Novel automatic first-arrival picking method for ultrasound sound-speed tomography

Ultrasound sound-speed tomography (USST) is a promising technique for breast cancer diagnosis that is currently under investigation. Compared with two-dimensional X-ray mammography, it not only provides three-dimensional images but also avoids radiation exposure. However, the image quality of USST is highly dependent on the accuracy of travel time map (TTM). To improve the accuracy, a novel automatic first-arrival picking method is proposed in this study. With this method, Akaike information criterion is used to obtain travel time roughly, then cross-correlation of neighboring traces is employed to correct the obtained travel time. Simulation, phantom, and ex vivo experiments are implemented. The simulation experiments showed that the absolute errors of the proposed method were 52 and 98 ns for simple and complex structure data, respectively. The phantom and ex vivo experiments demonstrated the feasibility of the proposed method. In this study, a novel and robust first-arrival picking method was proposed for USST.