Multistatic Data Sets Research Articles

The impact of loss function domain for optimizing ultrasound imaging

The conventional view of ultrasound pulse-echo data—focused sound sent in a direction and bounced back towards the transducer—does not capture the rich information available. REFoCUS beamforming abandons this limitation, combining the ideas of spatially coded excitation and synthetic aperture imaging. Each transmission is an encoding of elements with various weights and time delays, and the multistatic data set (all transmit/receive element pairs) is estimated from the received data. We can, therefore, apply a single focusing operation across different choices of transmit pulse sequencing and ask questions about how to best optimize that sequence.The multistatic data set is a useful mathematical model since it is tied to individual array elements. Several works have used such raw echo data in optimization problems, for instance training neural networks to improve data quality from limited transmissions. However, we have found that the image formation process (e.g., focusing, beamforming) can change the appearance of errors in the data set. Even small errors in the raw data can result in significant image artifacts due to the inherent ill-conditioning of the beamforming operation. We demonstrate improvements in optimization using loss functions defined in the image domain compared to the raw multistatic data.

Extending Retrospective Encoding for Robust Recovery of the Multistatic Data Set.

Robust recovery of multistatic synthetic aperture data from conventional ultrasound sequences can enable complete transmit-and-receive focusing at all points in the field of view without the drawbacks of virtual-source synthetic aperture and further enables more advanced imaging applications, such as backscatter coherence, sound speed estimation, and phase aberration correction. Recovery of the multistatic data set has previously been demonstrated on a steered transmit sequence for phased arrays using an adjoint-based method. We introduce two methods to improve the accuracy of the multistatic data set. We first modify the original technique used for steered transmit sequences by applying a ramp filter to compensate for the nonuniform frequency scaling introduced by the adjoint-based method. Then, we present a regularized inversion technique that allows additional aperture specification and is intended to work for both steered transmit and walking aperture sequences. The ramp-filtered adjoint and regularized inversion techniques, respectively, improve the correlation of the recovered signal with the ground truth from 0.9404 to 0.9774 and 0.9894 in steered transmit sequences and 0.4610 to 0.4733 and 0.9936 in walking aperture sequences.

Detection of Antipersonnel Mines by Using the Factorization Method on Multistatic Ground-Penetrating Radar Measurements

The factorization method (FM) has been applied to measurement data from a multistatic ground-penetrating radar operating in close proximity to the ground, which was used in a measurement campaign on the Joint Research Centre mine test lane in Ispra, Italy. This paper is targeted toward a future hand-held demining system. The according space limits restrict an independent positioning of transmit and receive antennas. Hence, very small multistatic datasets are obtained, representing a difficult case for the reconstruction with the FM