Heating ultrasonic probe heat control method and system

Abstract

The invention discloses a heat control method and system for a heating ultrasonic probe. And through a first temperature-time convolutional network, a temperature delay image representing the temperatures corresponding to the power-on starting time point and all the power-on stopping time points is used to integrally find the relationship between the temperatures of different power-on stopping time points and the delays of the power-on stopping time points. And constructing a time-temperature curve and acquiring a three-dimensional time-temperature image. And convolving the three-dimensional time-temperature image through a second temperature-time convolution network, and finding the temperature change of a time point with the same time length from the power-on stopping time point. And the temperature change of a plurality of stopping surrounding time points between the two power-on stopping time points is found by utilizing the difference of the coefficients of the time-temperature curve.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for controlling the heat of a heated ultrasonic probe. Background Art

[0002] At present, because the handheld ultrasound probe used generates heat during use, the large amount of heat will damage the tissues and bacteria in the surgical area, so it is necessary to install a thermistor in the handheld ultrasound probe to monitor the heat of the ultrasound probe in the working state.

[0003] However, there is a delay between the length of the heating time and the amount of heat reached, so that the current temperature when heating stops is not the highest temperature of the handheld ultrasound probe, and the highest temperature of the handheld ultrasound probe appears some time after heating stops.

[0004] So we need to find the correlation between the two. Summary of the invention

[0005] The object of the present invention is to provide a method and system for controlling the heat of a heated ultrasonic probe, so as to solve the above-mentioned problems existing in the prior art.

[0006] In a first aspect, an embodiment of the present invention provides a method for controlling the heat of a heated ultrasonic probe, comprising: Acquire a power-on start time point and a plurality of power-off stop time points; the power-on start time point indicates a time point at which power is started; the power-off stop time point indicates a time point at which power is stopped; Based on multiple power-off time points, a corresponding multiple probe time-temperature images are acquired; the probe time-temperature images include temperatures of multiple stop-around time points; the stop-around time points include n time points earlier than the power-off time point and n time points later than the power-off time point; Based on multiple probe time-temperature images, the highest temperature at the time point of power-off and the corresponding time points around the power-off is detected to obtain a temperature time-lapse image; A first temperature delay feature is obtained based on the temperature delay image through a first temperature-time convolution network; the first temperature delay feature is used to detect the degree of delay of the temperature at multiple power-off time points; Based on multiple probe time-temperature images, determine the temperature changes corresponding to different power-off time points to obtain a second temperature delay feature; The first temperature delay feature and the second temperature delay feature are input into a prediction network to obtain a predicted power-off time point; the predicted power-off time point represents the earliest predicted power-off time point that can reach a preset temperature; A signal to stop energizing is sent at the predicted energizing stop time point.

[0007] Optionally, obtaining a first temperature delay feature based on the temperature delay image through a first temperature-time convolutional network includes: The first temperature-time convolution network includes a two-dimensional convolution kernel of p*((2n+1)*2); p represents the width of the temperature delay image, (2n+1) represents the time length between the power-off time point and the corresponding multiple stop surrounding time points; ((2n+1)*2) represents the change in the delay between the temperature at two power-off time points and the corresponding highest temperature found by using a two-dimensional convolution kernel; With a step size of ((2n+1)*2), convolving the two-dimensional convolution kernel included in the first temperature-time convolution network on the temperature delay image to obtain a first detection feature vector; The first detection feature vector is input into a first neural network to detect the characteristics of the temperature change at two power-off time points to obtain a first temperature delay feature.

[0008] Optionally, acquiring corresponding multiple probe time-temperature images based on multiple power-off time points includes: Acquire multiple time points around the stop; the time points around the stop include n time points earlier than the power-off time point and n time points later than the power-off time point; the time lengths of any two adjacent time points around the stop are the same; Obtain the temperatures corresponding to multiple stop-around time points as probe temperatures; A time-temperature coordinate axis is constructed with the time point as the abscissa and the probe temperature as the ordinate; the abscissa of the origin of the time-temperature coordinate axis represents the time point when power is turned on; the ordinate of the origin of the time-temperature coordinate axis represents the temperature as 0; With the horizontal axis of the time-temperature coordinate axis as the length and the vertical axis as the width, the probe time-temperature image is drawn by taking the stop surrounding time points and the corresponding probe temperatures; the length of the probe time-temperature image represents the time length between three adjacent stop power-on time points; the width of the probe time-temperature image represents 0 to 100 degrees Celsius; The probe time-temperature image is a point image.

[0009] Optionally, the determining, based on multiple probe time-temperature images, temperature changes corresponding to different power-off time points to obtain a second temperature delay feature includes: The time point of power-off and multiple time points around power-off in the probe time-temperature image are used to construct a curve with the corresponding temperature to obtain a time-temperature curve; Multiple probe time-temperature images correspond to multiple time-temperature curves; According to the time point of power off from early to late, multiple probe time-temperature images are superimposed to obtain a three-dimensional time-temperature image; Obtaining a first change feature based on the three-dimensional time-temperature image through a second temperature-time convolutional network; Based on the multiple time-temperature curves, detect the coefficient change to obtain a second change feature; A second temperature delay characteristic is obtained according to the first change characteristic and the second change characteristic.

[0010] Optionally, obtaining the first change feature based on the three-dimensional time-temperature image through the second temperature-time convolution network includes: The second temperature-time convolution network includes a three-dimensional temperature-time convolution network and a two-dimensional temperature-time convolution network; The three-dimensional temperature-time convolution network includes a three-dimensional convolution kernel of p*2*2; p represents the height of the three-dimensional time-temperature image; In the width direction of the three-dimensional time-temperature image, the three-dimensional convolution kernel of the three-dimensional time-temperature image is convolved on the three-dimensional time-temperature image with a step size of 1, and the temperature change of different starting temperatures when the power is turned on for the same time is detected to obtain a first characteristic image; the width of the first characteristic image corresponds to the width of the three-dimensional time-temperature image; the length of the first characteristic image corresponds to the length of the three-dimensional time-temperature image; Based on the first feature image, a first change feature is obtained through a two-dimensional temperature-time convolution network; the first change feature represents the feature of the feature change of adjacent power-off time points.

[0011] Optionally, obtaining a first change feature based on the first feature image through a two-dimensional temperature-time convolution network includes: The two-dimensional temperature-time convolution network includes a two-dimensional convolution kernel of m*2; m represents the width of the first feature image; In the long direction of the first feature image, with a step size of 1, the two-dimensional convolution kernel of the two-dimensional temperature-time convolution network is convolved on the first feature image to obtain a first change feature; the first change feature is a one-dimensional vector.

[0012] Optionally, the detecting coefficient change based on the multiple time-temperature curves to obtain a second change feature includes: According to the power-off time points from early to late, the coefficients of the time-temperature curve are sequentially input into the time convolution network to obtain the second change feature.

[0013] Optionally, the method of detecting the highest temperature at the power-off time point and the corresponding surrounding time points based on multiple probe time-temperature images to obtain a temperature delay image includes: In the probe time-temperature image, the highest detected temperature value is taken as the highest temperature; multiple probe time-temperature images correspond to multiple highest temperatures; In the probe time-temperature image, the time point corresponding to the highest temperature is taken as the highest temperature time point; The temperature corresponding to the power-off time point corresponding to the probe time-temperature image is used as the power-off temperature; The power-off time point, power-off temperature, maximum temperature time point and maximum temperature corresponding to the probe time-temperature image are taken as a time-temperature set; Multiple probe time-temperature images correspond to obtaining multiple time-temperature sets; Based on multiple time-temperature sets, a temperature time-lapse image is obtained.

[0014] Optionally, obtaining a temperature time-lapse image based on multiple time-temperature sets includes: Obtaining the latest power-off time point; the latest power-off time point represents a power-off time point that is later than other power-off time points among the multiple power-off time points; Acquire a complete time image; the length of the complete time image represents multiple de-energization time points from the start time point of energization to the latest de-energization time point; Mark the point consisting of the power-off time point and the power-off temperature in the time-temperature set in the complete time image to obtain the stop position; The point consisting of the highest power-on time point and the highest power-on temperature in the time-temperature set is marked in the complete time image to obtain the highest position; multiple stop positions and multiple highest positions are obtained corresponding to multiple time-temperature sets; The stop position and the corresponding highest position in the complete time image are connected with a straight line to obtain a temperature time-lapse image.

[0015] In a second aspect, an embodiment of the present invention provides a heat control system for a heated ultrasound probe, comprising: An acquisition module is used to acquire a power-on start time point and a plurality of power-off stop time points; the power-on start time point indicates a power-on start time point; the power-off stop time point indicates a power-off stop time point; based on the plurality of power-off stop time points, a plurality of corresponding probe time-temperature images are acquired; the probe time-temperature images include temperatures at a plurality of stop surrounding time points; the stop surrounding time points include n time points earlier than the power-off stop time point and n time points later than the power-off stop time point; A temperature time-lapse image acquisition module is used to detect the highest temperature at the power-off time point and the corresponding surrounding time points based on multiple probe time temperature images to obtain a temperature time-lapse image; A first temperature delay detection module, configured to obtain a first temperature delay feature based on the temperature delay image through a first temperature time convolution network; the first temperature delay feature is used to detect the degree of temperature delay at multiple power-off time points; A second temperature delay detection module is used to determine the temperature change corresponding to different power-off time points based on multiple probe time-temperature images to obtain a second temperature delay feature; A prediction module, configured to input the first temperature delay feature and the second temperature delay feature into a prediction network to obtain a predicted power-off time point; the predicted power-off time point represents the earliest predicted power-off time point that can reach a preset temperature; The reminder module is used to send a power-off signal at the predicted power-off time point.

[0016] Compared with the prior art, the embodiments of the present invention achieve the following beneficial effects: The embodiments of the present invention also provide a method and system for controlling the heat of a heated ultrasonic probe.

[0017] In the present invention, there is a delay between the time when heating is stopped and the time when the handheld ultrasonic probe reaches the highest temperature.

[0018] Through the first temperature-time convolutional network, a temperature delay image representing the temperatures corresponding to the power-on start time point and all the power-off time points is used to find the overall relationship between the temperatures at different power-off time points and the delays at the power-off time points.

[0019] Reconstruct the time-temperature curve and obtain the three-dimensional time-temperature image.

[0020] The three-dimensional time-temperature image is convolved by the second temperature-time convolution network to find the temperature change at the time point with the same time length from the time point when the power is stopped.

[0021] And by using the difference in coefficients of the time-temperature curve, the temperature changes at multiple stop-around time points between two stop-power-on time points are found.

[0022] The technical effect is achieved by finding the correlation between the power-off time point and the temperature, thereby accurately predicting the time point when the preset temperature is reached. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The present invention provides a flow chart of a method for controlling the heat of a heated ultrasonic probe. DETAILED DESCRIPTION

[0024] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0025] Example 1 like Figure 1 As shown, an embodiment of the present invention provides a method for controlling the heat of a heated ultrasonic probe, the method comprising: S101: Acquire a power-on start time point and a plurality of power-off stop time points; the power-on start time point indicates a time point at which power is started; and the power-off stop time point indicates a time point at which power is stopped.

[0026] The length of the time period between any two adjacent power-off time points is the same.

[0027] The amount of electricity supplied at the multiple power-on time points is the same.

[0028] S102: Based on multiple power-off time points, obtain corresponding multiple probe time-temperature images; the probe time-temperature images include temperatures of multiple stop-around time points; the stop-around time points include n time points earlier than the power-off time point and n time points later than the power-off time point.

[0029] S103: Based on the multiple probe time-temperature images, the highest temperature at the power-off time point and the corresponding surrounding time points is detected to obtain a temperature delay image.

[0030] S104: obtaining a first temperature delay feature based on the temperature delay image through a first temperature-time convolution network; the first temperature delay feature is used to detect the degree of temperature delay at multiple power-off time points.

[0031] S105: Based on the multiple probe time-temperature images, determine the temperature changes corresponding to different power-off time points to obtain a second temperature delay feature.

[0032] S106: Input the first temperature delay feature and the second temperature delay feature into a prediction network to obtain a predicted power-off time point; the predicted power-off time point represents the earliest predicted power-off time point that can reach a preset temperature.

[0033] Among them, in this embodiment, the prediction network is a fully connected neural network (Fully Connected Neural Network, FCNN).

[0034] The prediction network is a network trained using historical data.

[0035] S107: Sending a signal to stop power supply at the predicted power supply stop time point.

[0036] Establish a test between the power supply amount and the probe temperature at the specified time, and stop when the temperature reaches a certain level; (the temperature will rise and fall within a certain range) Optionally, obtaining a first temperature delay feature based on the temperature delay image through a first temperature-time convolutional network includes: The first temperature-time convolution network includes a two-dimensional convolution kernel of p*((2n+1)*2).

[0037] Wherein, p and n are positive integers.

[0038] p represents the width of the temperature delay image, (2n+1) represents the time length between the power-off time point and the corresponding multiple stop time points; ((2n+1)*2) represents the change in the delay between the temperature of two power-off time points and the corresponding highest temperature found by using a two-dimensional convolution kernel.

[0039] With a step size of ((2n+1)*2), the two-dimensional convolution kernel included in the first temperature-time convolution network is convolved on the temperature delay image to obtain a first detection feature vector.

[0040] Through the above method, the special two-dimensional convolution kernel contained in the first temperature-time convolution network can convert the image into a one-dimensional vector.

[0041] The first detection feature vector is input into a first neural network to detect the characteristics of the temperature change at two power-off time points to obtain a first temperature delay feature.

[0042] Wherein, the first neural network is a fully connected neural network (Fully Connected Neural Network, FCNN).

[0043] Optionally, acquiring corresponding multiple probe time-temperature images based on multiple power-off time points includes: Acquire multiple time points around the stop; the time points around the stop include n time points earlier than the power-off time point and n time points later than the power-off time point; the time lengths of any two adjacent time points around the stop are the same; Obtain the temperatures corresponding to multiple stop-around time points as probe temperatures; A time-temperature coordinate axis is constructed with the time point as the abscissa and the probe temperature as the ordinate; the abscissa of the origin of the time-temperature coordinate axis represents the time point when power is turned on; the ordinate of the origin of the time-temperature coordinate axis represents the temperature as 0; With the horizontal axis of the time-temperature coordinate axis as the length and the vertical axis as the width, the stop surrounding time points and the corresponding probe temperatures are plotted as a probe time-temperature image; the length of the probe time-temperature image represents the time length between three adjacent stop power-on time points; the width of the probe time-temperature image represents 0 to 100 degrees Celsius.

[0044] The probe time-temperature image is a point image.

[0045] The lower left corner of the probe time-temperature image is the origin.

[0046] In this embodiment, the probe time temperature image has a size of 512*512. The coordinate axes 0, 1, ..., 511, 512 correspond to each pixel of the probe time temperature image respectively. The length of the probe time temperature image is evenly divided into 2n+1 points. If n is 8, take the horizontal coordinate 0 as the starting point, round (512 / 17) down to 30, and the points on the coordinate axis are: (0,0), (30,y1), (60,y2), (90,y3), (120,y4), (150,y5), (180,y6), (210,y7), (240,y8), (270,y9), (300,y10), (330,y11), (360,y12), (390,y13), (420,y14), (450y15), (480,y16). 0, y1, y2, y3, y4, y5, y6, y7, y8, y9, y10, y11, y12, y13, y14, y15, y16 represent the temperatures corresponding to a plurality of stop ambient time points and power-off time points, and y8 represents the temperature corresponding to the power-off time point.

[0047] Wherein, the probe time-temperature image is a binary image.

[0048] Optionally, the determining, based on multiple probe time-temperature images, temperature changes corresponding to different power-off time points to obtain a second temperature delay feature includes: The time point of power-off and a plurality of time points around power-off in the probe time-temperature image are combined with the corresponding temperatures to construct a curve to obtain a time-temperature curve.

[0049] In this embodiment, the curve image is a curve constructed by using polynomial interpolation to combine the power-off time point and multiple stop surrounding time points in the probe time-temperature image with multiple points represented by corresponding temperatures.

[0050] Multiple probe time-temperature images correspond to multiple time-temperature curves; According to the time points of power-off from early to late, multiple probe time-temperature images are superimposed to obtain a three-dimensional time-temperature image.

[0051] The length of the three-dimensional time-temperature image is equal to the length of the curve image, the height of the three-dimensional time-temperature image is equal to the height of the curve image, and the width of the three-dimensional time-temperature image is equal to the sum of the widths of multiple curve images.

[0052] A first change feature is obtained based on the three-dimensional time-temperature image through a second temperature-time convolutional network.

[0053] Based on the multiple time-temperature curves, the coefficient change is detected to obtain a second change feature.

[0054] A second temperature delay characteristic is obtained according to the first change characteristic and the second change characteristic.

[0055] Optionally, obtaining the first change feature based on the three-dimensional time-temperature image through the second temperature-time convolution network includes: The second temperature-time convolution network includes a three-dimensional temperature-time convolution network and a two-dimensional temperature-time convolution network.

[0056] In this embodiment, the three-dimensional temperature-time convolutional network is a three-dimensional convolutional neural network (3D Convolutional Neural Networks, CNN). The two-dimensional temperature-time convolutional network is a convolutional neural network (Convolutional Neural Networks, CNN).

[0057] The three-dimensional temperature-time convolution network includes a three-dimensional convolution kernel of p*2*2; p represents the height of the three-dimensional time-temperature image; In the width direction of the three-dimensional time-temperature image, with a step size of 1, the three-dimensional convolution kernel of the three-dimensional time-temperature image is convolved on the three-dimensional time-temperature image, and the temperature change of different starting temperatures when the power is on for the same time is detected to obtain a first characteristic image; the width of the first characteristic image corresponds to the width of the three-dimensional time-temperature image; the length of the first characteristic image corresponds to the length of the three-dimensional time-temperature image.

[0058] Based on the first feature image, a first change feature is obtained through a two-dimensional temperature-time convolution network; the first change feature represents the feature of the feature change of adjacent power-off time points.

[0059] Optionally, obtaining a first change feature based on the first feature image through a two-dimensional temperature-time convolution network includes: The two-dimensional temperature-time convolution network includes an m*2 two-dimensional convolution kernel; m represents the width of the first feature image.

[0060] Wherein, m is a positive integer.

[0061] In the long direction of the first feature image, with a step size of 1, the two-dimensional convolution kernel of the two-dimensional temperature-time convolution network is convolved on the first feature image to obtain a first change feature; the first change feature is a one-dimensional vector.

[0062] Optionally, the detecting coefficient change based on the multiple time-temperature curves to obtain a second change feature includes: According to the power-off time points from early to late, the coefficients of the time-temperature curve are sequentially input into the time convolution network to obtain the second change feature.

[0063] Optionally, the method of detecting the highest temperature at the power-off time point and the corresponding surrounding time points based on multiple probe time-temperature images to obtain a temperature delay image includes: In the probe time-temperature image, the highest detected temperature value is taken as the highest temperature; multiple probe time-temperature images correspond to multiple highest temperatures; In the probe time-temperature image, the time point corresponding to the highest temperature is taken as the highest temperature time point; The temperature corresponding to the power-off time point corresponding to the probe time-temperature image is used as the power-off temperature; The power-off time point, power-off temperature, maximum temperature time point and maximum temperature corresponding to the probe time-temperature image are taken as a time-temperature set; Multiple probe time-temperature images correspond to obtaining multiple time-temperature sets; Based on multiple time-temperature sets, a temperature time-lapse image is obtained.

[0064] Optionally, obtaining a temperature time-lapse image based on multiple time-temperature sets includes: Obtaining the latest power-off time point; the latest power-off time point represents a power-off time point that is later than other power-off time points among the multiple power-off time points; A complete time image is acquired; the length of the complete time image represents multiple de-energization time points from the start time point of energization to the latest de-energization time point.

[0065] Among them, as in this embodiment, two adjacent power-off time points are divided into 2n time points, and the number of power-off time points is m, so the complete time image is divided into 2n*m points to represent the power-off time points and the surrounding time points.

[0066] Mark the point consisting of the power-off time point and the power-off temperature in the time-temperature set in the complete time image to obtain the stop position; The point consisting of the highest power-on time point and the highest power-on temperature in the time-temperature set is marked in the complete time image to obtain the highest position; multiple stop positions and multiple highest positions are obtained corresponding to multiple time-temperature sets.

[0067] The highest power-on time point is one of the multiple stop peripheral time points.

[0068] The stop position and the corresponding highest position in the complete time image are connected with a straight line to obtain a temperature time-lapse image.

[0069] Example 2

[0070] Based on the above-mentioned method for controlling the heat of a heated ultrasonic probe, an embodiment of the present invention also provides a heated ultrasonic probe heat control system, the system comprising an acquisition module, a temperature delay image acquisition module, a first temperature delay detection module, a second temperature delay detection module, a prediction module and a reminder module.

[0071] An acquisition module is used to acquire a power-on start time point and a plurality of power-off stop time points; the power-on start time point indicates a power-on start time point; the power-off stop time point indicates a power-off stop time point; based on the plurality of power-off stop time points, a plurality of corresponding probe time-temperature images are acquired; the probe time-temperature images include temperatures at a plurality of stop surrounding time points; the stop surrounding time points include n time points earlier than the power-off stop time point and n time points later than the power-off stop time point; A temperature time-lapse image acquisition module is used to detect the highest temperature at the power-off time point and the corresponding surrounding time points based on multiple probe time temperature images to obtain a temperature time-lapse image; A first temperature delay detection module, configured to obtain a first temperature delay feature based on the temperature delay image through a first temperature time convolution network; the first temperature delay feature is used to detect the degree of temperature delay at multiple power-off time points; A second temperature delay detection module is used to determine the temperature change corresponding to different power-off time points based on multiple probe time-temperature images to obtain a second temperature delay feature; A prediction module, configured to input the first temperature delay feature and the second temperature delay feature into a prediction network to obtain a predicted power-off time point; the predicted power-off time point represents the earliest predicted power-off time point that can reach a preset temperature; The reminder module is used to send a power-off signal at the predicted power-off time point.

[0072] The algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus.

[0073] Various general purpose systems can also be used with the teachings based herein. From the above description, the structure required to construct such a system is apparent.

[0074] Furthermore, the present invention is not specific to any particular programming language.

[0075] It will be appreciated that a variety of programming languages ​​may be used to implement the teachings of the present invention as described herein and that the above descriptions using specific languages ​​are intended to disclose the best mode for carrying out the present invention.

Claims

1. A method for controlling the heat of a heated ultrasonic probe, characterized in that: include: Acquire a power-on start time point and a plurality of power-off stop time points; the power-on start time point indicates a time point at which power is started; the power-off stop time point indicates a time point at which power is stopped; Based on multiple power-off time points, a corresponding multiple probe time-temperature images are acquired; the probe time-temperature images include temperatures of multiple stop-around time points; the stop-around time points include n time points earlier than the power-off time point and n time points later than the power-off time point; Based on multiple probe time-temperature images, the highest temperature at the time point of power-off and the corresponding time points around the power-off is detected to obtain a temperature time-lapse image; A first temperature delay feature is obtained based on the temperature delay image through a first temperature-time convolution network; the first temperature delay feature is used to detect the degree of delay of the temperature at multiple power-off time points; Based on multiple probe time-temperature images, determine the temperature changes corresponding to different power-off time points to obtain a second temperature delay feature; The first temperature delay feature and the second temperature delay feature are input into a prediction network to obtain a predicted power-off time point; the predicted power-off time point represents the earliest predicted power-off time point that can reach a preset temperature; A signal to stop energizing is sent at the predicted energizing stop time point.

2. A method for controlling the heat of a heated ultrasonic probe according to claim 1, characterized in that: The first temperature time-delay feature is obtained based on the temperature time-delay image through the first temperature time convolution network, including: The first temperature-time convolution network includes a two-dimensional convolution kernel of p*((2n+1)*2); p represents the width of the temperature delay image, (2n+1) represents the time length between the power-off time point and the corresponding multiple stop surrounding time points; ((2n+1)*2) represents the change in the delay between the temperature at two power-off time points and the corresponding highest temperature found by using a two-dimensional convolution kernel; With a step size of ((2n+1)*2), convolving the two-dimensional convolution kernel included in the first temperature-time convolution network on the temperature delay image to obtain a first detection feature vector; The first detection feature vector is input into a first neural network to detect the characteristics of the temperature change at two power-off time points to obtain a first temperature delay feature.

3. A method for controlling the heat of a heated ultrasonic probe according to claim 1, characterized in that: The step of acquiring corresponding multiple probe time-temperature images based on multiple power-off time points includes: Acquire multiple time points around the stop; the time points around the stop include n time points earlier than the power-off time point and n time points later than the power-off time point; the time lengths of any two adjacent time points around the stop are the same; Obtain the temperatures corresponding to multiple stop-around time points as probe temperatures; A time-temperature coordinate axis is constructed with the time point as the abscissa and the probe temperature as the ordinate; the abscissa of the origin of the time-temperature coordinate axis represents the time point when power is turned on; the ordinate of the origin of the time-temperature coordinate axis represents the temperature as 0; With the horizontal axis of the time-temperature coordinate axis as the length and the vertical axis as the width, the probe time-temperature image is drawn by taking the stop surrounding time points and the corresponding probe temperatures; the length of the probe time-temperature image represents the time length between three adjacent stop power-on time points; the width of the probe time-temperature image represents 0 to 100 degrees Celsius; The probe time-temperature image is a point image.

4. A method for controlling the heat of a heated ultrasonic probe according to claim 1, characterized in that: The method of determining the temperature change corresponding to different power-off time points based on the multiple probe time-temperature images to obtain the second temperature delay feature includes: The time point of power-off and multiple time points around power-off in the probe time-temperature image are used to construct a curve with the corresponding temperature to obtain a time-temperature curve; Multiple probe time-temperature images correspond to multiple time-temperature curves; According to the time point of power off from early to late, multiple probe time-temperature images are superimposed to obtain a three-dimensional time-temperature image; Obtaining a first change feature based on the three-dimensional time-temperature image through a second temperature-time convolutional network; Based on the multiple time-temperature curves, detect the coefficient change to obtain a second change feature; A second temperature delay characteristic is obtained according to the first change characteristic and the second change characteristic.

5. A method for controlling the heat of a heated ultrasonic probe according to claim 4, characterized in that: The first change feature is obtained based on the three-dimensional time-temperature image through the second temperature-time convolution network, including: The second temperature-time convolution network includes a three-dimensional temperature-time convolution network and a two-dimensional temperature-time convolution network; The three-dimensional temperature-time convolution network includes a three-dimensional convolution kernel of p*2*2; p represents the height of the three-dimensional time-temperature image; In the width direction of the three-dimensional time-temperature image, the three-dimensional convolution kernel of the three-dimensional time-temperature image is convolved on the three-dimensional time-temperature image with a step size of 1, and the temperature change of different starting temperatures when the power is turned on for the same time is detected to obtain a first characteristic image; the width of the first characteristic image corresponds to the width of the three-dimensional time-temperature image; the length of the first characteristic image corresponds to the length of the three-dimensional time-temperature image; Based on the first feature image, a first change feature is obtained through a two-dimensional temperature-time convolution network; the first change feature represents the feature of the feature change of adjacent power-off time points.

6. A method for controlling the heat of a heated ultrasonic probe according to claim 5, characterized in that: The obtaining of a first change feature based on the first feature image through a two-dimensional temperature-time convolution network includes: The two-dimensional temperature-time convolution network includes a two-dimensional convolution kernel of m*2; m represents the width of the first feature image; In the long direction of the first feature image, with a step size of 1, the two-dimensional convolution kernel of the two-dimensional temperature-time convolution network is convolved on the first feature image to obtain a first change feature; the first change feature is a one-dimensional vector.

7. A method for controlling the heat of a heated ultrasonic probe according to claim 4, characterized in that: The detecting coefficient change based on the multiple time-temperature curves to obtain a second change feature includes: According to the power-off time points from early to late, the coefficients of the time-temperature curve are sequentially input into the time convolution network to obtain the second change feature.

8. The method for controlling the heat of a heated ultrasonic probe according to claim 1, characterized in that: The method of detecting the highest temperature at the power-off time point and the corresponding surrounding time points based on multiple probe time-temperature images to obtain a temperature delay image includes: In the probe time-temperature image, the highest detected temperature value is taken as the highest temperature; multiple probe time-temperature images correspond to multiple highest temperatures; In the probe time-temperature image, the time point corresponding to the highest temperature is taken as the highest temperature time point; The temperature corresponding to the power-off time point corresponding to the probe time-temperature image is used as the power-off temperature; The power-off time point, power-off temperature, maximum temperature time point and maximum temperature corresponding to the probe time-temperature image are taken as a time-temperature set; Multiple probe time-temperature images correspond to obtaining multiple time-temperature sets; Based on multiple time-temperature sets, a temperature time-lapse image is obtained.

9. A method for controlling the heat of a heated ultrasonic probe according to claim 8, characterized in that: The step of obtaining a temperature time-lapse image based on multiple time-temperature sets includes: Obtaining the latest power-off time point; the latest power-off time point represents a power-off time point that is later than other power-off time points among the multiple power-off time points; Acquire a complete time image; the length of the complete time image represents multiple de-energization time points from the start time point of energization to the latest de-energization time point; Mark the point consisting of the power-off time point and the power-off temperature in the time-temperature set in the complete time image to obtain the stop position; The point consisting of the highest power-on time point and the highest power-on temperature in the time-temperature set is marked in the complete time image to obtain the highest position; multiple stop positions and multiple highest positions are obtained corresponding to multiple time-temperature sets; The stop position and the corresponding highest position in the complete time image are connected with a straight line to obtain a temperature time-lapse image.

10. A heat control system for a heated ultrasonic probe, characterized in that: include: An acquisition module is used to acquire a power-on start time point and a plurality of power-off stop time points; the power-on start time point indicates a power-on start time point; the power-off stop time point indicates a power-off stop time point; based on the plurality of power-off stop time points, a plurality of corresponding probe time-temperature images are acquired; the probe time-temperature images include temperatures at a plurality of stop surrounding time points; the stop surrounding time points include n time points earlier than the power-off stop time point and n time points later than the power-off stop time point; A temperature time-lapse image acquisition module is used to detect the highest temperature at the power-off time point and the corresponding surrounding time points based on multiple probe time temperature images to obtain a temperature time-lapse image; A first temperature delay detection module, configured to obtain a first temperature delay feature based on the temperature delay image through a first temperature time convolution network; the first temperature delay feature is used to detect the degree of temperature delay at multiple power-off time points; A second temperature delay detection module is used to determine the temperature change corresponding to different power-off time points based on multiple probe time-temperature images to obtain a second temperature delay feature; A prediction module, configured to input the first temperature delay feature and the second temperature delay feature into a prediction network to obtain a predicted power-off time point; the predicted power-off time point represents the earliest predicted power-off time point that can reach a preset temperature; The reminder module is used to send a power-off signal at the predicted power-off time point.

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