Paridar Roya, Asl Babak Mohammadzadeh
Department of Biomedical Engineering, Tarbiat Modares University, Tehran, Iran.
Department of Biomedical Engineering, Tarbiat Modares University, Tehran, Iran.
Ultrasound Med Biol. 2023 Jul;49(7):1627-1637. doi: 10.1016/j.ultrasmedbio.2023.03.015. Epub 2023 Apr 21.
Coherent plane wave compounding (CPWC) imaging is an efficient technique in high-frame-rate ultrasound imaging. To improve the image quality obtained from the CPWC, the adaptive minimum variance (MV) algorithm can be used. However, the high computational complexity of this algorithm negatively affects the frame rate. In other words, achieving a high frame rate and high-quality features simultaneously remains a challenge in medical ultrasound imaging. The aim of the work described here was to develop an algorithm to tackle this challenge and improve the frame rate while preserving the good quality of the resulting image.
A tensor completion (TC)-based MV algorithm is proposed to simultaneously improve the frame rate and image quality in CPWC. In the proposed method, the MV algorithm is applied to a limited number of pixels in the beamforming grid. Then, the appropriate values are assigned to the remaining unprocessed pixels by using the TC algorithm. The proposed algorithm speeds up the beamforming process, and consequently, improves the frame rate.
The computational complexity of the proposed TC-based MV algorithm is reduced compared with that of the conventional MV algorithm while the good quality of this algorithm is preserved. The results indicate that, in particular, by processing 40% of the beamforming grid using the MV beamformer followed by the TC algorithm, a reconstructed image comparable to that in the case in which the MV algorithm is performed on the full beamforming grid is obtained; the difference between the contrast-to-noise ratio evaluation metric between these two cases is about 0.16 dB for the experimental-resolution phantom. Also, the resulting images obtained from the MV algorithm and the TC-based MV method have the same resolution, indicating that the TC-based MV algorithm can successfully achieve the quality of the MV algorithm with a lower computational complexity.
The TC-based MV algorithm is proposed in CPWC with the goal of improving frame rate and image quality. Qualitative and quantitative results reveal that by use of the proposed algorithm, the quality of the reconstructed image will be comparable to that of the conventional MV algorithm, and the frame rate will be improved.
相干平面波复合（CPWC）成像是一种高效的高帧率超声成像技术。为了提高从CPWC获得的图像质量，可以使用自适应最小方差（MV）算法。然而，该算法的高计算复杂度对帧率产生负面影响。换句话说，在医学超声成像中同时实现高帧率和高质量特征仍然是一个挑战。本文所述工作的目的是开发一种算法来应对这一挑战，并在保持所得图像质量良好的同时提高帧率。
提出一种基于张量补全（TC）的MV算法，以在CPWC中同时提高帧率和图像质量。在所提出的方法中，MV算法应用于波束形成网格中的有限数量像素。然后，通过使用TC算法为其余未处理像素分配适当的值。所提出的算法加快了波束形成过程，从而提高了帧率。
与传统MV算法相比，所提出的基于TC的MV算法的计算复杂度降低，同时该算法的良好质量得以保留。结果表明，特别是通过使用MV波束形成器处理40%的波束形成网格，然后使用TC算法，可以获得与在全波束形成网格上执行MV算法时相当的重建图像；对于实验分辨率体模，这两种情况之间的对比度噪声比评估指标差异约为0.16 dB。此外，从MV算法和基于TC的MV方法获得的所得图像具有相同的分辨率，这表明基于TC的MV算法可以以较低的计算复杂度成功实现MV算法的质量。
在CPWC中提出基于TC的MV算法，目标是提高帧率和图像质量。定性和定量结果表明，通过使用所提出的算法，重建图像的质量将与传统MV算法相当，并且帧率将得到提高。
