Tomographic density imaging using modified DF–DBIM approach
10.1007/s13534-019-00129-5
- Author:
Tran Quang HUY
1
;
Nguyen Thi CUC
;
Van Dung NGUYEN
;
Ton That LONG
;
Tran Duc TAN
Author Information
1. Faculty of Physics, Hanoi Pedagogical University 2, Nguyen Van Linh Street, Xuan Hoa Ward, Phuc Yen Town, Vinh Phuc Province, Vietnam.
- Publication Type:Original Article
- Keywords:
Ultrasound tomography;
Distorted Born iterative method (DBIM);
Density imaging;
Inverse scattering;
Duple frequency (DF)
- MeSH:
Image Processing, Computer-Assisted;
Methods;
Transducers;
Ultrasonics;
Ultrasonography
- From:
Biomedical Engineering Letters
2019;9(4):449-465
- CountryRepublic of Korea
- Language:English
-
Abstract:
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.
