Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo

doi:10.1002/jbio.202300289

	Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo
	Li, Xinke1 ; Ge, Peng1 ; Shen, Yuting1 ; Gao, Feng1 ; Gao, Fei1,2,3
	2023
发表期刊	JOURNAL OF BIOPHOTONICS (IF:2.0[JCR-2023],2.6[5-Year])
ISSN	1864-063X
EISSN	1864-0648
卷号	17 期号:2
DOI	10.1002/jbio.202300289
摘要	Photoacoustic imaging (PAI) has been applied to many biomedical applications over the past decades. However, the received PA signal usually suffers from poor SNR. Conventional solution of employing higher-power laser, or doing long-time signal averaging, may raise the system cost, time consumption, and tissue damage. Another strategy is de-noising algorithm design. In this paper, we propose a gradient-based adaptive wavelet de-noising method, which sets the energy gradient mutation point of low-frequency wavelet components as the threshold. We conducted simulation, ex-vivo and in-vivo experiments using acoustic-resolution PAM. The quality of de-noised PA image/signal by our proposed algorithm has improved by at least 30%, in comparison to the traditional signal denoising algorithms, which produces better contrast and clearer details. Moreover, it produces good results when dealing with multi-layer structures. The proposed de-noising method provides potential to improve the SNR of PA signal under single-shot low-power laser illumination for biomedical applications in vivo. © 2023 Wiley-VCH GmbH.
关键词	Image denoising Image enhancement Medical applications Photoacoustic effect Signal to noise ratio Adaptive wavelets De-noising Denoising methods Gradient based In-vivo In-Vivo imaging Low power laser Photo-acoustic imaging Wavelet denoising Wavelets transform
URL	查看原文
收录类别	EI
语种	英语
出版者	John Wiley and Sons Inc
EI入藏号	20235015215635
EI主题词	Wavelet transforms
EI分类号	716.1 Information Theory and Signal Processing ; 723.2 Data Processing and Image Processing ; 741.1 Light/Optics ; 751.1 Acoustic Waves ; 921.3 Mathematical Transformations
原始文献类型	Article in Press
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/347911
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_本科生
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	Li, Xinke,Ge, Peng,Shen, Yuting,et al. Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo[J]. JOURNAL OF BIOPHOTONICS,2023,17(2).
APA	Li, Xinke,Ge, Peng,Shen, Yuting,Gao, Feng,&Gao, Fei.(2023).Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo.JOURNAL OF BIOPHOTONICS,17(2).
MLA	Li, Xinke,et al."Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo".JOURNAL OF BIOPHOTONICS 17.2(2023).