Tomographic density imaging using modified DF–DBIM approach

Ultrasonic computed tomography based on back scattering theory is the most powerful and accurate tool in ultrasound based imaging approaches because it is capable of providing quantitative information about the imaged target and detects very small targets. The duple-frequency distorted Born iterative method (DF–DBIM), which uses density information along with sound contrast for imaging, is a promising approach for imaging targets at the level of biological tissues. With two frequencies f₁ (low) and f₂ (high) through Nf₁ and Nf₂ iterations respectively, this method is used to estimate target density along with sound contrast. The implications of duple-frequency fusion for the image reconstruction quality of density information along with sound contrast based ultrasound tomography have been analyzed in this paper. In this paper, we concentrate on the selection of parameters that is supposed to be the best to improve the reconstruction quality of ultrasound tomography. When there are restraints imposed on simulated scenarios to have control of the computational cost, the iteration number Nf₁ is determined resulting in giving the best performance. The DF–DBIM is only effective if there are a moderate number of iterations, transmitters and receivers. In case that the number of transducers is either too large or too small, a result of reconstruction which is better than that of the single frequency approach is not produced by the implementation of DF–DBIM. A fixed sum N(iter) of Nf₁ and Nf₂ was given, the investigation of simulation results shows that the best value of Nf₁ is [N(iter)/2 − 1]. The error, when applying this way of choosing the parameters, will be normalized with the reduction of 56.11%, compared to use single frequency as used in the conventional DBIM method. The target density along with sound contrast is used to image targets in this paper. It is a fact that low-frequency offers fine convergence, and high-frequency offers fine spatial resolution. Wherefore, this technique can effectively expand DBIM's applicability to the problem of biological tissue reconstruction. Thanks to the usage of empirical data, this work will be further developed prior to its application in reality.

Study of Linear Sampling Method with Partial-view Data in Electromagnetic Inverse Scattering Imaging / 航天医学与医学工程

Objective To study the application of the linear sampling method(LSM) in 2D electromagnetic inverse scattering imaging and to mainly discuss the imaging quality of LSM with partial-view data.Methods Get the norm of solution vector to the equivalent integral equation using numerical calculation in every sampling point at imaging region,and represent the norm with gray to reconstruct the scattering shape.Results Under all incident angles [0,360?] and all observation angles [0,360?],the imaging quality of the far-field pattern of scattering wave was obtained very well.But when reducing the range of the incident angles and observation angles,the imaging quality declined.Particularly,the imaging quality in the case of both incident angles and observation angles being at the same side of the observed object,were much better than both in opposite sides.Furthermore,the profile of the object was imaged more clearly as its position corresponding to the orientation of the incident/observation angle.Conclusion Although the imaging quality will decline with partial-view data in electromagnetic inverse scattering,the effectiveness of imaging with LSM still deserves attention.