S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo

doi:10.1016/j.ultrasmedbio.2023.07.014

	S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo
	Shen, Yuting1 ; Zhang, Jiadong1 ; Jiang, Daohuai1 ; Gao, Zijian1 ; Zheng, Yuwei1 ; Gao, Feng1 ; Gao, Fei1,2,3
	2023
发表期刊	ULTRASOUND IN MEDICINE AND BIOLOGY (IF:2.4[JCR-2023],2.9[5-Year])
ISSN	0301-5629
EISSN	1879-291X
卷号	50 期号:1 页码:18-27
DOI	10.1016/j.ultrasmedbio.2023.07.014
摘要	Objective: Photoacoustic imaging has undergone rapid development in recent years. To simulate photoacoustic imaging on a computer, the most popular MATLAB toolbox currently used for the forward projection process is k-Wave. However, k-Wave suffers from significant computation time. Here we propose a straightforward simulation approach based on superposed Wave (s-Wave) to accelerate photoacoustic simulation. Methods: In this study, we consider the initial pressure distribution as a collection of individual pixels. By obtaining standard sensor data from a single pixel beforehand, we can easily manipulate the phase and amplitude of the sensor data for specific pixels using loop and multiplication operators. The effectiveness of this approach is validated through an optimization-based reconstruction algorithm. Results: The results reveal significantly reduced computation time compared with k-Wave. Particularly in a sparse 3-D configuration, s-Wave exhibits a speed improvement >2000 times compared with k-Wave. In terms of optimization-based image reconstruction, in vivo imaging results reveal that using the s-Wave method yields images highly similar to those obtained using k-Wave, while reducing the reconstruction time by approximately 50 times. Conclusion: Proposed here is an accelerated optimization-based algorithm for photoacoustic image reconstruction, using the fast s-Wave forward projection simulation. Our method achieves substantial time savings, particularly in sparse system configurations. Future work will focus on further optimizing the algorithm and expanding its applicability to a broader range of photoacoustic imaging scenarios. © 2023
关键词	MATLAB Photoacoustic effect Pixels Shear waves Computation time Images reconstruction Imaging simulation Optimisations Optimization-based reconstruction Photo-acoustic imaging Photoacoustic image Photoacoustic imaging simulation Sensors data Superposed wave
收录类别	EI
语种	英语
出版者	Elsevier Inc.
EI入藏号	20234114869282
EI主题词	Image reconstruction
EI分类号	723.5 Computer Applications ; 741.1 Light/Optics ; 751.1 Acoustic Waves ; 921 Mathematics ; 931.1 Mechanics
原始文献类型	Article in Press
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/340979
专题	信息科学与技术学院信息科学与技术学院_PI研究组_高飞组信息科学与技术学院_硕士生信息科学与技术学院_博士生
通讯作者	Gao, Feng; Gao, Fei
作者单位	1.Hybrid Imaging System Laboratory, School of Information Science and Technology, ShanghaiTech University, Shanghai, China; 2.Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, Shanghai, China; 3.Shanghai Clinical Research and Trial Center, Shanghai, China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Shen, Yuting,Zhang, Jiadong,Jiang, Daohuai,et al. S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo[J]. ULTRASOUND IN MEDICINE AND BIOLOGY,2023,50(1):18-27.
APA	Shen, Yuting.,Zhang, Jiadong.,Jiang, Daohuai.,Gao, Zijian.,Zheng, Yuwei.,...&Gao, Fei.(2023).S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo.ULTRASOUND IN MEDICINE AND BIOLOGY,50(1),18-27.
MLA	Shen, Yuting,et al."S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo".ULTRASOUND IN MEDICINE AND BIOLOGY 50.1(2023):18-27.