Photoacoustic Signal Enhancement using a Novel Adaptive Filtering Algorithm

被引:1
作者
Zafar, Mohsin [1 ]
Manwar, Rayyan [1 ]
Kratkiewicz, Karl [1 ]
Hosseinzadeh, Matin [2 ]
Hariri, Ali [1 ]
Noei, Shahryar [2 ]
Avanaki, Mohammad [1 ,3 ,4 ]
机构
[1] Wayne State Univ, Dept Biomed Engn, Detroit, MI 48201 USA
[2] Sharif Univ Technol, Dept Elect Engn, Tehran, Iran
[3] Wayne State Univ, Sch Med, Dept Neurol, Detroit, MI 48201 USA
[4] Barbara Ann Karmanos Canc Inst, Detroit, MI 48201 USA
来源
PHOTONS PLUS ULTRASOUND: IMAGING AND SENSING 2019 | 2019年 / 10878卷
关键词
photoacoustic imaging; signal enhancement; low-energy laser diodes; EMPIRICAL MODE DECOMPOSITION; COMPUTED-TOMOGRAPHY; MICROSCOPY; REDUCTION;
D O I
10.1117/12.2510557
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Photoacoustic (PA) signal experiences excessive background noise when generated using cost-effective, low-energy laser diodes. A denoising technique is essential in this case. Averaging is a common approach to increase the Signal-to-Noise Ratio (SNR) of PA signals. This technique requires numbers of data acquisition in hundreds and thousands and hence, demands more hardware and time consuming at the same time. Here, an adaptive method based on Adaptive Line Enhancers (ALE) algorithm to improve the SNR of PA signals has been presented. Our results validate the feasibility of the usage of an adaptive method and also indicate excellent improvement in terms of increasing the SNR of the PA signals. Additionally, this proposed algorithm requires way less number of acquisitions as compared to the conventional averaging techniques that leads to faster PA image processing.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Adaptive local iterative filtering for signal decomposition and instantaneous frequency analysis
    Cicone, Antonio
    Liu, Jingfang
    Zhou, Haomin
    APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS, 2016, 41 (02) : 384 - +
  • [32] Denoising preterm EEG by signal decomposition and adaptive filtering: A comparative study
    Navarro, X.
    Poree, F.
    Beuchee, A.
    Carrault, G.
    MEDICAL ENGINEERING & PHYSICS, 2015, 37 (03) : 315 - 320
  • [33] Stabilization and variations to the adaptive local iterative filtering algorithm: the fast resampled iterative filtering method
    Barbarino, Giovanni
    Cicone, Antonio
    NUMERISCHE MATHEMATIK, 2024, 156 (02) : 395 - 433
  • [34] Adaptive algorithms for solving generalized eigenvalue signal enhancement problems
    Morgan, DR
    SIGNAL PROCESSING, 2004, 84 (06) : 957 - 968
  • [35] Adaptive Empirical Mode Decomposition for Signal Enhancement with application to speech
    Chatlani, Navin
    Soraghan, John J.
    PROCEEDINGS OF IWSSIP 2008: 15TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING, 2008, : 101 - 104
  • [36] Signal enhancement in wireless sensor networks based on adaptive filters
    Tang, Jun
    JOURNAL OF MEASUREMENTS IN ENGINEERING, 2023, 11 (02) : 141 - 153
  • [37] Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing
    Matz, Vaclav
    Smid, Radislav
    Starman, Stanislav
    Kreidl, Marcel
    ULTRASONICS, 2009, 49 (08) : 752 - 759
  • [38] Photoacoustic signal measurement using thin film Fabry-Perot optical interferometer for photoacoustic microscopy
    Park, Soongho
    Eom, Jonghyun
    Lee, Byeong Ha
    2015 IEEE SENSORS, 2015, : 564 - 566
  • [39] Reconstruction of Photoacoustic Tomography Inside a Scattering Layer Using a Matrix Filtering Method
    Rui, Wei
    Liu, Zhipeng
    Tao, Chao
    Liu, Xiaojun
    APPLIED SCIENCES-BASEL, 2019, 9 (10):
  • [40] Adaptive beamforming for photoacoustic imaging using linear array transducer
    Park, Suhyun
    Karpiouk, Andrei B.
    Aglyamov, Salavat R.
    2008 IEEE ULTRASONICS SYMPOSIUM, VOLS 1-4 AND APPENDIX, 2008, : 1088 - 1091