Implementation of Wide-Beam Ultrasound Imaging Based on a Convex Transducer
Shi Xinwang, Feng Lian, Zhou Xiaowei*
(State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing 400016, China)
Abstract：Ultrasound wide-beam imaging is a high frame rate ultrasound imaging method that can better balance several important imaging properties such as image spatial resolution, contrast ratio, and frame rate, which is implemented by putting the transmitting focus point far away from the actual imaging depth when compared to the traditional line-by-line scanning, plane and diverging wave imaging methods. Current studies on ultrasound wide-beam imaging are only based on linear array ultrasound transducers that have a limited imaging field of view and are not suitable for imaging of deep tissues and organs. In this paper, we investigated the wide-beam imaging algorithm based on a convex array ultrasound transducer and evaluated performance of the wide-beam imaging method with convex linear array. With a convex array transducer with 128 arrays, wide-beam imaging was implemented in two environments, a simulation platform and a real experiment scenario. The original channel data were first collected in both scenarios and then a delay and sum method was used to beamform and reconstruct the wide-beam ultrasound images. Quantitative analysis was performed in terms of the image contrast and spatial resolution and compared with the traditional focused line-by-line scanning, the diverging wave imaging methods. Compared with compound diverging wave imaging, the wide-beam imaging had higher image contrast (simulated case: 19.6 dB, increased by 67.1%; experimental case: 19.1 dB, increased by 33.1%), but its performance on resolution was different in the simulated and experimental cases (spatial resolution in the simulated case: 1.11 mm, increased by 18.1%; in the experimental case: 1.48 mm, decreased by 15.4%). Overall, the wide-beam imaging had better performance than compound diverging wave imaging. In comparison with the focused line-by-line scanning, wide beam imaging exhibited more uniform imaging resolution and a higher frame rate. This study implemented the wide-beam ultrasound imaging based on a convex imaging transducer for the first time and validated that the imaging method had more balanced imaging performance than the diverging wave imaging methods and traditional focused method, which offered a better imaging strategy for some relevant clinical applications, especially for the abdominal ultrasound.
史新旺, 冯炼, 周小伟. 基于凸阵列超声换能器的宽波束成像算法研究[J]. 中国生物医学工程学报, 2024, 43(3): 278-285.
Shi Xinwang, Feng Lian, Zhou Xiaowei. Implementation of Wide-Beam Ultrasound Imaging Based on a Convex Transducer. Chinese Journal of Biomedical Engineering, 2024, 43(3): 278-285.
[1] Asl BM, Mahloojifar A. Minimum variance beamforming combined with adaptive coherence weighting applied to medical ultrasound imaging [J]. IEEE Trans Ultrason Ferroelectr Freq Control, 2009, 56(9): 1923-1931. [2] Hansen PM, Hemmsen M, Brandt A, et al. Clinical evaluation of synthetic aperture sequential beamforming ultrasound in patients with liver tumors [J]. Ultrasound Med Biol, 2014, 40(12): 2805-2810. [3] Cikes M, Tong L, Sutherland GR, et al. Ultrafast cardiac ultrasound imaging: technical principles, applications, and clinical benefits [J]. JACC: Cardiovascular Imaging, 2014, 7(8): 812-823. [4] Bae MH, Jeong MK. Bidirectional pixel based focusing in conventional b-mode ultrasound imaging [J]. Electron Lett, 1998, 34(22): 2105-2107. [5] Kim C, Yoon C, Park JH, et al. Evaluation of ultrasound synthetic aperture imaging using bidirectional pixel-based focusing: preliminary phantom and in vivo breast study [J]. IEEE Trans Biomed Eng, 2013, 60(10): 2716-2724. [6] 刘晶, 刘荣, 夏静静, 等. 基于宽波束激励的高帧频超声成像方法研究 [J]. 集成技术, 2016, 5(6): 45-51. [7] 张亚东, 郑驰超, 彭虎. 基于自适应调节过零点系数的远聚焦超声成像算法 [J]. 生物医学工程研究, 2021, 40: 380-388. [8] 徐祥, 汪亚中, 郑驰超, 等. 基于自适应加权算法的远聚焦超声成像 [J]. 生物医学工程研究, 2020, 39(4): 319-329. [9] Perrot V, Polichetti M, Varray F, et al. So you think you can das? a viewpoint on delay-and-sum beamforming [J]. Ultrasonics, 2021, 111(3):106309. [10] Kang J, Go D, Song I, et al. Wide field-of-view ultrafast curved array imaging using diverging waves [J]. IEEE Trans Biomed Eng, 2019, 67(6): 1638-1649. [11] Demi L. Practical guide to ultrasound beam forming: beam pattern and image reconstruction analysis [J]. Applied Sciences, 2018, 8(9): 1544. [12] Montaldo G, Tanter M, Bercoff J, et al. Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography [J]. IEEE Trans Ultrason Ferroelectr Freq Control, 2009, 56(3): 489-506. [13] Wang Y, Zheng C, Peng H. Dynamic coherence factor based on the standard deviation for coherent plane-wave compounding [J]. Comput Biol Med, 2019, 108: 249-262. [14] Camacho J, Parrilla M, Fritsch C. Phase coherence imaging [J]. IEEE Trans Ultrason Ferroelectr Freq Control, 2009, 56(5):958-974. [15] Ranganathan K, Walker WF. Cystic resolution: a performance metric for ultrasound imaging systems [J]. IEEE Trans Ultrason Ferroelectr Freq Control,2007, 54(4):782-792. [16] Zhao W, Feng S, Wang Y, et al. A joint delay-and-sum and Fourier beamforming method for high frame rate ultrasound imaging [J]. CMES-Computer Modeling in Engineering & Sciences, 2020, 123(1):427-440. [17] Guo W, Wang Y, Yu J. Ultrasound harmonic enhanced imaging using eigenspace-based coherence factor [J]. Ultrasonics, 2016, 72: 106-116. [18] Zhao J, Wang Y, Yu J, et al. Short-lag spatial coherence ultrasound imaging with adaptive synthetic transmit aperture focusing [J]. Ultrasonic Imaging, 2017, 39(4): 224-239. [19] Jensen JA. Field: a program for simulating ultrasound systems [J]. Med Biol Eng Comput, 1996, 34(1):351-352. [20] Jensen JA, Svendsen NB. Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers [J]. IEEE Trans on Ultrason Ferroelectr and Freq Control, 1992, 39(2):262-267. [21] Paridar R, Asl BM. Ultrafast plane wave imaging using tensor completion-based minimum variance algorithm [J]. Ultrasound Med Biol, 2023, 49(7): 1627-1637. [22] Tong L, Wang P, Li X, et al. Ultrasound plane-wave compressed sensing reconstruction method using intra-frame and inter-frame joint multi-hypothesis and reference frame multi-hypothesis predictions [J]. Ultrasound Med Biol, 2024, 50(1): 77-90. [23] 刘晶. 基于宽波束激励的高帧频超声成像方法研究与实现 [D].沈阳:东北大学,2019.
