Method and apparatus for measuring ultrasonic viscoelasticity, device and medium

An apparatus for measuring ultrasonic viscoelasticity, comprising:

• an equation establishing module, configured to establish an inhomogeneous viscoelastic wave equation, wherein the inhomogeneous viscoelastic wave equation characterizes a relationship between particle vertical vibration velocity and a stream function;
• a neural network construction module, configured to code the inhomogeneous viscoelastic wave equation as a loss function and construct a physics-informed neural network, wherein the physics-informed neural network comprises a spatial-temporal neural network, a spatial neural network and the loss function, the spatial-temporal neural network is configured to predict the stream function, the inhomogeneous viscoelastic wave equation is used to obtain the particle vertical vibration velocity based on the stream function outputted, the spatial neural network is configured to predict shear modulus and viscosity, and the loss function is used to calculate an aggregate loss based on the particle vertical vibration velocity, the shear modulus and the viscosity;
• a vibration velocity determining module, configured to determine multi-frame particle vertical vibration velocity of an object to be measured based on consecutive frames of ultrasonic radio frequency signals of the object to be measured;
• and
• an application module, configured to input the multi-frame particle vertical vibration velocity of the object to be measured as supervisory data into the physics-informed neural network, to obtain a spatial distribution of the shear modulus and a spatial distribution of the viscosity of the object to be measured.

A computer device, comprising:

• a memory,
• a processor, and
• a computer program, stored in the memory and executable on the processor, wherein
• the processor is configured to execute the computer program to implement a method, wherein
• the method comprises:
• establishing an inhomogeneous viscoelastic wave equation, wherein the inhomogeneous viscoelastic wave equation characterizes a relationship between particle vertical vibration velocity and a stream function;
• coding the inhomogeneous viscoelastic wave equation as a loss function, and constructing a physics-informed neural network, wherein the physics-informed neural network comprises a spatial-temporal neural network, a spatial neural network and the loss function, the spatial-temporal neural network is configured to predict the stream function, the inhomogeneous viscoelastic wave equation is used to obtain the particle vertical vibration velocity based on the stream function outputted, the spatial neural network is configured to predict shear modulus and viscosity, and the loss function is used to calculate an aggregate loss based on the particle vertical vibration velocity, the shear modulus and the viscosity;
• determining multi-frame particle vertical vibration velocity of an object to be measured based on consecutive frames of ultrasonic radio frequency signals of the object to be measured;
• and
• inputting the multi-frame particle vertical vibration velocity of the object to be measured as supervisory data into the physics-informed neural network, to obtain a spatial distribution of the shear modulus and a spatial distribution of the viscosity of the object to be measured.