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High frame rate adaptive imaging using coherence factor weighting and the MVDR method

Adaptive imaging has been extensively studied. Although some success has been demonstrated, these approaches generally are not suitable for high frame rate (HFR) imaging where broad transmit beams are required. In this study, we propose an effective adaptive imaging method suitable for HFR imaging based on coherence factor (CF) weighting and the minimum variance distortionless response (MVDR) method. The CF is a focusing quality index estimated from receive-channel data. It is the ratio between the energy of the coherent sum to the total incoherent energy. This method is an adaptive weighting technique in which the amplitude of each image pixel is weighted by the corresponding CF such that the unwanted side lobes are reduced. Direct implementation of the CF weighting in HFR imaging does not provide satisfactory results because broad transmit beams required for HFR imaging affect accuracy of CF calculations. In this study, we overcome this problem by applying the MVDR method to the delayed channel data. Specifically, the MVDR method is used for angle of arrival estimation. The beam sum data are then weighted by the estimated CF. A synthetic transmit aperture method is used for HFR imaging. Only 8 firings are required to form an image. Both simulations and clinical breast imaging data are used. In the experiments, clinical breast data are acquired using a programmable array system. With the proposed method, the average contrast enhancement is 4.59 dB and the average CNR enhancement is 20.19%. The results demonstrated that the proposed method can improve image quality. Even for HFR imaging with only 8 firings per image, effective contrast enhancement and better lesion boundary can be achieved. Efficacy of the proposed method is clearly demonstrated.