Rapid rotational magneto-acousto-electrical tomography with filtered back-projection algorithm based on plane waves

Iterative Reconstruction Algorithms in Magneto-Acousto-Electrical Computed Tomography (MAE-CT) for Image Quality Improvement

Magneto-acousto-electrical computed tomography (MAE-CT) is a recently developed rotational magneto-acousto-electrical tomography (MAET) method, which can map the conductivity parameter of tissues with high spatial resolution. Since the imaging mode of MAE-CT is similar to that of CT, the reconstruction algorithms for CT are possible to be adopted for MAE-CT. Previous studies have demonstrated that the filtered back-projection (FBP) algorithm, which is one of the most common CT reconstruction algorithms, can be used for MAE-CT reconstruction. However, FBP has some inherent shortcomings of being sensitive to noise and non-uniform distribution of views. In this study, we introduced iterative reconstruction (IR) method in MAE-CT reconstruction and compared its performance with that of the FBP. The numerical simulation, the phantom, and in vitro experiments were performed, and several IR algorithms (ART, SART, SIRT) were used for reconstruction. The results show that the images reconstructed by the FBP and IR are similar when the data is noise-free in the simulation. As the noise level increases, the images reconstructed by SART and SIRT are more robust to the noise than FBP. In the phantom experiment, noise and some stripe artifacts caused by the FBP are removed by SART and SIRT algorithms. In conclusion, the IR method used in CT is applicable in MAE-CT, and it performs better than FBP, which indicates that the state-of-the-art achievements in the CT algorithm can also be adopted for the MAE-CT reconstruction in the future.

Magneto-acoustic-electrical tomography combining maximum length sequence-coded excitation and liquid metal image contrast agent

Magneto-acoustic-electrical tomography (MAET) combines the advantages of ultrasound and electrical impedance functional tomography methods and has important research value in the early diagnosis of tumors and biocurrent monitoring. In this study, we propose a MAET method combining liquid metal image enhancement and maximum length sequence (MLS)-coded excitation to improve the signal-to-noise ratio (SNR) of MAET. The results indicate that liquid metal can achieve image enhancement of tissue MAET. When 7-, 15-, 31- and 63-bit MLS-coded excitations were applied to the samples, the SNR was improved by 28, 34, 40 and 45 dB, respectively. For a similar SNR improvement, the total used time under 31-bit MLS-coded excitation can be shortened to 23% under single-pulse excitation. The experimental results prove the feasibility of applying the MLS code to rotational MAET and reveal the significance of liquid metal as an image intensifier to improve the quality of MAET.