The invention relates to a
muscle-bone ultrasonic multi-parameter imaging method based on a
physical information neural network. The method comprises the following steps: S1, obtaining an observation
signal; s2, constructing a generator and a
discriminator; s3, generating an analog ultrasonic
signal generated at the position of the ultrasonic
transducer; s4, inputting the simulated ultrasonic
signal and the observation signal into a
discriminator together, and training the
discriminator based on a generative adversarial task objective function; and S5, updating the current sound velocity distribution and the current
medium density distribution of the generator, generating the simulated ultrasonic signal again, if the difference between the simulated ultrasonic signal and the observation signal is smaller than a threshold value and does not reach the
training period, returning to S3, and otherwise, taking the current sound velocity distribution and the current
medium density distribution at the moment as a multi-parameter imaging result of the
muscle bone tissue. Compared with the prior art, the method has the advantages that the physical consistency of imaging results is improved, and then multi-parameter imaging of sound velocity and density of
muscle bone tissue is accurately achieved.