Fast axial and lateral displacement estimation in myocardial elastography based on RF signals with predictions

Myocardial elastography (ME) is a strain imaging technique used to diagnose myocardial diseases. Axial and lateral displacement calculations are pre-conditions of strain image acquisition in ME. W.N. Lee et al. proposed a normalized cross-correlation (NCC) and recorrelation method to obtain both axial and lateral displacements in ME. However, this method is not noise-resistant and of high computational cost. This paper proposes a predicted fast NCC algorithm based on W.N. Lee's method, with the additions of sum-table NCC and a displacement prediction algorithm, to obtain efficient and accurate axial and lateral displacements. Compared to experiments based on the NCC and recorrelation methods, the results indicate that the proposed NCC method is much faster (predicted fast NCC method, 69.75s for a 520×260 image; NCC and recorrelation method, 1092.25s for a 520×260 image) and demonstrates better performance in eliminating decorrelation noise (SNR of the axial and lateral strain using the proposed method, 5.87 and 1.25, respectively; SNR of the axial and lateral strain using the NCC and recorrelation method, 1.48 and 1.09, respectively).