Ultrafast ultrasound imaging with a limited number of emissions based on Cantor selection pattern

In coherent plane-wave compounding (CPWC), frame rate improvement is challenging. As the number of emissions reduces, the frame rate will increase. However, this improvement is at the cost of quality deterioration of the reconstructed image. To deal with the compromise between image quality and frame rate, we propose a novel method based on the Cantor selection pattern in this paper. In the proposed method, a set that includes a limited number of emissions (Cantor set) is sparsely selected within a specific angular interval. At this stage, the number of selected emissions is considerably reduced, and consequently, it can be promising in practical applications. Also, to prevent image quality degradation, we propose to use the multiple signal classification (MUSIC) algorithm's output as a weighting factor. In the MUSIC algorithm, which is suitable for processing the sparse dataset, the second-order data associated with a larger number of uniformly selected emissions (called Co-emission) is constructed from the Cantor set, leading to quality improvement of the resulting image. Evaluations demonstrate that the proposed method improves the quality of the image in comparison with the delay-and-sum (DAS) method in which the emissions included in Cantor and Co-emission sets are used. In particular, for the experimental contrast phantom, and by using eight emissions, the proposed method leads to 50% and 45.45% resolution improvement compared to DAS corresponding to using the emission numbers included in Cantor set (i.e., 8) and Co-emission set (i.e., 27), respectively, while keeping the speckle preservation metric comparable to the other mentioned cases. Also, by using the proposed method, 46.49% and 0.63% contrast ratio improvement is achieved compared to DAS corresponding to using the emissions included in Cantor and Co-emission sets, respectively, for in-vivo dataset.