Reconstructions of shear modulus, Poisson's ratio, and density using approximate mean normal stress lambda epsilon alpha alpha as unknown.

As a differential diagnosis technique for living soft tissues, we are developing ultrasonic-strain-measurement-based shear modulus reconstruction methods. Previously, we reported three-dimensional (3-D) and 2-D reconstruction methods utilizing a typical Poisson's ratio very close to 0.5 (nearly-incompressible). However, because a decrease in the accuracy of the reconstructed value was confirmed to be due to the difference between the original value and the set value, we proposed 3-D and 2-D methods of reconstructing Poisson's ratio as well. Furthermore, we proposed methods of reconstructing density and dealing with dynamic deformation. However, due to tissue incompressibility, the reconstructions of shear modulus, Poisson's ratio, and density became unstable. In this report, to obtain stable, unique reconstructions, we describe a new reconstruction method using mean normal stress approximated by the product of one of Lame's constants X and volume strain epsilon alpha alpha as an unknown. Regularization is simultaneously applied to the respective distributions to decrease the instability of the reconstructions due to measurement errors of the deformation. This method also enables stable, unique reconstructions of shear modulus and density under the condition that the mean normal stress remains unknown. We also verify the effectiveness of this method through 3-D simulations, while showing erroneous artifacts occurring when 2-D and 1-D reconstructions are performed.