TY - JOUR
T1 - Ultrasound Computed Tomography using physical-informed Neural Network
AU - Liu, Xilun
AU - Almekkawy, Mohamed
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Ultrasound computed tomography (USCT) is an important diagnostic technique for improved imaging in medical area. The reconstruction of tissue properties, such as attenuation, mass density, and speed of sound (SoS), can be used to monitor and analyze the tissue condition. In this paper, an optimized physical-based architecture called physics-informed neural network (PINN) is used to solve the inverse problems of USCT. This neural network leverages the physical information by adding the residuals of a system of Partial Differential Equations (PDE) to the loss function in the learning process. By incorporating all the information including the PDE, initial and boundary conditions, proposed nerual network can learn solutions of the wave equation. The results showed that PINN can extract the SoS value within an acceptable error.
AB - Ultrasound computed tomography (USCT) is an important diagnostic technique for improved imaging in medical area. The reconstruction of tissue properties, such as attenuation, mass density, and speed of sound (SoS), can be used to monitor and analyze the tissue condition. In this paper, an optimized physical-based architecture called physics-informed neural network (PINN) is used to solve the inverse problems of USCT. This neural network leverages the physical information by adding the residuals of a system of Partial Differential Equations (PDE) to the loss function in the learning process. By incorporating all the information including the PDE, initial and boundary conditions, proposed nerual network can learn solutions of the wave equation. The results showed that PINN can extract the SoS value within an acceptable error.
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U2 - 10.1109/IUS52206.2021.9593314
DO - 10.1109/IUS52206.2021.9593314
M3 - Conference article
AN - SCOPUS:85122889811
SN - 1948-5719
JO - IEEE International Ultrasonics Symposium, IUS
JF - IEEE International Ultrasonics Symposium, IUS
T2 - 2021 IEEE International Ultrasonics Symposium, IUS 2021
Y2 - 11 September 2011 through 16 September 2011
ER -