Method and device for determining tissue rotation cutting force, and readable storage medium

Abstract

Embodiments of the present application disclose a method and device for determining the rotation cutting force of tissue and a readable storage medium. The method comprises obtaining tissue characteristic information related to the softness and hardness of target tissue; obtaining softness and hardness information of the target tissue according to the tissue characteristic information, wherein the softness and hardness information is used to represent the softness and hardness of different positions of the target tissue; and determining the rotation cutting force of the tissue at different positions of the target tissue according to the corresponding relationship between the softness and hardness and the rotation cutting force. The rotation cutting efficiency can be improved.

Description

Technical Field

[0001] This invention relates to the field of biomedicine, and more specifically to a method, apparatus, and readable storage medium for determining tissue cutting force. Background Technology

[0002] With technological advancements, minimally invasive rotary biopsy can now be used to biopsies or perform minimally invasive treatments on human tissues (such as tumors, nodules, and benign lesions). Also known as vacuum-assisted fully automated minimally invasive rotary biopsy, this procedure involves making a small incision (a few millimeters) in the skin of the tissue's location. Under ultrasound guidance, a rotary biopsy blade is inserted through this incision to the tissue's location. The blade then cuts layer by layer, and negative pressure suction removes the tissue from the body, achieving the purpose of biopsy or minimally invasive treatment. Minimally invasive rotary biopsy offers advantages such as minimal trauma, inconspicuous scarring, and short operation time.

[0003] Currently, in minimally invasive rotary cutting, although ultrasound can guide the puncture of the rotary cutting blade, the cutting force of the blade cannot be determined. This causes medical staff to spend time judging the cutting force during the rotary cutting procedure, affecting the cutting efficiency. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, device, and computer-readable storage medium for determining tissue rotary cutting force, which can improve rotary cutting efficiency.

[0005] This invention provides a method for determining the force of tissue rotary cutting, the method comprising:

[0006] Obtain tissue characteristic information related to the hardness or softness of the target tissue;

[0007] The softness / hardness information of the target tissue is obtained based on the tissue characteristic information, wherein the softness / hardness information is used to characterize the softness / hardness at different locations of the target tissue;

[0008] Based on the correspondence between hardness and cutting force, the cutting force is determined when cutting tissue at different locations of the target tissue.

[0009] In some embodiments, obtaining the softness / hardness information of the target tissue based on the tissue characteristic information includes:

[0010] The tissue characteristic information is input into the fusion model, and the fusion model outputs the softness and hardness information of the target tissue.

[0011] In some embodiments, the target tissue has multiple different organizational characteristic information, and the step of inputting the organizational characteristic information into a fusion model and outputting the softness / hardness information of the target tissue by the fusion model includes:

[0012] The fusion model performs fusion calculations on the multiple different organizational characteristic information according to the weight of each organizational characteristic information to obtain the softness and hardness information of the target organization.

[0013] In some embodiments, the weights assigned to each of the organizational characteristic information items are obtained based on the following method:

[0014] Linear regression is performed on the training data of the fusion model to obtain the weights of each of the tissue characteristic information.

[0015] In some embodiments, the organizational characteristic information includes the elasticity information of the target organization, the elasticity information being used to characterize the elasticity of the target organization at different locations;

[0016] The acquisition of tissue characteristic information related to the hardness or softness of the target tissue includes:

[0017] Obtain quasi-static elastic information and / or shear wave elastic information of the target tissue, wherein the quasi-static elastic information is used to characterize the relative elasticity at different locations of the target tissue, and the shear wave elastic information is used to characterize the absolute elasticity at different locations of the target tissue;

[0018] The elastic information of the target tissue is obtained based on the quasi-static elastic information and / or the shear wave elastic information.

[0019] In some embodiments, obtaining the elastic information of the target tissue based on the quasi-static elastic information and the shear wave elastic information includes:

[0020] The quasi-static elastic information and the shear wave elastic information are fused and calculated to obtain the elastic information of the target tissue.

[0021] In some embodiments, the tissue characteristic information includes the composition information of the target tissue, wherein the composition information is used to characterize the constituent substances at different locations of the target tissue and the content of each constituent substance;

[0022] The acquisition of tissue characteristic information related to the hardness or softness of the target tissue includes:

[0023] The ultrasonic wave is emitted toward the target tissue, and the echo signal of the ultrasonic wave is received.

[0024] The compositional information of the target tissue is obtained by extracting the constituent substances and the content of each constituent substance at different locations of the target tissue from the echo signal.

[0025] In some embodiments, the tissue characteristic information includes density information of the target tissue, the density information being used to characterize the density at different locations of the target tissue;

[0026] The acquisition of tissue characteristic information related to the hardness or softness of the target tissue includes:

[0027] The ultrasonic wave is emitted toward the target tissue, and the echo signal of the ultrasonic wave is received.

[0028] The density of the target tissue at different locations is extracted from the echo signal to obtain the density information of the target tissue.

[0029] In another aspect, the present invention provides a device for determining the force of tissue rotary cutting, the device comprising:

[0030] The acquisition module is used to acquire tissue characteristic information related to the softness or hardness of the target tissue.

[0031] The first determining module is configured to obtain the softness / hardness information of the target tissue based on the tissue characteristic information, wherein the softness / hardness information is used to characterize the softness / hardness at different locations of the target tissue; and

[0032] The second determining module is used to determine the rotary cutting force when rotary cutting tissue at different locations of the target tissue according to the correspondence between the degree of softness and the rotary cutting force.

[0033] In another aspect, the present invention provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the method described above.

[0034] In another aspect, the present invention provides an electronic device comprising a processor and a memory, the memory being used to store a computer program which, when executed by the processor, implements the method described above.

[0035] In some embodiments of this application, the softness / hardness information of the target tissue is obtained based on the tissue characteristic information. Then, based on the correspondence between the softness / hardness and the cutting force, the cutting force can be determined when cutting tissue at different locations of the target tissue. In this way, medical personnel performing the cutting procedure no longer need to spend time manually judging the cutting force at each location, thereby improving the cutting efficiency. Attached Figure Description

[0036] The features and advantages of the invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the invention in any way. In the drawings:

[0037] Figure 1 A schematic diagram of a rotary cutter provided in one embodiment of this application is shown;

[0038] Figure 2 A flowchart illustrating a method for determining tissue rotary cutting force according to an embodiment of this application is shown;

[0039] Figure 3 A schematic diagram of a target organization provided in one embodiment of this application is shown;

[0040] Figure 4 This illustration shows a schematic diagram of the location information of a target organization provided in one embodiment of this application;

[0041] Figure 5 It shows Figure 4 A diagram illustrating the resilience of the target organization;

[0042] Figure 6 It shows Figure 4 A schematic diagram illustrating the composition information of the target organization;

[0043] Figure 7 It shows Figure 4 A schematic diagram illustrating the density information of the target tissue.

[0044] Figure 8 It shows Figure 4 A diagram illustrating the hardness and softness of the target tissue.

[0045] Figure 9 A schematic diagram of the functional modules of a tissue slicing force determination device provided in one embodiment of this application is shown;

[0046] Figure 10 A schematic diagram of the structure of an electronic device provided in one embodiment of this application is shown. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Before describing the solution of this application, the principle of rotary cutting of the rotary cutter will be explained.

[0049] Please see Figure 1 This is a schematic diagram of a rotary cutter 100 provided in one embodiment of this application. Figure 1 In this design, the rotary cutter 100 includes a cutting groove 11. Under ultrasound guidance, after the rotary cutter 100 is inserted into the location of the target tissue, the target tissue can first be adsorbed into the cutting groove 11 using vacuum suction technology. Then, the target tissue within the cutting groove 11 is rotary-cut, and finally, the cut target tissue is transported outside the body. The target tissue includes, but is not limited to, tumor tissue, nodules, and benign lesions. Typically, because the rotary cutter 100 is relatively small, the cutting groove 11 cannot accommodate all the target tissue at once. Therefore, the cutting of the target tissue can be performed in multiple stages. That is, only a portion of the target tissue can be adsorbed into the cutting groove 11 for cutting each time.

[0050] The width X of the rotary cutting groove 11 can also be called the opening size. This opening size can be adjusted according to the width of the target tissue to be cut each time. For example, if the width of the target tissue to be cut is 1 cm during the first cut, the opening size of the rotary cutting blade 100 can be adjusted to 1 cm; if the width of the target tissue to be cut is 8 mm during the second cut, the opening size of the rotary cutting blade 100 can be adjusted to 8 mm. Of course, it is understandable that the opening size of the rotary cutting blade 100 can have a maximum limit. If the width of the target tissue to be cut exceeds this maximum limit, the cuts will be performed in multiple stages. For example, if the maximum allowable opening size of the rotary cutting blade 100 is 3 cm, and the width of the target tissue to be cut is 4 cm, then the target tissue needs to be cut in multiple stages.

[0051] Based on the above description, this application proposes a method for determining the cutting force of a tissue rotary cutter. This method allows for determining the cutting force according to the hardness of the target tissue, eliminating the need for medical personnel to spend time judging the cutting force during the cutting process, thereby improving cutting efficiency. The cutting force characterizes the force applied by the rotary cutter when cutting the target tissue within the cutting groove. Different cutting forces can be used to cut the target tissue according to its hardness. This method for determining the tissue cutting force can be applied to electronic devices. These electronic devices can be medical devices. Please refer to [link to relevant documentation]. Figure 2 This is a flowchart illustrating a method for determining tissue cutting force according to an embodiment of this application. Figure 2 In this study, the method for determining the shearing force of tissue microstructures includes the following steps:

[0052] Step S21: Obtain tissue characteristic information related to the softness and hardness of the target tissue.

[0053] In some embodiments, tissue characteristic information is used to characterize the tissue characteristics related to the degree of softness and hardness at different locations of the target tissue. Tissue characteristics can also be referred to as tissue features. Each tissue characteristic corresponds to a piece of tissue characteristic information. Specifically, tissue characteristics may include, but are not limited to, the elasticity, density, and composition of the target tissue; correspondingly, tissue characteristic information may include, but is not limited to, the elasticity information, density information, and composition information of the target tissue. Elasticity information is used to characterize the elasticity at different locations of the target tissue and may include displacement, strain, strain rate, elastic modulus, etc., without specific limitations; density information is used to characterize the density at different locations of the target tissue; composition information is used to characterize the constituent substances and the content of each constituent substance at different locations of the target tissue. Constituent substances include, but are not limited to, water, protein, fat, etc. In this application, the constituent substances and their contents can be collectively referred to as composition.

[0054] Based on the above introduction to organizational characteristic information, it can be understood that within a target organization, the same organizational characteristic can be different or the same at different locations. The following will combine... Figure 3 Let's illustrate with examples. Figure 3 In this context, the target organization is divided into five regions: A, B, C, D, and E. The flexibility of each region within these five regions can be as follows:

[0055] Region A: Elasticity is T1, density is M1;

[0056] Region B: Elasticity is T2, density is M2;

[0057] Region C: Elasticity is T3, density is M3;

[0058] Region D: Elasticity is T4, density is M4;

[0059] Region E: Elasticity is T5, density is M5.

[0060] Among them, T1, T2, T3, T4, and T5 may not be completely identical, indicating that the elasticity of the target tissue in these five regions may not be completely identical; M1, M2, M3, M4, and M5 may not be completely identical, indicating that the density of the target tissue in these five regions may not be completely identical.

[0061] Therefore, in this application, organizational characteristic information is used to characterize the organizational characteristics at various locations in the target organization, and each organizational characteristic corresponds to an organizational characteristic information.

[0062] In some embodiments, organizational characteristic information related to the firmness or softness of a target tissue refers to organizational characteristic information corresponding to organizational characteristics that affect the firmness or softness of the target tissue. Typically, the firmness or softness of a target tissue is the result of the combined influence of multiple organizational characteristics. The organizational characteristic information corresponding to these multiple organizational characteristics can be the organizational characteristic information related to the firmness or softness of the target tissue.

[0063] For example, for a target organization, different elasticities can result in different degrees of firmness, and target organizations with different compositions can also have different degrees of firmness. This indicates that both the elasticity and composition of the target organization affect its firmness. The firmness of a target organization is the result of the combined influence of its elasticity and composition. Therefore, organizational characteristic information related to the firmness of a target organization can include elasticity information and composition information.

[0064] In this embodiment, the elasticity, composition, and density information of the target tissue are used as tissue characteristic information related to the hardness or softness of the target tissue. It should be noted that the tissue characteristic information related to the hardness or softness of the target tissue can be determined based on the correlation between the target tissue's hardness or softness and each tissue characteristic information, depending on the actual situation. For example, among the aforementioned elasticity, composition, and density information, if it is assumed that the hardness or softness of the target tissue has a high correlation with elasticity information but a low correlation with composition and density information, then composition and density information can be excluded.

[0065] Of course, in accordance with actual needs, other organizational characteristic information of the target tissue can be added on the basis of the above-mentioned elasticity information, composition information and density information, and the above information can be used together as organizational characteristic information related to the softness and hardness of the target tissue; or at least one of the above-mentioned elasticity information, composition information and density information can be used as organizational characteristic information related to the softness and hardness of the target tissue, and this application does not limit this.

[0066] In this embodiment, the elasticity information can be obtained through the following steps:

[0067] 1) Obtain quasi-static elastic information and / or shear wave elastic information of the target tissue.

[0068] Optionally, only quasi-static elastic information, only shear wave elastic information, or both quasi-static elastic information and shear wave elastic information can be obtained. The specific acquisition method can be set according to the requirements.

[0069] Among them, quasi-static elasticity information is used to characterize the relative elasticity at different locations of the target tissue, while shear wave elasticity information is used to characterize the absolute elasticity at different locations of the target tissue. For any location of the target tissue, relative elasticity refers to the elastic characteristics of that location relative to the elasticity at other locations. For example, whether the elasticity at that location is better or worse than the elasticity at other locations. Absolute elasticity refers to the elastic modulus at various locations of the target tissue.

[0070] Furthermore, quasi-static elastic information can be obtained based on quasi-static elastic imaging of the target tissue. Shear wave elastic information can be obtained based on shear wave elastic imaging of the target tissue. Those skilled in the art can employ various techniques to achieve quasi-static elastic imaging and shear wave elastic imaging, which will not be elaborated upon here.

[0071] 2) Based on quasi-static elastic information and / or shear wave elastic information, the elastic information of the target tissue is obtained.

[0072] When only quasi-static elastic information of the target tissue is obtained, the obtained shear wave elastic information is used as the elastic information of the target tissue. When only shear wave elastic information is obtained, the obtained shear wave elastic information is used as the elastic information of the target tissue. In this embodiment, when both quasi-static and shear wave elastic information are obtained, they can be fused to calculate the elastic information of the target tissue. Specifically, for any location of the target tissue, the relative and absolute elasticities at that location can be fused to calculate the elasticity at that location. The elasticities calculated in this way comprehensively consider both the relative and absolute elasticities at the corresponding locations, resulting in more objective and accurate results. The quasi-static elastic information includes, but is not limited to, strain, strain rate, strain ratio, and strain distribution characteristics; the shear wave elastic information includes, but is not limited to, shear wave velocity, elastic modulus, and elastic modulus distribution characteristics.

[0073] In some embodiments, static elasticity information and shear wave elasticity information can be input into a trained elasticity model, which then outputs the elasticity information of the target tissue based on the static elasticity information and shear wave elasticity information. The elasticity model can be trained using linear regression or machine learning.

[0074] In this embodiment, the composition information can be obtained by: emitting ultrasonic waves to the target tissue and receiving the echo signals of the ultrasonic waves; extracting the constituent substances contained in the target tissue at different locations and the content of each constituent substance from the echo signals to obtain the composition information of the target tissue.

[0075] This process can also be called B-mode ultrasound imaging of the target tissue.

[0076] In this embodiment, density information can be obtained by emitting ultrasonic waves to the target tissue and receiving the echo signals of the ultrasonic waves; extracting the density of the target tissue at different locations from the echo signals to obtain the density information of the target tissue.

[0077] This process can also be called color Doppler ultrasound imaging of the target tissue.

[0078] Step S22: Obtain the softness / hardness information of the target tissue based on the tissue characteristic information, wherein the softness / hardness information is used to characterize the softness / hardness at different locations of the target tissue.

[0079] In some embodiments, tissue characteristic information can be input into a fusion model, which then outputs information about the softness / hardness of the target tissue. This fusion model can be pre-trained. The trained fusion model can have weights assigned to each tissue characteristic. These weights characterize the correlation between the tissue characteristic and the softness / hardness of the target tissue. Tissue characteristics with a higher correlation to the softness / hardness of the target tissue can have higher weights; tissue characteristics with a lower correlation can have lower weights.

[0080] For example, in this embodiment, it is assumed that elasticity has the greatest correlation with the softness and hardness of the target tissue, composition has a relatively small correlation with the softness and hardness of the target tissue, and density has the least correlation with the softness and hardness of the target tissue. In this case, the weight corresponding to elasticity can be the largest, the weight corresponding to composition can be relatively small, and the weight corresponding to density can be the smallest.

[0081] The fusion model calculates the hardness / softness of a target organization by fusing multiple different organizational characteristic information according to their respective weights. Specifically, the fusion model obtains the organizational characteristics at various locations within the target organization based on the individual organizational characteristic information, and then calculates the hardness / softness at each location according to the weights of these characteristics. When calculating the hardness / softness at each location, the influence of each organizational characteristic on the hardness / softness is considered based on its weight. Organizational characteristics with larger weights have a greater impact on the hardness / softness, while those with smaller weights have a smaller impact.

[0082] For example, in this embodiment, the elasticity, composition, and density of the target tissue at various locations are obtained based on elasticity information, composition information, and density information. For any location A of the target tissue, the elasticity, composition, and density at location A are fused and calculated to obtain the hardness / softness at location A. Specifically, when fusion-calculating the tissue characteristics at location A, it is assumed that elasticity has the largest weight, composition has a relatively small weight, and density has the smallest weight. Therefore, the influence of elasticity at location A on the hardness / softness is primarily considered, followed by the influence of the tissue at location A on the hardness / softness, and finally the influence of density at location A on the hardness / softness.

[0083] In this embodiment, the fusion model can be trained using linear regression. The weights assigned to each tissue characteristic can be obtained by performing linear regression on the training data of the fusion model.

[0084] Step S23: Determine the rotary cutting force when rotary cutting tissue at different locations of the target tissue according to the correspondence between softness and hardness and rotary cutting force.

[0085] In some embodiments, the relationship between the hardness of the target tissue and the rotary cutting force can be pre-established. Specifically, the rotary cutting force can be positively correlated with the hardness of the target tissue. The harder the target tissue, the greater the rotary cutting force can be; the softer the target tissue, the smaller the rotary cutting force can be.

[0086] Thus, after obtaining the softness and hardness information of the target tissue in step S22, the shearing force at each location of the target tissue can be found based on the correspondence.

[0087] For ease of understanding, the following is combined with Figure 4 Please provide an example. See also... Figure 4 This is a schematic diagram illustrating the location information of a target organization provided in one embodiment of this application. Figure 4 In the diagram, each dashed box can represent a location of the target tissue. The size of this location can be determined according to the size of the target tissue that the rotary cutter can cut in a single pass.

[0088] Combining the above step S21, the elasticity information, composition information, and density information of the target tissue can be obtained. Among them, the elasticity information can be as follows: Figure 5 As shown. Figure 5 In the diagram, T1 to T23 represent the elastic values ​​at each location. The composition information is shown in Figure 6. Figure 6 In the diagram, C1 to C23 represent the composition at each location. The packing density information is shown in Figure 7. Figure 7 In the diagram, D1 to D23 represent the compaction density at each location.

[0089] Combining step S22 above, by inputting elasticity information, composition information, and density information into the fusion model, the softness / hardness information of the target tissue can be obtained. The softness / hardness information can be as follows: Figure 8 As shown. Figure 8 In the diagram, Y1 to Y23 represent the hardness or softness at each location. Figure 8 Taking the first position in the upper left corner as an example, the hardness Y1 at that position can be determined by the weights corresponding to elasticity, composition, and density. Figure 5 T1 in Figure 6 C1 and Figure 7 The result is obtained by performing a fusion calculation on D1 in the matrix.

[0090] Combining the above step S23, according to Figure 8 The system retrieves the softness / hardness information and determines the corresponding rotary cutting force for each location, which is then used as the rotary cutting force for the tissue at that location. For example, if the rotary cutting force corresponding to Y1 is F1 and the rotary cutting force corresponding to Y2 is F2, then the tissue at Y1 will be rotary cut with a rotary cutting force of F1, and the tissue at Y2 will be rotary cut with a rotary cutting force of F2.

[0091] In some embodiments, to facilitate viewing by medical personnel performing the rotary cutting procedure, rotary cutting force information of the target tissue can also be output. This rotary cutting force information characterizes the required rotary cutting force when cutting tissue at different locations within the target tissue. Thus, medical personnel performing the rotary cutting procedure can sequentially cut tissue at different locations based on the rotary cutting force information, eliminating the need for manual judgment of the cutting force at each location and thereby improving cutting efficiency.

[0092] In summary, in the technical solutions of some embodiments of this application, the softness / hardness information of the target tissue is obtained based on tissue characteristic information related to the softness / hardness of the target tissue. Then, based on the correspondence between softness / hardness and cutting force, the cutting force can be determined when cutting tissue at different locations on the target tissue. Thus, medical personnel performing the cutting procedure no longer need to spend time manually judging the cutting force at each location, thereby improving cutting efficiency.

[0093] In addition, in some embodiments of the present application, when generating the softness and hardness information of the target tissue, the elasticity, composition and density of the target tissue at various locations are comprehensively considered, and the obtained softness and hardness information is more accurate, which in turn makes the obtained slicing force more accurate.

[0094] Furthermore, in some related technologies, the location of the target tissue is determined solely by ultrasound guidance during rotary cutting surgery, without assessing its firmness. This application comprehensively considers the elasticity, composition, and density of the target tissue at various locations to generate firmness information, which in turn determines the cutting force at each location. Therefore, compared to some related technologies, the method described in this application makes rotary cutting surgery more convenient for medical personnel.

[0095] Finally, each location of the target tissue has a corresponding rotary cutting force, which ensures that the appropriate force can be applied when rotary cutting each location, avoiding the problem of excessive or insufficient force, thereby reducing power consumption, wear and tear and tissue damage during rotary cutting.

[0096] Please see Figure 9 This is a functional module diagram of a tissue rotary cutting force determination device provided in one embodiment of this application. The tissue rotary cutting force determination device includes:

[0097] The acquisition module is used to acquire tissue characteristic information related to the softness or hardness of the target tissue.

[0098] The first determining module is configured to obtain the softness / hardness information of the target tissue based on the tissue characteristic information, wherein the softness / hardness information is used to characterize the softness / hardness at different locations of the target tissue; and

[0099] The second determining module is used to determine the rotary cutting force when rotary cutting tissue at different locations of the target tissue according to the correspondence between the degree of softness and the rotary cutting force.

[0100] Please see Figure 10 This is a schematic diagram of the structure of an electronic device provided in one embodiment of this application. The electronic device includes a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements the aforementioned method for determining the cutting force.

[0101] The processor can be a central processing unit (CPU). It can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0102] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the methods in the embodiments of this invention. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions, and modules stored in the memory, thereby implementing the methods described in the above embodiments.

[0103] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, the memory may include high-speed random access memory and non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0104] One embodiment of this application also provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the above-described method for determining the cutting force.

[0105] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for determining the force of tissue rotary cutting, characterized in that, The method includes: Obtain tissue characteristic information related to the softness and hardness of the target tissue. The tissue characteristic information includes elasticity information, composition information and density information of the target tissue. The elasticity information is used to characterize the elasticity at different locations of the target tissue. The composition information is used to characterize the constituent substances and the content of each constituent substance at different locations of the target tissue. The density information is used to characterize the density at different locations of the target tissue. Each location of the target tissue is divided according to the size of the tissue that can be cut by a rotary cutter in a single pass. The softness / hardness information of the target tissue is obtained based on the tissue characteristic information, wherein the softness / hardness information is used to characterize the softness / hardness at different locations of the target tissue; Based on the correspondence between hardness and cutting force, the cutting force is determined when cutting tissue at different locations of the target tissue. Wherein, obtaining the softness / hardness information of the target tissue based on the tissue characteristic information includes: The elasticity information, composition information, and density information are input into a fusion model. The fusion model performs fusion calculations according to the weights corresponding to the elasticity information, composition information, and density information, respectively, to obtain the softness and hardness information of the target tissue.

2. The method as described in claim 1, characterized in that, The weights assigned to each of the aforementioned organizational characteristic information are obtained based on the following method: Linear regression is performed on the training data of the fusion model to obtain the weights of each of the tissue characteristic information.

3. The method as described in claim 1, characterized in that, The acquisition of tissue characteristic information related to the hardness or softness of the target tissue includes: Obtain quasi-static elastic information and / or shear wave elastic information of the target tissue, wherein the quasi-static elastic information is used to characterize the relative elasticity at different locations of the target tissue, and the shear wave elastic information is used to characterize the absolute elasticity at different locations of the target tissue; The elastic information of the target tissue is obtained based on the quasi-static elastic information and / or the shear wave elastic information.

4. The method as described in claim 3, characterized in that, The process of obtaining the elastic information of the target tissue based on the quasi-static elastic information and the shear wave elastic information includes: The quasi-static elastic information and the shear wave elastic information are fused and calculated to obtain the elastic information of the target tissue.

5. The method as described in claim 1, characterized in that, The acquisition of tissue characteristic information related to the hardness or softness of the target tissue includes: The ultrasonic wave is emitted toward the target tissue, and the echo signal of the ultrasonic wave is received. The compositional information of the target tissue is obtained by extracting the constituent substances and the content of each constituent substance at different locations of the target tissue from the echo signal.

6. The method as described in claim 1, characterized in that, The acquisition of tissue characteristic information related to the hardness or softness of the target tissue includes: The ultrasonic wave is emitted toward the target tissue, and the echo signal of the ultrasonic wave is received. The density of the target tissue at different locations is extracted from the echo signal to obtain the density information of the target tissue.

7. A device for determining the force of tissue rotary cutting, characterized in that, The device includes: The acquisition module is used to acquire tissue characteristic information related to the softness and hardness of the target tissue. The tissue characteristic information includes elasticity information, composition information and density information of the target tissue. The elasticity information is used to characterize the elasticity at different locations of the target tissue. The composition information is used to characterize the constituent substances and the content of each constituent substance at different locations of the target tissue. The density information is used to characterize the density at different locations of the target tissue. Each location of the target tissue is divided according to the size of the tissue that can be cut by the rotary cutter in a single pass. The first determining module is used to obtain the softness / hardness information of the target tissue based on the tissue characteristic information, wherein the softness / hardness information is used to characterize the softness / hardness at different locations of the target tissue. Specifically, when obtaining the softness / hardness information of the target tissue, the elasticity information, the composition information, and the density information are input into a fusion model. The fusion model performs a fusion calculation according to the weights corresponding to the elasticity information, the composition information, and the density information, respectively, to obtain the softness / hardness information of the target tissue. The second determining module is used to determine the rotary cutting force when rotary cutting tissue at different locations of the target tissue according to the correspondence between the degree of softness and the rotary cutting force.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 6.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory being used to store a computer program that, when executed by the processor, implements the method as described in any one of claims 1 to 6.

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