new technical solution for a detection probe.

[0005] According to a first aspect of the present invention, a detection probe is provided. The detection probe includes:

[0006] case;

[0007] The sound head is installed inside the housing;

[0008] A sensor pair is installed inside the housing or on the outer wall of the housing. The sensor pair includes two pressure sensors, which are symmetrically distributed on both sides of the sound head, and the force-receiving part of the pressure sensor protrudes from the sound head.

[0009] Optionally, it also includes:

[0010] Mounting base, the mounting base being connected to the outer wall of the housing near the sound head end;

[0011] The mounting base is provided with mounting positions for mounting the sensor pair;

[0012] The connection between the mounting base and the outer wall of the housing near the sound head end can be either a fixed connection or a movable connection.

[0013] Optionally, multiple sensor pairs are provided, and the multiple sensor pairs are arranged in a centrally symmetrical manner with the sound head as the center.

[0014] Optionally, it also includes a flexible element connected to the housing, the flexible element being able to cover the pressure sensor, and the flexible element being able to protrude from the sound head.

[0015] Optionally, the pressure sensor has a first detection end that protrudes from the sound head, and the flexible element covers the first detection end.

[0016] Optionally, the pressure sensor has a first detection end, which is flush with the acoustic head, and the flexible member covers the first detection end and protrudes from the acoustic head.

[0017] Optionally, it also includes a coupling patch, which is disposed on the second detection end of the sound head and has a clearance structure for the first detection end of the pressure sensor, so that the flexible member covering the first detection end is flush with the coupling patch covering the second detection end of the sound head.

[0018] Optionally, the thickness of the coupling patch is less than or equal to 5 mm, and / or the ultrasonic attenuation coefficient of the coupling patch is less than or equal to 1 dB / cm / MHz, and / or the density of the coupling patch is less than or equal to 1.5 g / cm³. 3 .

[0019] According to a second aspect of this application, an ultrasound detection system is provided. The ultrasound detection system includes an elastography module, a blood flow imaging module, an ultrasound imaging module, and the detection probe described in the above embodiments, as well as a robotic arm, wherein:

[0020] The elastic imaging function module is used to perform elastic detection according to the elastic detection control signal to obtain elastic detection parameters;

[0021] The blood flow imaging function module is used to perform blood flow detection according to the blood flow detection control signal to obtain blood flow detection parameters;

[0022] The ultrasonic imaging function module is used to perform ultrasonic detection according to the ultrasonic detection control signal to obtain ultrasonic detection parameters;

[0023] The elastic imaging module and / or the ultrasonic imaging module also perform detection area identification according to the positioning control signal and send the location information to the control module;

[0024] The control module is configured to send positioning control information to the elastic imaging function module and / or the ultrasound imaging function module, and determine the current position of the detection probe and the position of the target detection area based on the received position information, and send a first movement control command to the robotic arm based on the difference information between the two positions; when it is determined that the detection probe has reached the target detection area based on the received position information, it sequentially sends a plurality of corresponding second movement control commands to the robotic arm based on a plurality of preset pressure values ​​within the target pressure range; and after sending each second movement control command, it simultaneously or sequentially sends the elastic detection control signal, the blood flow detection control signal and / or the ultrasound detection control signal.

[0025] The robotic arm controls the detection probe to move to the target detection area according to the first movement control command, and controls the detection probe to press down vertically according to the second movement control command.

[0026] Optionally, the elastic detection parameters include the group velocity, phase velocity, attenuation coefficient, dispersion characteristics, and / or anisotropy of the shear wave;

[0027] The blood flow detection parameters include vascular density, blood flow velocity, blood flow velocity gradient, vascular tortuosity, and / or blood flow resistance index;

[0028] The ultrasonic detection parameters include scattering, attenuation, scatterer distribution characteristics, and / or nonlinear acoustic parameters.

[0029] Optionally, it also includes an inflammation severity assessment module, wherein:

[0030] The control module is further configured to send an inflammation detection signal to the inflammation severity assessment module after sending each of the second movement control commands;

[0031] The inflammation severity assessment module is loaded with an inflammation severity training model, and obtains the elasticity detection parameters, the blood flow detection parameters, and / or the ultrasound detection parameters based on the inflammation detection signal, and generates inflammation severity information based on the inflammation severity training model;

[0032] The inflammation degree training model is based on the data of the test subjects and the correspondence between the elasticity detection parameters, the blood flow detection parameters, and / or the ultrasound detection parameters and the inflammation degree information, established by the tissue inflammation degree information obtained from pathological examination.

[0033] Optionally, the control module further assesses the likelihood of inflammation based on user input information indicating abnormal tissue condition during clinical examination and / or blood test parameters indicative of inflammation. Only if inflammation is confirmed will an inflammation detection signal be sent to the inflammation severity assessment module; and / or,

[0034] The inflammation severity training model was obtained by selecting sample data for different causes and training it.

[0035] Optionally, the user may be instructed with the elasticity detection parameters, the blood flow detection parameters, the ultrasound detection parameters, and / or the inflammation level information;

[0036] The methods for instructing users include one or more of the following:

[0037] The screen text display method includes: displaying the specific values ​​or status descriptions of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information in text form on the display screen;

[0038] The sound reminder method includes: emitting a preset sound signal through an audio output device, including audio broadcasting or a specific tone, to prompt the user to pay attention to the abnormal or specific state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information;

[0039] Different color graphic display methods include: using graphic elements of different colors or color combinations on the display screen to represent the relative size, trend of change or abnormal state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information, wherein each color or color combination corresponds to a specific parameter range or state category;

[0040] Different colored indicator light display methods include: using indicator light elements of different colors or color combinations to represent the relative magnitude, trend of change, or abnormal state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information, wherein each color or color combination corresponds to a specific parameter range or state category.

[0041] Optionally, it also includes an organization status assessment module, wherein:

[0042] The tissue condition assessment module is loaded with a tissue condition assessment model, which is used to assess tissue condition based on the elasticity detection parameters, the blood flow detection parameters, the ultrasound detection parameters, and / or inflammation degree information.

[0043] Indicate the assessed organizational status to the user;

[0044] The methods for instructing users include one or more of the following:

[0045] The screen text display method includes: displaying the specific score value or status description of the organization status in text form on the display screen;

[0046] The sound reminder method includes: emitting a preset sound signal through an audio output device, including audio broadcasting or a specific tone, to prompt the user to pay attention to the organizational status;

[0047] Different color graphic display methods include: using graphic elements of different colors or color combinations on a display screen to represent the organizational state;

[0048] Different colored indicator light display methods include: using indicator light elements of different colors or color combinations to indicate the organizational status.

[0049] Optionally, the method for constructing the organizational status assessment model includes:

[0050] Collect information on known tissue states and their corresponding viscoelastic parameters, blood flow parameters, quantitative ultrasound parameters, and tissue inflammation levels, and preprocess the data;

[0051] Select a machine learning model based on task requirements and data characteristics;

[0052] Train the model;

[0053] After the model training is completed, evaluate the model's prediction accuracy;

[0054] Based on the evaluation results, adjustments may be made to the model structure, parameter settings, or data preprocessing methods.

[0055] One technical advantage of this application is that the sound head is installed inside the housing, and the sensor pair is installed inside the housing or on the outer wall of the housing. The sensor pair includes two pressure sensors, which are symmetrically distributed on both sides of the sound head. The force-bearing part of the pressure sensor protrudes from the sound head. When the detection probe detects the area to be measured, the force-bearing part of the pressure sensor can directly contact the area to be measured, avoiding the influence of the internal structure of the detection probe on the pressure sensor and improving the accuracy of the detection results.

[0056] Other features and advantages of the present invention will become clear from the following detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings. Attached Figure Description

[0057] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the present invention and, together with their description, serve to explain the principles of the present invention.

[0058] Figure 1 This is a schematic diagram of the structure of a detection probe according to an embodiment of this application.

[0059] Figure 2 This is a schematic diagram of the structure of a detection probe according to another embodiment of this application.

[0060] Figure 3 This is a flowchart of a detection method according to an embodiment of this application.

[0061] Figure 4 This is a flowchart of a method for constructing an organizational status assessment model according to an embodiment of this application.

[0062] Figure label:

[0063] 1. Sound head; 2. Flexible component; 3. Housing; 4. Pressure sensor; 5. Connector; 6. Main board. Detailed Implementation

[0064] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0065] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0066] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0067] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0068] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0069] According to one embodiment of this application, a detection probe is provided. For example... Figure 1 and Figure 2 As shown, the detection probe includes a housing 3, a sound head 1, and a sensor pair. The sound head 1 is installed inside the housing 3. The sensor pair is installed inside the housing 3 or on the outer wall of the housing 3. The sensor pair includes two pressure sensors 4, which are symmetrically distributed on both sides of the sound head 1, and the force-receiving part of the pressure sensor 4 protrudes from the sound head 1.

[0070] In this example, the sound head 1 is installed inside the housing 3, and the sensor pair is installed inside the housing 3. The sensor pair includes two pressure sensors 4, which are symmetrically distributed on both sides of the sound head 1. The force-bearing part of the pressure sensor 4 protrudes from the sound head 1. When the detection probe detects the area to be measured, the force-bearing part of the pressure sensor 4 can directly contact the area to be measured, avoiding the influence of the internal structure of the detection probe on the pressure sensor 4 and improving the accuracy of the detection results.

[0071] In this example, the detection probe of this application can be a convex array probe type or a linear array probe type. The housing 3 has an inner cavity, and the acoustic head 1 is disposed within the inner cavity. The second detection end of the acoustic head 1 can protrude from the opening end of the housing 3, and the second detection end is used to contact the area to be detected. An operator (e.g., a doctor or nurse) can hold the housing 3, causing the second detection end of the acoustic head 1 to contact the skin and apply pressure. Because the force-receiving part of the pressure sensor 4 protrudes from the second detection end of the acoustic head 1, during pressure application, the force-receiving part of the pressure sensor 4 can directly contact and abut against the area to be detected, thereby avoiding the influence of the internal structure of the detection probe on the pressure sensor 4 and improving the accuracy of the detection results.

[0072] It should be noted that the two pressure sensors 4 of the sensor pair are stacked and distributed on opposite sides of the sound head 1. The pressure value tested by the sensor pair can be the average or weighted average of the values ​​of the two pressure sensors 4, which is beneficial to further improve the accuracy of the detection results.

[0073] In this example, the detection probe also includes a connector 5, through which the pressure sensor 4 is mounted to the inner wall of the housing 3. The connector 5 can be connected to the inner wall of the housing 3; for example, it can be fixed to the inner wall of the housing 3 using fasteners such as screws, and the pressure sensor 4 can be connected to the connector 5 using fasteners such as screws, thus connecting the pressure sensor 4 to the inner wall of the housing 3 via the connector 5. Alternatively, the connector 5 can also be connected to the housing 3 by snap-fit, welding, or bonding. Those skilled in the art can comprehensively consider factors such as the material, shape, working environment, and fixing requirements of the connector 5 and the housing 3 to ensure a firm, stable, and reliable fixation; no specific limitations are made here.

[0074] In this example, the detection probe also includes a motherboard 6, which is housed within the housing 3 and electrically connected to the pressure sensor 4. The pressure sensor 4 transmits the sensed pressure data to the motherboard 6 to achieve pressure detection.

[0075] In this example, the sensor pair can also be disposed on the outer wall of the housing 3. For example, the sensor pair can be directly fixedly connected to the outer wall of the housing. Alternatively, the detection probe also includes a mounting base, which is connected to the outer wall of the housing 3 near the sound head 1. The mounting base has mounting positions for mounting the sensor pair. The connection between the mounting base and the outer wall of the housing 3 can be a fixed connection or a movable connection. Fixed connections include, but are not limited to, riveting, bolting, welding, bonding, and any other connection method that can firmly fix the mounting base to the housing 3. Movable connections include, but are not limited to, snap-fit, plug-in, hinge, slide rail connection, and any other connection method that allows the mounting base to move or rotate relative to the housing 3 to a certain extent.

[0076] In one example, there are multiple sensor pairs, and the multiple sensor pairs are arranged in a centrally symmetrical manner with respect to the sound head 1.

[0077] In this example, multiple sensor pairs are provided, and each sensor pair includes two pressure sensors 4. The multiple sensor pairs are arranged symmetrically about the sound head 1, that is, the multiple pressure sensors 4 can be arranged at circumferential intervals along the sound head 1. For example, the multiple pressure sensors 4 can be evenly arranged at circumferential intervals along the sound head 1.

[0078] The actual pressure value detected by the probe can be the average or weighted average of the pressure values ​​from multiple sensor pairs. Alternatively, it can be calculated using Kalman filtering, least squares method, data fusion algorithm, median calculation, or moving average method from the pressure values ​​of multiple pressure sensor pairs to obtain the actual pressure value detected by the probe. Those skilled in the art can determine the appropriate method based on the specific circumstances, and no specific limitation is made here.

[0079] In this example, the sensor pairs can be set to two, three, four, or five, etc., as can be determined by those skilled in the art according to the actual situation, and no specific limitation is made here.

[0080] In one example, such as Figure 1 and Figure 2 As shown, the detection probe also includes a flexible component 2, which is connected to the housing 3. The flexible component 2 can cover the pressure sensor 4 and protrude from the sound head 1.

[0081] In this example, the flexible member 2 is connected to a possible open end. For example, the flexible member 2 can be integrally formed with the housing 3, or the flexible member 2 can be bonded to the housing 3. Those skilled in the art can decide according to the actual situation, and no specific limitation is made here.

[0082] The flexible element 2 covers the first sensing end of the pressure sensor 4 to form a force-bearing part. The first sensing end is used to detect pressure. The flexible element 2 can contact and abut against the area to be detected and transmit pressure to the first sensing end. By incorporating the flexible element 2, patient comfort can be improved.

[0083] In one example, such as Figure 1 As shown, the pressure sensor 4 has a first detection end that protrudes from the acoustic head 1, and the flexible member 2 covers the first detection end. The protruding first detection end improves the accuracy of pressure detection.

[0084] Alternatively, in this example, the first detection end is flush with the sound head 1, and the flexible member 2 covers the first detection end and protrudes from the sound head 1. This design is more compact and suitable for scenarios with limited space.

[0085] In one example, the detection probe also includes a coupling patch disposed at the second detection end of the acoustic head 1, and is provided with a clearance structure for the first detection end of the pressure sensor 4, so that the flexible member 2 covering the first detection end is flush with the coupling patch covering the second detection end of the acoustic head 1.

[0086] In this example, the area to be detected is coated with a coupling agent. When the detection probe moves and scans, it can scrape off the coupling agent, leading to missing coupling agent underneath the probe and poor coupling, thus affecting image quality. Therefore, a coupling adhesive is attached to the second detection end of the acoustic probe 1. This coupling adhesive has a clearance structure, such as clearance holes. The clearance structure is used to avoid the first detection end of the pressure sensor 4. The flexible component 2 covering the first detection end is flush with the coupling adhesive covering the second detection end to reduce scraping of the coupling agent and improve imaging performance.

[0087] In one example, the thickness of the coupling patch is less than or equal to 5 mm, and / or the ultrasonic attenuation coefficient of the coupling patch is less than or equal to 1 dB / cm / MHz, and / or the density of the coupling patch is less than or equal to 1.5 g / cm³. 3 .

[0088] The thickness of the coupling patch can be 5mm, 4mm, 3mm, or 2mm, etc. The ultrasonic attenuation coefficient of the coupling patch can be 1dB / cm / MHz, 0.9dB / cm / MHz, or 0.8dB / cm / MHz, etc. The density of the coupling patch can be 1.5g / cm³. 3 1.3g / cm 3 or 1g / cm 3 Of course, the specific structure and parameters of the coupling patch can be determined by those skilled in the art based on the actual situation, and no specific limitations are made here.

[0089] According to another embodiment of this application, a detection method is provided, which uses the detection probe of the above embodiment to perform pressure detection. Figure 3 As shown, the detection method includes:

[0090] S310. When it is detected that the force-receiving parts of both pressure sensors in the sensor pair are in contact with the area to be detected, the pressure values ​​detected by the two pressure sensors 4 in the sensor pair are acquired respectively. First, the detection probe is moved towards the area to be detected so that the force-receiving parts of the pressure sensors in the sensor pair can contact the area to be detected. For example, the detection probe can be pressed perpendicularly to the area to be detected, that is, the detection probe can be perpendicular to the area to be detected. When it is detected that the force-receiving parts of both pressure sensors in the sensor pair are in contact with the area to be detected, the pressure values ​​detected by the two pressure sensors 4 in the sensor pair are acquired respectively.

[0091] S320. Calculate the difference in pressure values ​​between the two pressure sensors 4 of the sensor pair. If the actual difference is less than or equal to a first preset difference, the pressure value detected by the sensor pair is determined to be valid. The difference in pressure values ​​between the two pressure sensors 4 is calculated based on their respective detection values. If the difference is less than or equal to the first preset difference, the pressure value detected by the sensor pair is determined to be valid. After the detection probe presses against the area to be detected, the two pressure sensors of the sensor pair can detect the pressure value separately. If the difference between the two pressure values ​​is less than or equal to the first preset difference, the pressure value detected by the sensor pair is determined to be valid. For example, it can be assumed that the detection probe is pressing vertically against the area to be detected.

[0092] It should be noted that the pressure values ​​detected by both pressure sensors in the sensor pair are greater than 0, that is, both pressure sensors are enabled. If one of the pressure sensors is not enabled, the detection of the sensor pair is determined to be invalid.

[0093] S330. Calculate the pressure value of the detection probe based on the effective pressure value detected by the sensor. The pressure value detected by the detection probe is calculated based on the pressure values ​​detected by the two pressure sensors 4.

[0094] In one example, the detection method further includes: enabling the sensor pair when it is detected that the force-receiving parts of both pressure sensors 4 of the sensor pair are in contact with the area to be detected;

[0095] The continuous enable time of the two pressure sensors 4 of the sensor pair is monitored. When the continuous enable time of both is greater than or equal to a preset time, the pressure value detected by the sensor pair is determined to be valid.

[0096] In this example, during the detection process, the detection probe needs to press on the area to be detected. The pressure sensor then continuously detects the pressure; that is, the pressure sensor remains continuously enabled. The enable time is the actual effective time for the sensor. When the actual effective time is greater than or equal to a preset time, the sensor is deemed to have detected a valid pressure value. When the actual effective time is less than the preset time, the sensor is deemed to have detected an invalid pressure value. For example, the preset time can be set to 2s, 2.5s, or 3s, etc., which can be determined by those skilled in the art according to the actual situation, and is not specifically limited here.

[0097] In one example, there are multiple sensor pairs. The proportion of the number of sensor pairs whose detected pressure values ​​are valid is calculated relative to the total number of sensor pairs. If the proportion is greater than or equal to a preset proportion, the pressure value detected by the detection probe is determined to be valid.

[0098] In this example, the multiple sensor pairs include valid sensor pairs and invalid sensor pairs. Valid sensor pairs represent those capable of acquiring valid pressure values, while invalid sensor pairs represent those whose pressure values ​​were not recorded. The ratio of valid sensor pairs to the total number of sensor pairs is calculated. If the ratio is greater than or equal to a preset ratio, the pressure value detected by the detection probe is considered valid; otherwise, the pressure value detected by the detection probe is considered invalid. For example, the preset ratio could be 10%. Of course, the specific value of the preset ratio can be determined by those skilled in the art based on actual circumstances, and is not specifically limited here.

[0099] Alternatively, in this example, if more than a certain percentage of valid sensor pairs have a relative deviation exceeding a preset relative deviation, the detection probe is deemed invalid for that detection. For example, exceeding 10% or 20%, etc., can be determined by those skilled in the art based on the actual situation, and no specific limitation is made here.

[0100] The relative deviation can be calculated as (estimated value - effective pressure value) / effective pressure value. Of course, the relative deviation can also be calculated using other algorithms, which can be determined by those skilled in the art based on the actual situation; no specific limitations are made here.

[0101] In one example, the detection method further includes: selecting a sensor pair whose pressure value difference between the two pressure sensors 4 is less than or equal to a second preset difference; wherein the second preset difference is less than the first preset difference; and calculating the pressure value of the detection probe based on the effective pressure value detected by the selected sensor pair.

[0102] In this example, the second preset difference is less than the first preset difference. The pressure value of the two pressure sensors 4 in the selected sensor pair is less than or equal to the second preset difference. Then, the pressure value of the detection probe is calculated based on the effective pressure value detected by the selected sensor, which helps to further improve the detection accuracy.

[0103] In one example, the calculation of the pressure value of the detection probe based on the effective pressure value detected by the sensor includes: calculating the average of multiple effective pressure values, weighted average calculation, Kalman filtering calculation, least squares calculation, data fusion algorithm calculation, median calculation, or moving average calculation to obtain the pressure value detected by the detection probe.

[0104] In this example, the average is calculated as the average of the pressure values ​​from multiple valid sensor pairs. The weighted average is calculated by assigning different weights to each sensor pair based on their reliability or accuracy, and then calculating the weighted average. The weights can be determined based on factors such as the relative deviation of the sensor pair's pressure readings, historical performance, and calibration results.

[0105] Another method is to use the Kalman filter, a recursive algorithm used to estimate the state of a dynamic system in the presence of noise. It calculates the optimal estimate of the current state based on the estimate of the previous state and the current sensor measurements. The sensed values ​​of each sensor pair can be considered as measurements of the system state; by fusing these measurements using the Kalman filter algorithm, a more accurate pressure estimate can be obtained.

[0106] Another approach is to use the least squares method, which finds the best function fit for the data by minimizing the sum of squared errors, even when errors exist. Since there is a linear relationship between pressure and sensor output, the least squares method can be used to fit these data, resulting in a more accurate pressure estimate.

[0107] Another method is data fusion algorithm calculation, which combines information from multiple data sources and fuses this information using a specific algorithm to obtain more accurate results. Sensing values ​​from different sensor pairs can be considered as different data sources, and data fusion algorithms can be used to combine these data to obtain more precise pressure detection values.

[0108] Another method is the median method, which involves sorting a set of data from smallest to largest and taking the middle value. The sensor values ​​from different sensor pairs are sorted, and the median is then used as the final pressure detection value.

[0109] Another method is the moving average method, which is a data smoothing technique that eliminates noise by calculating the average value of data within a certain window. For real-time pressure detection systems, the moving average method can be used to smooth the sensed values ​​from different sensor pairs, thereby obtaining more stable pressure detection values.

[0110] Of course, those skilled in the art can determine the specific calculation method according to the actual situation, and no specific limitation is made here.

[0111] In this example, the detection probe can perform multiple tests, and the actual pressure values ​​obtained from these multiple tests can be calculated using the calculation method described in the above embodiment to obtain the final pressure detection data.

[0112] According to another embodiment of this application, an acoustic detection system is provided. The detection system includes an elastography module, a blood flow imaging module, an ultrasound imaging module, a detection probe as described in the above embodiments, a control module for controlling the detection probe to perform the detection method described in the above embodiments, and a robotic arm.

[0113] The elastic imaging module is used to perform elastic detection according to the elastic detection control signal to obtain elastic detection parameters.

[0114] The blood flow imaging function module is used to perform blood flow detection according to the blood flow detection control signal to obtain blood flow detection parameters;

[0115] The ultrasonic imaging function module is used to perform ultrasonic detection according to the ultrasonic detection control signal to obtain ultrasonic detection parameters;

[0116] The elastic imaging module and / or the ultrasonic imaging module also perform detection area identification according to the positioning control signal and send the location information to the control module;

[0117] The control module is configured to send positioning control information to the elastic imaging function module and / or the ultrasound imaging function module, and determine the current position of the detection probe and the position of the target detection area based on the received position information, and send a first movement control command to the robotic arm based on the difference information between the two positions; when it is determined that the detection probe has reached the target detection area based on the received position information, it sequentially sends a plurality of corresponding second movement control commands to the robotic arm based on a plurality of preset pressure values ​​within the target pressure range; and after sending each second movement control command, it simultaneously or sequentially sends the elastic detection control signal, the blood flow detection control signal and / or the ultrasound detection control signal.

[0118] The robotic arm controls the detection probe to move to the target detection area according to the first movement control command, and controls the detection probe to press down vertically according to the second movement control command.

[0119] In this example, the detection probe includes a housing, a sound head, and a pair of sensors. The sound head is mounted inside the housing. The sensor pair, also mounted inside the housing, includes two pressure sensors symmetrically distributed on both sides of the sound head, with the force-bearing portion of each pressure sensor protruding from the sound head. When the detection probe detects the area to be measured, the force-bearing portion of the pressure sensor can directly contact the area, avoiding the influence of the internal structure of the detection probe on the pressure sensors and improving the accuracy of the detection results.

[0120] In this example, the elasticity detection parameters include the group velocity, phase velocity, attenuation coefficient, dispersion characteristics, and / or anisotropy of the shear wave; the blood flow detection parameters include vascular density, blood flow velocity, blood flow velocity gradient, vascular tortuosity, and / or blood flow resistance index; and the ultrasound detection parameters include scattering, attenuation, scatterer distribution characteristics, and / or nonlinear acoustic parameters.

[0121] In this example, the ultrasound detection system also includes an inflammation severity assessment module, wherein:

[0122] The control module is further configured to send an inflammation detection signal to the inflammation severity assessment module after sending each of the second movement control commands;

[0123] The inflammation severity assessment module is loaded with an inflammation severity training model, and obtains the elasticity detection parameters, the blood flow detection parameters, and / or the ultrasound detection parameters based on the inflammation detection signal, and generates inflammation severity information based on the inflammation severity training model;

[0124] The inflammation degree training model is based on the data of the test subjects and the correspondence between the elasticity detection parameters, the blood flow detection parameters, and / or the ultrasound detection parameters and the inflammation degree information, established by the tissue inflammation degree information obtained from pathological examination.

[0125] In this example, the control module also assesses the likelihood of inflammation based on user input information indicating abnormal tissue condition during clinical examination and / or blood test parameters indicating inflammation. If inflammation is confirmed, an inflammation detection signal is sent to the inflammation severity assessment module. And / or, the inflammation severity training model is obtained by screening sample data for different etiologies and training it.

[0126] In this example, the user is shown the elasticity detection parameters, the blood flow detection parameters, the ultrasound detection parameters, and / or the inflammation level information;

[0127] The methods for instructing users include one or more of the following:

[0128] The screen text display method includes: displaying the specific values ​​or status descriptions of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information in text form on the display screen;

[0129] The sound reminder method includes: emitting a preset sound signal through an audio output device, including audio broadcasting or a specific tone, to prompt the user to pay attention to the abnormal or specific state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information;

[0130] Different color graphic display methods include: using graphic elements of different colors or color combinations on the display screen to represent the relative size, trend of change or abnormal state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information, wherein each color or color combination corresponds to a specific parameter range or state category;

[0131] Different colored indicator light display methods include: using indicator light elements of different colors or color combinations to represent the relative magnitude, trend of change, or abnormal state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information, wherein each color or color combination corresponds to a specific parameter range or state category.

[0132] In this example, the ultrasound detection system also includes a tissue condition assessment module, wherein:

[0133] The tissue condition assessment module is loaded with a tissue condition assessment model, which is used to assess tissue condition based on the elasticity detection parameters, the blood flow detection parameters, the ultrasound detection parameters, and / or inflammation degree information.

[0134] Indicate the assessed organizational status to the user;

[0135] The methods for instructing users include one or more of the following:

[0136] The screen text display method includes: displaying the specific score value or status description of the organization status in text form on the display screen;

[0137] The sound reminder method includes: emitting a preset sound signal through an audio output device, including audio broadcasting or a specific tone, to prompt the user to pay attention to the organizational status;

[0138] Different color graphic display methods include: using graphic elements of different colors or color combinations on a display screen to represent the organizational state;

[0139] Different colored indicator light display methods include: using indicator light elements of different colors or color combinations to indicate the organizational status.

[0140] In this example, the probe is pressed down on the area to be tested, allowing for the measurement of viscoelastic parameters, blood flow parameters, and quantitative ultrasound parameters under different pressures. The blood flow parameters and quantitative ultrasound parameters can be acquired simultaneously in a single ultrasound examination or separately in different ultrasound examinations. The viscoelastic parameters are acquired during a single viscoelasticity measurement.

[0141] In this example, a multiple elasticity testing method can be employed during the elasticity testing process. Specifically, firstly, the elastic imaging area of ​​the region to be tested and the set target pressure range are acquired. Next, the initial detection position of the detection probe within the elastic imaging area is determined, and the probe is controlled to be vertically pressed down to that position. Then, based on the detection position and multiple pressure values ​​within the target pressure range, the probe is controlled to sequentially apply these pressure values, and elasticity testing is performed at each pressure value. During each elasticity test, the system records parameters such as shear wave group velocity and phase velocity, thereby obtaining the elastic modulus distribution and dispersion curve of the region to be tested under different pressures. This ensures that the pressure applied to the region to be tested is within a specific range, thereby improving the accuracy of elastic parameter measurement.

[0142] Blood flow parameters can be measured during ultrasound examination. Using blood flow imaging techniques, such as color Doppler ultrasound, the system can display the blood flow distribution in the area under test in real time and calculate relevant blood flow parameters, such as vessel density, blood flow velocity, blood flow velocity gradient, and vessel tortuosity. These parameters reflect the blood flow state within the area under test.

[0143] The acquisition of quantitative ultrasound parameters is relatively flexible. They can be acquired simultaneously with blood flow parameters during ultrasound detection, or they can be extracted separately from different ultrasound detection sessions. These parameters can comprehensively characterize the acoustic properties of the area under test.

[0144] In one example, the ultrasound detection system also includes a tissue condition assessment model. The acquired viscoelastic parameters, blood flow parameters, quantitative ultrasound parameters, and tissue inflammation information are input into the tissue condition assessment model, which can output the assessment results of the target tissue.

[0145] In this example, the tissue condition assessment model extracts features from the input parameters and fuses these features to form a more comprehensive tissue representation. Based on the extracted and fused features, the model outputs an assessment result for the target tissue. The assessment result can be presented in the form of health status, degree of lesion, etc., such as grade, score, or probability. This tissue condition assessment model not only improves the accuracy of the assessment but also reduces reliance on the subjective experience of healthcare professionals, allowing them to provide supplementary information for clinical decision-making based on the assessment results.

[0146] In one example, such as Figure 4 As shown, the method for constructing the organizational status assessment model includes:

[0147] S410. Collect known tissue states and their corresponding viscoelastic parameters, blood flow parameters, quantitative ultrasound parameters, and tissue inflammation levels, and preprocess the data. A large amount of known tissue states (e.g., healthy, diseased, etc.) and their corresponding viscoelastic parameters, blood flow parameters, quantitative ultrasound parameters, and tissue inflammation levels were pre-collected. This data covered patients of different ages, genders, diseases, and lesion degrees to ensure data diversity and representativeness. Subsequently, the data underwent preprocessing, including cleaning outliers and missing values, standardizing or normalizing the data, and dividing the data into training, validation, and test sets for subsequent model training, validation, and evaluation.

[0148] S420. Select a machine learning model based on task requirements and data characteristics. Choose a suitable machine learning model, such as a deep neural network (DNN) or a convolutional neural network (CNN). When designing the model structure, focus on its ability to automatically extract feature information from the input parameters. Use convolutional layers and pooling layers to extract spatial features from quantitative ultrasound parameters, and use fully connected layers and activation functions to fuse and nonlinearly transform viscoelastic parameters, blood flow parameters, and tissue inflammation levels.

[0149] S430. Train the organizational status assessment model. During model training, the model parameters are continuously adjusted using the training dataset and optimization methods such as backpropagation and gradient descent. Appropriate loss functions, such as mean squared error (MSE) or cross-entropy loss, are set to measure the difference between the predicted and actual assessment results. Simultaneously, the training process is monitored using a validation set to prevent overfitting and underfitting.

[0150] S440. After the organizational status assessment model has been trained, evaluate the model's predictive accuracy. After training, evaluate the model's predictive accuracy on the test set, using metrics such as precision, recall, and F1 score.

[0151] S450. Based on the evaluation results, adjust the structure, parameter settings, or data preprocessing methods of the organizational status assessment model. Adjust and optimize the model structure, parameter settings, or data preprocessing methods based on the evaluation results to improve the model's predictive performance.

[0152] In this example, the method for training the degree of tissue inflammation includes:

[0153] S1: Obtain data from the subjects and the degree of tissue inflammation based on pathological examination;

[0154] The data of the test subjects include age, gender, BMI, degree of tissue inflammation, disease, elasticity test parameters, blood flow test parameters, and ultrasound test parameters, etc.

[0155] S2: Based on the elasticity detection parameters, blood flow detection parameters, and / or the ultrasound detection parameters of the test subject, a comprehensive evaluation parameter is obtained;

[0156] In one application example, the comprehensive evaluation parameter algorithm can adopt a linear design, specifically implemented as a weighted summation method. This method assigns corresponding weighting coefficients to the elasticity detection parameters, blood flow detection parameters, and ultrasound detection parameters of the test subject, and then performs a weighted summation operation to finally obtain the comprehensive evaluation parameters.

[0157] In another application example, the comprehensive evaluation parameter algorithm can also be a nonlinear design. For instance, a comprehensive scoring algorithm based on a neural network can be constructed, specifically including: an input layer receiving elasticity detection parameters, blood flow detection parameters, and ultrasound detection parameters as input; a hidden layer performing nonlinear transformations and feature extraction on the input data through connections between multiple layers of neurons; and an output layer outputting the comprehensive scoring parameters. During training, the neural network is trained using a known dataset, continuously adjusting the weights and biases of the neurons to ensure that the output comprehensive scoring parameters match the actual situation.

[0158] S3: Establish the working characteristic curve of the test subjects, with sensitivity and specificity as the x-axis and y-axis, respectively;

[0159] S4: Based on the subjects' working characteristic curves and the degree of tissue inflammation, calculate the sensitivity, specificity, positive predictive value, and negative predictive value corresponding to the threshold values ​​of the comprehensive evaluation parameters;

[0160] S5: Determine the Youden index based on sensitivity and specificity;

[0161] S6: Select the largest Youden index as the optimal threshold to determine the comprehensive assessment parameter corresponding to the degree of inflammation in each tissue.

[0162] In this example, the tissue inflammation severity training method further includes the following steps to further optimize and expand its application:

[0163] 1. Assessing the likelihood of tissue inflammation: Clinically confirming abnormal tissue condition and using inflammation-related parameters (such as alanine aminotransferase (ALT) and aspartate aminotransferase (AST)) to determine the presence of inflammation. If these parameters indicate inflammation, further monitoring and evaluation of the degree of inflammation can be achieved using tissue stiffness or parameters reflecting stiffness.

[0164] 2. Monitor tissue stiffness during treatment: When there is a possibility of inflammation in the tissue, continuously monitor tissue stiffness or parameters reflecting stiffness during treatment. If the monitored tissue stiffness continues to decrease and reaches a plateau value, the degree of tissue fibrosis or related information can be obtained based on the plateau value.

[0165] 3. Determine the treatment effect: If the monitored tissue stiffness continues to decrease and reaches a normal or near-normal level during the treatment process, the tissue inflammation can be considered to have been effectively treated; conversely, if the tissue stiffness continues to increase or remains at a high level, the treatment plan may need to be adjusted.

[0166] 4. Establish corresponding relationships for different causes: Since tissue inflammation caused by different causes may have different pathophysiological characteristics, a corresponding relationship between tissue stiffness and the degree of tissue inflammation can be established for different causes to improve the accuracy and reliability of diagnosis.

[0167] The above embodiments mainly describe the differences between the various embodiments. As long as the different optimization features between the various embodiments are not contradictory, they can be combined to form a better embodiment. For the sake of brevity, they will not be elaborated here.

[0168] Although specific embodiments of the present invention have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A detection probe, characterized in that, include: Shell (3); The sound head (1) is installed inside the housing (3); The sensor pair is installed inside the housing (3) or on the outer wall of the housing (3). The sensor pair includes two pressure sensors (4). The two sensors are symmetrically distributed on both sides of the sound head (1), and the force-receiving part of the pressure sensor (4) protrudes from the sound head (1).

2. The detection probe according to claim 1, characterized in that, Also includes: Mounting base, the mounting base being connected to the outer wall of the housing (3) near the sound head end; The mounting base is provided with mounting positions for mounting the sensor pair; The connection between the mounting base and the outer wall of the housing (3) near the sound head end is either a fixed connection or a movable connection.

3. The detection probe according to claim 1, characterized in that, The sensor pair is provided in multiple ways, and the multiple sensor pairs are arranged in a centrally symmetrical manner with the sound head (1) as the center.

4. The detection probe according to claim 1, characterized in that, It also includes a flexible element (2) connected to the housing (3), the flexible element (2) being able to cover the pressure sensor (4), and the flexible element (2) being able to protrude from the sound head (1).

5. The detection probe according to claim 4, characterized in that, The pressure sensor (4) is provided with a first detection end, which protrudes from the sound head (1), and the flexible member (2) covers the first detection end.

6. The detection probe according to claim 4, characterized in that, The pressure sensor (4) is provided with a first detection end, which is flush with the sound head (1), and the flexible member (2) covers the first detection end and protrudes from the sound head (1).

7. The detection probe according to claim 5 or 6, characterized in that, It also includes a coupling patch, which is disposed at the second detection end of the sound head (1) and is provided with a clearance structure for the first detection end of the pressure sensor (4) so ​​that the flexible part (2) covering the first detection end is flush with the coupling patch covering the second detection end of the sound head (1).

8. The detection probe according to claim 7, characterized in that, The thickness of the coupling patch is less than or equal to 5 mm, and / or the ultrasonic attenuation coefficient of the coupling patch is less than or equal to 1 dB / cm / MHz, and / or the density of the coupling patch is less than or equal to 1.5 g / cm³. 3 .

9. An ultrasonic testing system, characterized in that, The system includes an elastography module, a blood flow imaging module, an ultrasound imaging module, a detection probe as described in any one of claims 1 to 8, and a robotic arm, wherein: The elastic imaging function module is used to perform elastic detection according to the elastic detection control signal to obtain elastic detection parameters; The blood flow imaging function module is used to perform blood flow detection according to the blood flow detection control signal to obtain blood flow detection parameters; The ultrasonic imaging function module is used to perform ultrasonic detection according to the ultrasonic detection control signal to obtain ultrasonic detection parameters; The elastic imaging module and / or the ultrasonic imaging module also perform detection area identification according to the positioning control signal and send the location information to the control module; The control module is configured to send positioning control information to the elastic imaging function module and / or the ultrasound imaging function module, and determine the current position of the detection probe and the position of the target detection area based on the received position information, and send a first movement control command to the robotic arm based on the difference information between the two positions; when it is determined that the detection probe has reached the target detection area based on the received position information, it sequentially sends a plurality of corresponding second movement control commands to the robotic arm based on a plurality of preset pressure values ​​within the target pressure range; and after sending each second movement control command, it simultaneously or sequentially sends the elastic detection control signal, the blood flow detection control signal and / or the ultrasound detection control signal. The robotic arm controls the detection probe to move to the target detection area according to the first movement control command, and controls the detection probe to press down vertically according to the second movement control command.

10. The ultrasonic testing system according to claim 9, characterized in that, The elastic detection parameters include the group velocity, phase velocity, attenuation coefficient, dispersion characteristics, and / or anisotropy of the shear wave. The blood flow detection parameters include vascular density, blood flow velocity, blood flow velocity gradient, vascular tortuosity, and / or blood flow resistance index; The ultrasonic detection parameters include scattering, attenuation, scatterer distribution characteristics, and / or nonlinear acoustic parameters.

11. The ultrasonic testing system according to claim 9, characterized in that, It also includes an inflammation severity assessment module, in which: The control module is further configured to send an inflammation detection signal to the inflammation severity assessment module after sending each of the second movement control commands; The inflammation severity assessment module is loaded with an inflammation severity training model, and obtains the elasticity detection parameters, the blood flow detection parameters, and / or the ultrasound detection parameters based on the inflammation detection signal, and generates inflammation severity information based on the inflammation severity training model; The inflammation degree training model is based on the data of the test subjects and the correspondence between the elasticity detection parameters, the blood flow detection parameters, and / or the ultrasound detection parameters and the inflammation degree information, established by the tissue inflammation degree information obtained from pathological examination.

12. The ultrasonic testing system according to claim 11, characterized in that: The control module further assesses the likelihood of inflammation based on user input information indicating abnormal tissue condition during clinical examination and / or blood test parameters indicative of inflammation. Only if inflammation is confirmed will an inflammation detection signal be sent to the inflammation severity assessment module; and / or, The inflammation severity training model was obtained by selecting sample data for different causes and training it.

13. The ultrasonic testing system according to claim 11, characterized in that: Indicate to the user the elasticity detection parameters, the blood flow detection parameters, the ultrasound detection parameters, and / or the inflammation level information; The methods for instructing users include one or more of the following: The screen text display method includes: displaying the specific values ​​or status descriptions of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information in text form on the display screen; The sound reminder method includes: emitting a preset sound signal through an audio output device, including audio broadcasting or a specific tone, to prompt the user to pay attention to the abnormal or specific state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information; Different color graphic display methods include: using graphic elements of different colors or color combinations on the display screen to represent the relative size, trend of change or abnormal state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information, wherein each color or color combination corresponds to a specific parameter range or state category; Different colored indicator light display methods include: using indicator light elements of different colors or color combinations to represent the relative magnitude, trend of change, or abnormal state of the elasticity detection parameters, blood flow detection parameters, ultrasound detection parameters, and / or inflammation degree information, wherein each color or color combination corresponds to a specific parameter range or state category.

14. The ultrasonic testing system according to claim 11, characterized in that, It also includes an organization status assessment module, in which: The tissue condition assessment module is loaded with a tissue condition assessment model, which is used to assess tissue condition based on the elasticity detection parameters, the blood flow detection parameters, the ultrasound detection parameters, and / or inflammation degree information. Indicate the assessed organizational status to the user; The methods for instructing users include one or more of the following: The screen text display method includes: displaying the specific score value or status description of the organization status in text form on the display screen; The sound reminder method includes: emitting a preset sound signal through an audio output device, including audio broadcasting or a specific tone, to prompt the user to pay attention to the organizational status; Different color graphic display methods include: using graphic elements of different colors or color combinations on a display screen to represent the organizational state; Different colored indicator light display methods include: using indicator light elements of different colors or color combinations to indicate the organizational status.

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