서강대학교

초록/요약

In medical ultrasound imaging, a pre-determined sound speed (e.g., 1540m/s) is typically used in receive beamforming. However, the propagating sound speed varies substantially due to the inhomogeneity of soft tissues. This results in a decrease in the quality of the imaging with respect to CNR, SNR, and spatial resolution. To resolve this issue, various sound speed estimation methods (e.g., CF, MASAD) based on focus quality have been proposed. However, these methods are not reliable with respect to the size and position of the region of interest (ROI) since these methods are easily affected by off-axis signals. In this paper, a new sound speed estimation method based on adaptive delay error curve fitting (ADEC) is proposed. In the ADEC method, the optimal sound speed is identified by applying compensated delay curve fitting. Compensated delay curve fitting uses the delay error profile generated by the cross-correlation of the delayed channel data with an assumed sound speed. To evaluate the performance of the proposed method, phantom and in-vivo studies were conducted. The experiment results indicated that the ADEC method is able to estimate the optimal sound speed with minimal impact from either on-axis or off-axis signals in both the phantom and the in vivo experiment conditions. In conclusion, the proposed method is able to robustly improve image quality by identifying the optimal sound speed for various ROIs.