Adaptive denoising of photoacoustic signal and image based on modified Kalman filter

doi:10.1002/jbio.202200362

	Adaptive denoising of photoacoustic signal and image based on modified Kalman filter
	Hu, Tianqu1 ; Huang, Zihao1 ; Ge, Peng1 ; 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	16 期号:5
发表状态	已发表
DOI	10.1002/jbio.202200362
摘要	As a burgeoning medical imaging method based on hybrid fusion of light and ultrasound, photoacoustic imaging (PAI) has demonstrated high potential in various biomedical applications, especially in revealing the functional and molecular information to improve diagnostic accuracy. However, stemming from weak amplitude and unavoidable random noise, caused by limited laser power and severe attenuation in deep tissue imaging, PA signals are usually of low signal-to-noise ratio, and reconstructed PA images are of low quality. Despite that conventional Kalman filter (KF) can remove Gaussian noise in time domain, it lacks adaptability in real-time estimation due to its fixed model. Moreover, KF-based denoising algorithm has not been applied in PAI before. In this paper, we propose an adaptive modified KF (MKF) targeted at PAI denoising by tuning system noise matrix Q and measurement noise matrix R in the conventional KF model. Additionally, in order to compensate the signal skewing caused by MKF, we cascade the backward part of Rauch-Tung-Striebel smoother, which utilizes the newly determined Q. Finally, as a supplement, we add a commonly used differential filter to remove in-band reflection artifacts. Experimental results using phantom and ex vivo colorectal tissue are provided to prove validity of the algorithm.
关键词	adaptive denoising backward RTS smoother modified Kalman filter photoacoustic imaging
URL	查看原文
收录类别	SCI ; EI ; SCOPUS
语种	英语
资助项目	Double First-Class Initiative Fund of ShanghaiTech University[2022X0203-904-04] ; National Natural Science Foundation of China[61805139] ; Shanghai Clinical Research and Trial Center[2022A0305-418-02] ; United Imaging Intelligence[2019X0203-501-02]
WOS研究方向	Biochemistry & Molecular Biology ; Biophysics ; Optics
WOS类目	Biochemical Research Methods ; Biophysics ; Optics
WOS记录号	WOS:000917199000001
出版者	WILEY-V C H VERLAG GMBH
EI入藏号	20230513463099
EI主题词	Diagnosis
EI分类号	461.1 Biomedical Engineering ; 461.2 Biological Materials and Tissue Engineering ; 461.6 Medicine and Pharmacology ; 716.1 Information Theory and Signal Processing ; 723.2 Data Processing and Image Processing ; 741.1 Light/Optics ; 746 Imaging Techniques ; 751.1 Acoustic Waves ; 921 Mathematics
原始文献类型	Journal article (JA)
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/278846
专题	信息科学与技术学院_本科生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
通讯作者	Gao, Feng; Gao, Fei
作者单位	1.ShanghaiTech Univ, Sch Informat Sci & Technol, Hybrid Imaging Syst Lab, Shanghai 201210, Peoples R China 2.Shanghai Clin Res & Trial Ctr, Shanghai, Peoples R China 3.Shanghai Engn Res Ctr Energy Efficient & Custom AI, Shanghai, Peoples R 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	Hu, Tianqu,Huang, Zihao,Ge, Peng,et al. Adaptive denoising of photoacoustic signal and image based on modified Kalman filter[J]. JOURNAL OF BIOPHOTONICS,2023,16(5).
APA	Hu, Tianqu,Huang, Zihao,Ge, Peng,Gao, Feng,&Gao, Fei.(2023).Adaptive denoising of photoacoustic signal and image based on modified Kalman filter.JOURNAL OF BIOPHOTONICS,16(5).
MLA	Hu, Tianqu,et al."Adaptive denoising of photoacoustic signal and image based on modified Kalman filter".JOURNAL OF BIOPHOTONICS 16.5(2023).