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Sound speed imaging is one modal of ultrasound computed tomography (USCT) which is helpful for early breast disease diagnosis. One of the most critical processes of sound speed reconstruction is time-of-flight picking. As each of the traditional time-of-flight picking methods has shortcomings for real data, in this study, a practical priorinformation-based combination (PIBC) solution for picking the difference of time-of-flight between the reference data and the object data (DTOF) is proposed to enhance the reconstruction accuracy and uniformity. By using DTOF, some system bias will be effectively alleviated. Firstly, by analyzing the signal-amplitude, the "penetrating-through-the-object" and the "bypassing-the-object" signals are distinguished. Then for the "penetrating-throughthe-object" signals, based on the 'majority rule,' the consistency of DTOF picked by different methods are calculated as a basis to combine the advantages of different picking methods; for the "bypassing-the-object" signals, the DTOF closest to zero is chosen. Finally, the DTOFs are post-processed to suppress the noise by a median filter and to fix the deficiency of the system by an interpolation operator. The new solution is verified by in vitro breast phantom experiment conducted on the home-made USCT system "Lucid." The proposed PIBC solution can quantitatively decrease Root Mean Squared Error (RMSE) and Mean Squared Error (MSE) of DTOF picking and enhance the image quality of reconstructed sound speed images with higher accuracy and uniformity. This work is significant for ray-based sound speed reconstruction and can provide a fine initial solution for high-resolution wave-based reconstruction.

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<abstract> <p>Ultrasound computed tomography (USCT) has been developed for breast tumor screening. The sound-speed modal of USCT can provide quantitative sound-speed values to help tumor diagnosis. Time-of-flight (TOF) is the critical input in sound-speed reconstruction. However, we found that the missing data problem in the detected TOF causes artifacts on the reconstructed sound-speed images, which may affect the tumor identification. In this study, to address the missing TOF data problem, we first adopted the singular value threshold (SVT) algorithm to complete the TOF matrix. The threshold value in SVT is difficult to determine, so we proposed a selection strategy, that is, to enumerate the threshold values as the multiples of the maximum singular value of the incomplete matrix and then evaluate the image quality to select the proper threshold value. In the numerical breast phantom experiment, the artifacts are eliminated, and the accuracy is higher than the accuracy of the compared methods. In the in vivo experiment, we reconstructed the sound-speed image of the breast of a volunteer with invasive breast cancer, and the SVT algorithm improved the image sharpness. The completion of DTOF based on SVT gives better accuracy than the compared methods, but too large a threshold value decreases the accuracy. In the future, the selection method of the threshold value needs further research, and more USCT cases should be included in the experiments.</p> </abstract>