A multi-scale intestinal torsion simulation method and system based on a virtual body envelope

Abstract

The application discloses a kind of multi-scale intestinal torsion simulation method and system based on virtual body envelope, method includes: constructing the intestinal geometric model including mucous membrane layer, muscle layer and plasma layer;Add virtual envelope body that wraps intestinal geometric model, obtain the deformation characteristics of virtual envelope body by exerting external force on the virtual envelope body;The deformation characteristics are substituted into intestinal geometric model to obtain macro stress field, and the reference feedback force of intestinal geometric model in macro stress field is calculated;Uniformly embedded discrete fiber bundle model in the stress concentration area of intestinal geometric model;According to the overall tensile amount of fiber bundle model, the damage rate of fiber bundle model is calculated;Determine the correction coefficient by damage rate calculation, and the reference feedback force is corrected to obtain tactile feedback force;The present application realizes the synchronous accurate simulation of macroscopic deformation visual reality and microscopic damage tactile feedback in small intestine torsion simulation by virtual body envelope and discrete fiber bundle multiscale coupling.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of surgical simulation, and particularly relates to a multi-scale intestinal torsion simulation method and system based on a virtual body envelope. BACKGROUND

[0002] Intestinal torsion is a common acute abdomen in general surgery, which has a rapid onset. If it cannot be diagnosed and surgically intervened in time, it is easy to lead to ischemia, necrosis and perforation of intestinal segments, and the mortality rate is as high as 15%-40%. The precise judgment of the degree of torsion and tissue damage by surgical operation directly determines the treatment effect of the patient. At present, virtual surgery simulation technology has become the core means of surgical training, especially in the surgical training of small intestine, a flexible organ, which needs to restore the visual reality of macroscopic torsion deformation and the tactile feedback of microscopic damage at the same time.

[0003] The existing surgical simulation system regards the tissue as a uniform continuous medium, and uses a single hyperelastic constitutive model to simulate the overall deformation, which fails to fully consider the layered anatomical structures of small intestinal mucosa, muscle layer and serosa, leading to distortion of the visual performance and biomechanical response of macroscopic torsion deformation, and almost unable to transmit the tactile differences caused by microscopic structural damage (such as collagen fiber fracture), so that the trainees cannot establish a neural mapping of damage degree and tactile feedback through virtual operation, greatly weakening the training effect. SUMMARY

[0004] The present application provides a multi-scale intestinal torsion simulation method and system based on a virtual body envelope, which realizes the synchronous and precise simulation of visual reality of macroscopic deformation and tactile feedback of microscopic damage in small intestine torsion simulation through multi-scale coupling of virtual body envelope and discrete fiber bundle.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows:

[0006] The present application provides a multi-scale intestinal torsion simulation method based on a virtual body envelope, comprising:

[0007] constructing three-dimensional models of mucosa layer, muscle layer and serosa layer according to intestinal scanning data, and composing an intestinal geometric model from the three-dimensional models of mucosa layer, muscle layer and serosa layer;

[0008] adding a virtual envelope body wrapping the intestinal geometric model, receiving an input signal corresponding to a surgical operation, applying an external force to the virtual envelope body according to the input signal to obtain deformation characteristics of the virtual envelope body, and substituting the deformation characteristics into the intestinal geometric model to obtain a macroscopic stress field and calculating a reference feedback force of the intestinal geometric model in the macroscopic stress field;

[0009] identifying a stress concentration area of the intestinal geometric model according to the macroscopic stress field, uniformly embedding a discrete fiber bundle model in the stress concentration area, calculating the overall stretch of the fiber bundle model in the macroscopic stress field,

[0010] The fracture probability of the fiber bundle model is calculated using the Weibull distribution function based on the overall tensile amount. The Monte Carlo fracture simulation algorithm is used to determine whether the fiber bundle model has fractured based on the fracture probability, and the damage rate of the fiber bundle model in the stress concentration area is calculated.

[0011] The correction coefficient is determined by calculating the damage rate, and the tactile feedback force is obtained by correcting the reference feedback force using the correction coefficient.

[0012] Furthermore, based on intestinal scan data, three-dimensional models of the mucosa, muscularis propria, and serosa are constructed. These three-dimensional models constitute the intestinal geometric model, specifically including:

[0013] A basic model of the mucosal layer was constructed based on intestinal scan data. The basic model of the mucosal layer was then meshed, and villi microstructures were imported into each grid point of the basic model of the mucosal layer to obtain a three-dimensional model of the mucosal layer.

[0014] An inner circular smooth muscle and an outer longitudinal smooth muscle were added to the surface of the mucosal layer. The mechanical properties of the inner circular smooth muscle and the outer longitudinal smooth muscle were described by an anisotropic material model to obtain a three-dimensional model of the muscle layer.

[0015] An ultrathin shell model is added to the surface of the muscle layer, and the optical properties (transparency and refractive index) of the ultrathin shell model are adjusted to obtain a three-dimensional model of the slurry layer.

[0016] The intestinal geometric model is obtained by superimposing the three-dimensional models of the mucosa, muscle layer and serosa in order from the inside out.

[0017] Furthermore, the deformation characteristics of the virtual envelope are obtained by applying an external force to the virtual envelope based on the input signal, specifically including:

[0018] The final torsion angle and loading rate of the virtual envelope are determined based on the external force. A total torsion is then applied to the virtual envelope based on the final torsion angle and loading rate, expressed by the following formula:

[0019]

[0020] In the formula, Axial coordinates in the intestinal geometry model The angle of torsion at the location; For the axial coordinates of the intestinal geometry model; For time indexing; The final twist angle at the end of the virtual envelope; It is an exponential function; For loading rate; This represents the total length of the intestinal geometric model;

[0021] The deformation characteristics of the virtual envelope are obtained by calculating the position coordinates of each envelope point after the virtual envelope is twisted.

[0022] Furthermore, the deformation characteristics are substituted into the intestinal geometric model to obtain the macroscopic stress field, specifically including:

[0023] A mapping relationship is established between the envelope points of the virtual envelope and the feature points of the intestinal geometric model. The deformation features of the virtual envelope are substituted into the intestinal geometric model to obtain the movement distance of any feature point in the intestinal geometric model. The formula is as follows:

[0024]

[0025]

[0026]

[0027] In the formula, The first in the intestinal geometric model The distance traveled by each feature point It is a smooth decay function; For the first intestinal geometric model The feature point before the virtual envelope twists. The distance between each envelope point is smoothed and attenuated. After the virtual envelope is twisted, the first The position coordinates of the envelope points; The first in the intestinal geometric model The feature point before the virtual envelope twists. The distance between the envelope points; It is an L2 norm; The first in the intestinal geometric model The position coordinates of each feature point; For the virtual envelope before twisting the first The position coordinates of the envelope points; The adjustment parameters are used to control the attenuation width. It is an exponential function;

[0028] A displacement field is constructed by the movement distance of each feature point in the intestinal geometric model. The right Cauchy-Green deformation tensor and deformation gradient tensor of the intestinal geometric model are calculated based on the displacement field, expressed by the following formula:

[0029]

[0030] ,

[0031] In the formula, For the deformation gradient tensor; Unit tensor; The gradient of the displacement field; The determinant of the deformation gradient tensor; This is a function for calculating determinants. For the right Cauchy-Green deformation tensor; The matrix transpose of the deformable gradient tensor; This is the matrix transpose.

[0032] The total strain energy density of the intestinal geometric model is calculated based on the right Cauchy-Green deformation tensor and the deformation gradient tensor. The macroscopic stress field is then obtained by calculating the total strain energy density of the intestinal geometric model, expressed by the following formula:

[0033]

[0034]

[0035] In the formula, Engineering stress for the intestinal geometry model; for right Find the partial derivative; This represents the total strain energy density of the intestinal geometric model; This represents the macroscopic stress field.

[0036] Furthermore, the total strain energy density of the intestinal geometric model is calculated based on the right Cauchy-Green deformation tensor and the deformation gradient tensor, expressed by the following formula:

[0037]

[0038]

[0039]

[0040] In the formula, The first in the intestinal geometric model The strain energy density of the layer; Shear modulus; It is the first invariant of the right Cauchy-Green deformation tensor; Bulk modulus; It is the trace operator; This represents the total strain energy density of the intestinal geometry model. This represents the total number of layers in the intestinal geometry model. The first in the intestinal geometric model Surface characteristic functions of the layer.

[0041] Furthermore, the overall tensile amount of the fiber bundle model within the macroscopic stress field is calculated, specifically including:

[0042] Each fiber bundle model consists of a linearly arranged set of fiber particles, with adjacent fiber particles connected by a massless spring. The coordinates of the fiber particles after stretching the fiber bundle model are obtained by driving the motion of each fiber particle through a macroscopic stress field. The formula is as follows:

[0043]

[0044]

[0045] In the formula, In the fiber bundle model, the first The mass of each fiber particle In the macroscopic stress field The driving force transmitted by each fiber particle It is the elastic force inside the fiber bundle model. The damping coefficient is... For time indexing, For the fiber bundle model, the elastic coefficients are... For the first In the root fiber bundle model, the first The position coordinates of each fiber particle; For the first In the root fiber bundle model, the first The position coordinates of each fiber particle Let be the length of the massless spring between the two fiber particles. It is a unit direction vector, with the direction from point to ;

[0046] The overall stretching of the fiber bundle model is calculated based on the coordinates of the fiber particles after stretching, expressed by the following formula:

[0047]

[0048] In the formula, For the first The overall stretching of the root fiber bundle model; and These are the coordinates of fiber particles at the beginning and end of the stretched fiber bundle model, respectively. For the first The number of fiber particles in the root fiber bundle model; For the first The initial length of the root fiber bundle model.

[0049] Furthermore, the breakage probability of the fiber bundle model is calculated using the Weibull distribution function based on the overall tensile amount, specifically including:

[0050]

[0051] wherein, is the first characteristic parameter set in the Weibull distribution function, is the fracture probability of the fiber bundle model, is the second characteristic parameter set in the Weibull distribution function, is the overall stretch of the fiber bundle model; is the stretch threshold of the fiber bundle model; is the first characteristic parameter set in the Weibull distribution function, is the second characteristic parameter set in the Weibull distribution function.

[0052] Further, the Monte Carlo fracture simulation algorithm is used to determine whether the fiber bundle model is fractured based on the fracture probability, specifically including:

[0053] The fracture probability of the fiber bundle model is compared with the generated random number, and the value range of the random number is 0 to 1; if the fracture probability of the fiber bundle model is greater than the generated random number, it is determined that the fiber bundle model is fractured; otherwise, it is determined that the fiber bundle model is not fractured.

[0054] Further, the damage rate of the fiber bundle model in the stress concentration area is calculated, specifically including:

[0055] The fiber bundle model is sampled, and the time The number of fiber bundle models that have been fractured is calculated to obtain the damage rate of the fiber bundle model, and the expression formula is:

[0056]

[0057] wherein, is the time is the damage rate of the fiber bundle model in the stress concentration area; is the time is the number of fiber bundle models that have been fractured; is the sampling number of the fiber bundle model.

[0058] Further, the reference feedback force of the intestinal geometric model in the macro stress field is calculated, specifically including:

[0059]

[0060] wherein, is the reference feedback force of the intestinal geometric model, is the scaling coefficient of the force feedback device, is the surface area of the surgical instrument in contact with the tissue, is the macro stress field, is the unit normal vector of the contact surface, is the area infinitesimal on the contact surface.

[0061] Further, the correction coefficient is determined by the damage rate calculation, the haptic feedback force is obtained by correcting the reference feedback force by using the correction coefficient, and specifically includes:

[0062]

[0063]

[0064] In the formula, is a correction coefficient, is the damage rate of the fiber bundle model in the stress concentration area at time is the damage rate of the fiber bundle model in the stress concentration area; is a yield zone attenuation parameter 1; is a yield initiation damage rate; is a damage rate corresponding to the peak force; is a yield zone attenuation parameter 2; is a minimum strength coefficient of the failure zone; is a residual strength coefficient at the peak; is a failure attenuation rate; is a residual strength zone initiation damage rate; is a residual strength coefficient; is a haptic feedback force; is a reference feedback force of the intestinal geometric model.

[0065] The second aspect of the present application provides a multi-scale intestinal torsion simulation system based on a virtual body envelope, comprising:

[0066] A model construction unit constructs three-dimensional models of mucosa, muscle layer and serosa layer according to intestinal scan data, and the intestinal geometric model is composed of the three-dimensional models of mucosa, muscle layer and serosa layer;

[0067] A deformation simulation unit adds a virtual envelope body wrapping the intestinal geometric model, receives an input signal corresponding to a surgical operation, applies an external force to the virtual envelope body according to the input signal to obtain deformation characteristics of the virtual envelope body, and substitutes the deformation characteristics into the intestinal geometric model to obtain a macro stress field and calculate a reference feedback force of the intestinal geometric model in the macro stress field;

[0068] A stretching simulation unit identifies a stress concentration area of the intestinal geometric model according to the macro stress field, uniformly embeds discrete fiber bundle models in the stress concentration area, and calculates an overall stretching amount of the fiber bundle models in the macro stress field;

[0069] A damage identification unit calculates a fracture probability of the fiber bundle models by using a Weibull distribution function according to the overall stretching amount, judges whether the fiber bundle models have fractured based on the fracture probability by using a Monte Carlo fracture simulation algorithm, and calculates a damage rate of the fiber bundle models in the stress concentration area;

[0070] The haptic feedback unit determines a correction coefficient through damage rate calculation, corrects the reference feedback force using the correction coefficient to obtain the haptic feedback force.

[0071] The third aspect of the present application provides an electronic terminal, characterized in that comprising a processor and a storage medium; the storage medium is used for storing instructions; the processor is used for operating according to the instructions to execute the steps of the multiscale intestinal torsion simulation method of the first aspect.

[0072] Compared with the prior art, the present application has the following beneficial effects:

[0073] The present application constructs three-dimensional models of the mucosa layer, muscle layer and serosa layer according to intestinal scanning data, and the intestinal geometric model is composed of the three-dimensional models of the mucosa layer, muscle layer and serosa layer; the mechanical properties of the mucosa layer, muscle layer and serosa layer can be independently represented, and the stress and strain distribution of each layer during torsional deformation conforms to the biomechanical law.

[0074] The present application adds a virtual envelope body wrapping the intestinal geometric model, receives an input signal corresponding to a surgical operation, applies an external force to the virtual envelope body according to the input signal to obtain the deformation characteristics of the virtual envelope body; the deformation characteristics are substituted into the intestinal geometric model to obtain a macro stress field, and the reference feedback force of the intestinal geometric model in the macro stress field is calculated; the virtual envelope body greatly reduces the overhead of collision detection and contact force calculation, the mapping process of the deformation characteristics of the envelope body to the intestinal model accurately simulates the physiological scenario of intestinal torsion during the surgical process, and the calculation of the macro stress field retains the biological mechanical authenticity.

[0075] The present application identifies a stress concentration area of the intestinal geometric model according to the macro stress field, and uniformly embeds discrete fiber bundle models in the stress concentration area; the fiber bundle model decouples the micro calculation amount and the macro deformation scale, avoiding invalid calculation power consumption; the damage rate of the fiber bundle model in the stress concentration area is determined according to the fracture probability of the fiber bundle model; the damage rate aggregates the micro fracture events into a macro mechanical state index, can capture the continuous change process of the intestinal tissue during the surgical process, and fills the gap that the existing simulation cannot represent the cumulative damage of the microstructure.

[0076] The present application determines a correction coefficient through damage rate calculation, corrects the reference feedback force using the correction coefficient to obtain the haptic feedback force, so that the force feedback device can accurately and completely transmit the nonlinear mechanical evolution of the tissue, and realizes the synchronous and accurate simulation of the macro deformation visual authenticity and the micro damage haptic feedback in the small intestine torsion simulation. BRIEF DESCRIPTION OF DRAWINGS

[0077] Figure 1 It is the flowchart of the multiscale intestinal torsion simulation method provided by the embodiment 1 of the present application;

[0078] Figure 2 is a virtual envelope body torsion simulation effect diagram provided by the embodiment 1 of the present application;

[0079] Figure 3 is a macroscopic stress field generation flowchart provided by the embodiment 1 of the present application;

[0080] Figure 4 is a haptic feedback force generation flowchart provided by the embodiment 1 of the present application. DETAILED DESCRIPTION

[0081] The present application will be further described below in conjunction with the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application.

[0082] Embodiment 1

[0083] As shown in Figure 1 , the present embodiment provides a multi-scale intestinal torsion simulation method based on a virtual body envelope, comprising:

[0084] constructing three-dimensional models of the mucosa layer, muscle layer and serosa layer according to intestinal scan data, and composing an intestinal geometric model from the three-dimensional models of the mucosa layer, muscle layer and serosa layer, specifically comprising:

[0085] constructing a mucosa layer basic model according to intestinal scan data, meshing the mucosa layer basic model, and importing villus microstructure into each grid point of the mucosa layer basic model to obtain a three-dimensional model of the mucosa layer;

[0086] adding inner circular smooth muscle and outer longitudinal smooth muscle on the surface of the mucosa layer, and obtaining a three-dimensional model of the muscle layer by describing the mechanical properties of the inner circular smooth muscle and the outer longitudinal smooth muscle through an anisotropic material model;

[0087] adding an ultrathin shell model on the surface of the muscle layer, and adjusting the optical properties (transparency and refractive index) of the ultrathin shell model to obtain a three-dimensional model of the serosa layer;

[0088] stacking the three-dimensional models of the mucosa layer, muscle layer and serosa layer in the order from inside to outside to obtain an intestinal geometric model; the present embodiment can independently characterize the mechanical properties of the mucosa layer, muscle layer and serosa layer, and ensure that the stress and strain distribution of each layer during torsion deformation conforms to the laws of biomechanics.

[0089] As shown in Figure 2 and Figure 3 , a virtual envelope body wrapping the intestinal geometric model is added, an input signal corresponding to a surgical operation is received, and deformation characteristics of the virtual envelope body are obtained by applying an external force to the virtual envelope body according to the input signal, specifically comprising:

[0090] Determine the final torsion angle and loading rate of the virtual envelope body based on external force, and apply overall torsion to the virtual envelope body according to the final torsion angle and the loading rate, and the expression formula is:

[0091]

[0092] In the formula, is the torsion angle at the axial coordinate of the intestinal geometric model ; is the axial coordinate of the intestinal geometric model; is the time index; is the final torsion angle of the end of the virtual envelope body; is the exponential function; is the loading rate; is the total length of the intestinal geometric model;

[0093] Calculate the position coordinates of each envelope point after the virtual envelope body is twisted to obtain the deformation characteristics of the virtual envelope body.

[0094] Substitute the deformation characteristics into the intestinal geometric model to obtain the macroscopic stress field, which specifically includes:

[0095] Establish a mapping relationship between the envelope points of the virtual envelope body and the feature points of the intestinal geometric model, substitute the deformation characteristics of the virtual envelope body into the intestinal geometric model to obtain the movement distance of any feature point of the intestinal geometric model, and the expression formula is:

[0096]

[0097]

[0098]

[0099] In the formula, is the movement distance of the th feature point in the intestinal geometric model, is the smooth attenuation function; is the smooth attenuation processing of the distance from the th feature point in the intestinal geometric model to the th envelope point before the virtual envelope body is twisted; is the position coordinate of the th envelope point after the virtual envelope body is twisted; is the distance from the th feature point in the intestinal geometric model to the th envelope point before the virtual envelope body is twisted; is the L2 norm; is the position coordinate of the th feature point in the intestinal geometric model; For the virtual envelope before twisting the first The position coordinates of the envelope points; The adjustment parameters are used to control the attenuation width. It is an exponential function;

[0100] This embodiment greatly reduces the overhead of collision detection and contact force calculation by introducing a virtual envelope. The mapping process of the deformation characteristics of the envelope to the intestinal model accurately simulates the physiological scenario of intestinal torsion during surgery, so that the calculation of macroscopic stress field retains biomechanical authenticity.

[0101] A displacement field is constructed by the movement distance of each feature point in the intestinal geometric model. The right Cauchy-Green deformation tensor and deformation gradient tensor of the intestinal geometric model are then calculated based on this displacement field, expressed by the following formula:

[0102]

[0103] ,

[0104] In the formula, For the deformation gradient tensor; Unit tensor; The gradient of the displacement field; The determinant of the deformation gradient tensor; This is a function for calculating determinants. For the right Cauchy-Green deformation tensor; The matrix transpose of the deformable gradient tensor; This is the matrix transpose.

[0105] The total strain energy density of the intestinal geometric model is calculated based on the right Cauchy-Green deformation tensor and the deformation gradient tensor, expressed by the following formula:

[0106]

[0107]

[0108]

[0109] In the formula, The first in the intestinal geometric model The strain energy density of the layer; Shear modulus; It is the first invariant of the right Cauchy-Green deformation tensor; Bulk modulus; It is the trace operator; This represents the total strain energy density of the intestinal geometry model. This represents the total number of layers in the intestinal geometry model. is the macroscopic stress field of the intestinal geometric model; is the surface characteristic function of the layer;

[0110] The macroscopic stress field is obtained by the total strain energy density calculation of the intestinal geometric model, and the expression formula is:

[0111]

[0112]

[0113] In the formula, is the engineering stress of the intestinal geometric model; is the is the partial derivative; is the total strain energy density of the intestinal geometric model; is the macroscopic stress field. The reference feedback force of the intestinal geometric model in the macroscopic stress field is calculated, which specifically includes:

[0114]

[0115]

[0116] In the formula, is the reference feedback force of the intestinal geometric model, is the scaling factor of the force feedback device, is the surface area of the surgical instrument in contact with the tissue, is the macroscopic stress field, is the unit normal vector of the contact surface, is the area microelement on the contact surface.

[0117] The stress concentration area of the intestinal geometric model is identified according to the macroscopic stress field, and the expression formula is:

[0118]

[0119] In the formula, indicates the stress concentration area; is the tissue characteristics of the intestinal geometric model; is the critical stress threshold set according to the tissue strength;

[0120] The discrete fiber bundle model is uniformly embedded in the stress concentration area; the overall stretch of the fiber bundle model in the macroscopic stress field is calculated, which specifically includes:

[0121] Each fiber bundle model is composed of a set of linearly arranged fiber particles, and the adjacent two fiber particles are connected by a massless spring. The fiber particle coordinates after stretching of the fiber bundle model are obtained by driving the movement of each fiber particle by the macroscopic stress field, and the expression formula is: ​

[0122]

[0123]

[0124] In the formula, In the fiber bundle model, the first The mass of each fiber particle In the macroscopic stress field The driving force transmitted by each fiber particle It is the internal elastic force of the fiber bundle model. The damping coefficient is... For time indexing, For the fiber bundle model, (The elastic coefficients are...) For the first In the root fiber bundle model, the first The position coordinates of each fiber particle; For the first In the root fiber bundle model, the first The position coordinates of each fiber particle Let be the length of the massless spring between the two fiber particles. It is a unit direction vector, with the direction from point to ;

[0125] The overall stretching of the fiber bundle model is calculated based on the coordinates of the fiber particles after stretching, expressed by the following formula:

[0126]

[0127] In the formula, For the first The overall stretching of the root fiber bundle model; and These are the coordinates of fiber particles at the beginning and end of the stretched fiber bundle model, respectively. For the first The number of fiber particles in the root fiber bundle model; For the first The initial length of the root fiber bundle model.

[0128] The breakage probability of the fiber bundle model is calculated using the Weibull distribution function based on the overall tensile amount, specifically including:

[0129]

[0130] In the formula, For the first Fracture probability of root fiber bundle model For the first The overall stretching of the root fiber bundle model; is a tensile threshold of the fiber bundle model; is a first characteristic parameter set in the Weibull distribution function, is a second characteristic parameter set in the Weibull distribution function.

[0131] The Monte Carlo fracture simulation algorithm is adopted to determine whether the fiber bundle model is fractured based on a fracture probability, and specifically includes:

[0132] The fracture probability of the fiber bundle model is compared with a generated random number, and the random number has a value range of 0 to 1; if the fracture probability of the fiber bundle model is greater than the generated random number, it is determined that the fiber bundle model is fractured; otherwise, it is determined that the fiber bundle model is not fractured.

[0133] The damage rate of the fiber bundle model in the stress concentration area is calculated, and specifically includes:

[0134] The fiber bundle model is sampled, and the time The number of fractured fiber bundle models is calculated to obtain the damage rate of the fiber bundle model, and the expression formula is:

[0135]

[0136] In the formula, is the damage rate of the fiber bundle model in the stress concentration area at time is the time is the number of fractured fiber bundle models in the sampling sample set at time is the sampling number of the fiber bundle model.

[0137] The fiber bundle model in the embodiment decouples the micro-computing amount and the macro-deformation scale, avoids invalid computing power consumption; the damage rate aggregates the micro-fracture event into a macro-mechanical state index, can capture the continuous change process of the intestinal tissue in the operation process, and fills the gap that the existing simulation cannot represent the cumulative damage of the microstructure.

[0138] As shown in the formula, the correction coefficient is determined by the damage rate calculation, the reference feedback force is corrected by using the correction coefficient to obtain the tactile feedback force, and specifically includes: Figure 4

[0139]

[0140]

[0141] In the formula, is the correction coefficient, is the damage rate of the fiber bundle model in the stress concentration area at time ​​​is a yield zone decay parameter 1; is a yield onset damage rate; is a peak force corresponding damage rate; is a yield zone decay parameter 2; is a failure zone minimum strength coefficient; is a peak residual strength coefficient; is a failure decay rate; is a residual strength zone onset damage rate; is a residual strength coefficient; is a haptic feedback force; is a baseline feedback force of the intestinal geometric model.

[0142] The embodiment corrects the baseline feedback force by the damage rate, and the system can deliver the whole cycle mechanical evolution of the tissue from the intact state to the yield, peak, failure and residual strength through high-fidelity simulation, so that the doctor can judge the critical state of tissue damage by hand feeling, and the risk prediction ability in training is greatly improved.

[0143] Embodiment 2

[0144] The embodiment provides a multi-scale intestinal torsion simulation system based on a virtual body envelope, which is used for the multi-scale intestinal torsion simulation method in embodiment 1, and comprises:

[0145] A model construction unit constructs three-dimensional models of a mucosa layer, a muscle layer and a serosa layer according to intestinal scanning data, and composes an intestinal geometric model from the three-dimensional models of the mucosa layer, the muscle layer and the serosa layer;

[0146] A deformation simulation unit adds a virtual envelope body wrapping the intestinal geometric model, receives an input signal corresponding to a surgical operation, applies external force to the virtual envelope body according to the input signal to obtain deformation characteristics of the virtual envelope body, and substitutes the deformation characteristics into the intestinal geometric model to obtain a macro stress field and calculate a baseline feedback force of the intestinal geometric model in the macro stress field;

[0147] A stretching simulation unit identifies a stress concentration area of the intestinal geometric model according to the macro stress field, uniformly embeds discrete fiber bundle models in the stress concentration area, and calculates an overall stretching amount of the fiber bundle models in the macro stress field;

[0148] A damage identification unit calculates a fiber bundle model fracture probability by using a Weibull distribution function according to the overall stretching amount, judges whether the fiber bundle model is fractured based on the fracture probability by using a Monte Carlo fracture simulation algorithm, and calculates a damage rate of the fiber bundle models in the stress concentration area;

[0149] A haptic feedback unit determines a correction coefficient by damage rate calculation, corrects the baseline feedback force by using the correction coefficient to obtain a haptic feedback force.

[0150] Embodiment 3

[0151] The embodiment provides an electronic terminal, characterized by comprising a processor and a storage medium; the storage medium is used for storing instructions; the processor is used for operating according to the instructions to perform steps of the multi-scale intestinal torsion simulation method in embodiment 1.

[0152] Those skilled in the art will understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0153] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flowchart

[0154] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flowchart

[0155] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a process for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flowchart

[0156] The above merely describes the preferred embodiments of the present application, and it should be pointed out that, for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. A multi-scale intestinal torsion simulation method based on virtual volume envelope, characterized in that, include: A three-dimensional model of the mucosa, muscularis propria, and serosa is constructed based on intestinal scanning data. The three-dimensional model of the mucosa, muscularis propria, and serosa constitutes the intestinal geometric model. A virtual envelope is added to enclose the intestinal geometry model, and input signals corresponding to surgical operations are received. External forces are applied to the virtual envelope based on the input signals to obtain the deformation characteristics of the virtual envelope. The deformation characteristics are substituted into the intestinal geometric model to obtain the macroscopic stress field, and the reference feedback force of the intestinal geometric model within the macroscopic stress field is calculated. Based on the macroscopic stress field, stress concentration regions of the intestinal geometric model are identified, and discrete fiber bundle models are uniformly embedded within the stress concentration regions; the overall stretching of the fiber bundle models within the macroscopic stress field is calculated. The fracture probability of the fiber bundle model is calculated using the Weibull distribution function based on the overall tensile amount. The Monte Carlo fracture simulation algorithm is used to determine whether the fiber bundle model has fractured based on the fracture probability, and the damage rate of the fiber bundle model in the stress concentration area is calculated. The correction coefficient is determined by calculating the damage rate, and the tactile feedback force is obtained by correcting the reference feedback force using the correction coefficient.

2. The multi-scale intestinal torsion simulation method according to claim 1, characterized in that, A three-dimensional model of the mucosa, muscularis propria, and serosa is constructed based on intestinal scan data. This three-dimensional model constitutes the intestinal geometric model, which specifically includes: A basic model of the mucosal layer was constructed based on intestinal scan data. The basic model of the mucosal layer was then meshed, and villi microstructures were imported into each grid point of the basic model of the mucosal layer to obtain a three-dimensional model of the mucosal layer. An inner circular smooth muscle and an outer longitudinal smooth muscle were added to the surface of the mucosal layer. The mechanical properties of the inner circular smooth muscle and the outer longitudinal smooth muscle were described by an anisotropic material model to obtain a three-dimensional model of the muscle layer. An ultrathin shell model is added to the surface of the muscle layer, and the optical properties of the ultrathin shell model are adjusted to obtain a three-dimensional model of the slurry layer. The intestinal geometric model is obtained by superimposing the three-dimensional models of the mucosa, muscle layer and serosa in order from the inside out.

3. The multi-scale intestinal torsion simulation method according to claim 1, characterized in that, The deformation characteristics of the virtual envelope are obtained by applying an external force to the virtual envelope based on the input signal, specifically including: The final torsion angle and loading rate of the virtual envelope are determined based on the external force. A total torsion is then applied to the virtual envelope based on the final torsion angle and loading rate, expressed by the following formula: ； In the formula, Axial coordinates in the intestinal geometry model The angle of torsion at the location; For the axial coordinates of the intestinal geometry model; For time indexing; The final twist angle at the end of the virtual envelope; It is an exponential function; For loading rate; This represents the total length of the intestinal geometric model; The deformation characteristics of the virtual envelope are obtained by calculating the position coordinates of each envelope point after the virtual envelope is twisted.

4. The multi-scale intestinal torsion simulation method according to claim 3, characterized in that, The macroscopic stress field is obtained by substituting deformation characteristics into the intestinal geometric model, specifically including: A mapping relationship is established between the envelope points of the virtual envelope and the feature points of the intestinal geometric model. The deformation features of the virtual envelope are substituted into the intestinal geometric model to obtain the movement distance of any feature point in the intestinal geometric model. The formula is as follows: ； ； ； In the formula, The first in the intestinal geometric model The distance traveled by each feature point It is a smooth decay function; For the first intestinal geometric model The feature point before the virtual envelope twists. The distance between each envelope point is smoothed and attenuated. After the virtual envelope is twisted, the first The position coordinates of the envelope points; The first in the intestinal geometric model The feature point before the virtual envelope twists. The distance between the envelope points; It is an L2 norm; The first in the intestinal geometric model The position coordinates of each feature point; For the virtual envelope before twisting the first The position coordinates of the envelope points; The adjustment parameters are used to control the attenuation width. It is an exponential function; A displacement field is constructed by the movement distance of each feature point in the intestinal geometric model. The right Cauchy-Green deformation tensor and deformation gradient tensor of the intestinal geometric model are calculated based on the displacement field, expressed by the following formula: ； ， ； In the formula, For the deformation gradient tensor; Unit tensor; The gradient of the displacement field; The determinant of the deformation gradient tensor; This is a function for calculating determinants. For the right Cauchy-Green deformation tensor; The matrix transpose of the deformable gradient tensor; This is the matrix transpose. The total strain energy density of the intestinal geometric model is calculated based on the right Cauchy-Green deformation tensor and the deformation gradient tensor. The macroscopic stress field is then obtained by calculating the total strain energy density of the intestinal geometric model, expressed by the following formula: ； ； In the formula, Engineering stress for the intestinal geometry model; for right Find the partial derivative; This represents the total strain energy density of the intestinal geometric model; This represents the macroscopic stress field.

5. The multi-scale intestinal torsion simulation method according to claim 4, characterized in that, The total strain energy density of the intestinal geometric model is calculated based on the right Cauchy-Green deformation tensor and the deformation gradient tensor, expressed by the following formula: ； ； ； In the formula, The first in the intestinal geometric model The strain energy density of the layer; Shear modulus; It is the first invariant of the right Cauchy-Green deformation tensor; Bulk modulus; It is the trace operator; This represents the total strain energy density of the intestinal geometry model. This represents the total number of layers in the intestinal geometry model. The first in the intestinal geometric model Surface characteristic functions of the layer.

6. The multi-scale intestinal torsion simulation method according to claim 1, characterized in that, The calculation of the overall tensile strength of the fiber bundle model within the macroscopic stress field includes: Each fiber bundle model consists of a linearly arranged set of fiber particles, with adjacent fiber particles connected by a massless spring. The coordinates of the fiber particles after stretching the fiber bundle model are obtained by driving the motion of each fiber particle through a macroscopic stress field. The formula is as follows: ； ； In the formula, In the fiber bundle model, the first The mass of each fiber particle In the macroscopic stress field The driving force transmitted by each fiber particle It is the elastic force inside the fiber bundle model. The damping coefficient is... For time indexing, For the fiber bundle model, the elastic coefficients are... For the first In the root fiber bundle model, the first The position coordinates of each fiber particle; For the first In the root fiber bundle model, the first The position coordinates of each fiber particle Let be the length of the massless spring between the two fiber particles. It is a unit direction vector, with the direction from point to ; The overall stretching of the fiber bundle model is calculated based on the coordinates of the fiber particles after stretching, expressed by the following formula: ； In the formula, For the first The overall stretching of the root fiber bundle model; and These are the coordinates of fiber particles at the beginning and end of the stretched fiber bundle model, respectively. For the first The number of fiber particles in the root fiber bundle model; For the first The initial length of the root fiber bundle model.

7. The multi-scale intestinal torsion simulation method according to claim 6, characterized in that, The breakage probability of the fiber bundle model is calculated using the Weibull distribution function based on the overall tensile amount, specifically including: ； In the formula, For the first Fracture probability of root fiber bundle model For the first The overall stretching of the root fiber bundle model; The stretching threshold for the fiber bundle model; This is the first characteristic parameter defined in the Weibull distribution function. This is the second characteristic parameter set in the Weibull distribution function.

8. The multi-scale intestinal torsion simulation method according to claim 1, characterized in that, The correction coefficient is determined by calculating the damage rate, and the tactile feedback force is obtained by correcting the baseline feedback force using the correction coefficient. Specifically, this includes: ； ； In the formula, For correction factor, In time Damage rate of fiber bundle model within stress concentration region; The attenuation parameter for the yield zone is 1; The initial damage rate at yield; This represents the damage rate corresponding to the peak force. The attenuation parameter for the yield zone is 2; This represents the minimum strength coefficient in the failure zone. The residual strength coefficient at the peak value; This refers to the failure decay rate; The initial damage rate in the residual strength zone; The residual strength coefficient; For tactile feedback force; This serves as the baseline feedback force for the intestinal geometric model.

9. A multi-scale intestinal torsion simulation system based on virtual volume envelope, characterized in that, include: The model building unit constructs a three-dimensional model of the mucosa, muscularis propria, and serosa based on intestinal scanning data. The three-dimensional models of the mucosa, muscularis propria, and serosa together form the intestinal geometric model. The deformation simulation unit adds a virtual envelope that surrounds the intestinal geometric model, receives input signals corresponding to surgical operations, applies external forces to the virtual envelope based on the input signals to obtain the deformation characteristics of the virtual envelope, substitutes the deformation characteristics into the intestinal geometric model to obtain the macroscopic stress field, and calculates the reference feedback force of the intestinal geometric model within the macroscopic stress field. The stretching simulation unit identifies stress concentration regions of the intestinal geometric model based on the macroscopic stress field, uniformly embeds discrete fiber bundle models within the stress concentration regions, and calculates the overall stretching of the fiber bundle models within the macroscopic stress field. The damage identification unit calculates the fracture probability of the fiber bundle model based on the overall tensile amount using the Weibull distribution function, uses the Monte Carlo fracture simulation algorithm to determine whether the fiber bundle model has fractured based on the fracture probability, and calculates the damage rate of the fiber bundle model in the stress concentration area. The tactile feedback unit determines the correction coefficient by calculating the damage rate, and uses the correction coefficient to correct the reference feedback force to obtain the tactile feedback force.

10. An electronic terminal, characterized in that, It includes a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the multi-scale intestinal torsion simulation method according to any one of claims 1 to 8.

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