A Preliminary Study of the Mean Scatterer Spacing Estimation from Pellets using Wavelet-Based Cepstral Analysis

被引:0
|
作者
Nasr, Remie [1 ]
Falou, Omar [1 ,2 ]
Shahin, Ahmad [1 ]
Wirtzfeld, Lauren [3 ]
Berndl, Elizabeth [3 ]
Kolios, Michael C. [3 ]
机构
[1] Amer Univ Culture & Educ, Lebanese Univ, Azm Ctr Res Biotechnol & Its Applicat DSST, Tripoli, Lebanon
[2] Amer Univ Culture & Educ, Lebanese Univ, Dept Sci, Tripoli, Lebanon
[3] Inst Biomed Engn Sci & Technol, Toronto, ON, Canada
关键词
cepstral analysis; wavelet transform; scatterer spacing; pellet; quantitative ultrasound; scatterer properties; tissue characterization; ultrasound backscatter;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Ultrasonic backscattered signals contain information regarding the scatterer structures of the imaged biological tissues; a uniform scatterer distribution could be represented by periodicities in the backscattered signals. This work aims to characterize these scatterer periodicities using wavelet improved cepstral analysis. This technique was tested on simulated ultrasound signals, where the periodicity was clearly visible. Simulation results indicate that this technique can effectively determine the value of the scatterer spacing. The technique was then tested on a HT-29 cell pellet, where the estimated scatterer spacing was found to be 17.67 +/- 3.85 mu m. Future work includes improving the technique with the aim of accurately estimating the mean scatterer spacing in tissues.
引用
收藏
页码:85 / 88
页数:4
相关论文
共 50 条
  • [21] Hyperspectral data analysis using wavelet-based classifiers
    Younan, NH
    King, RL
    Bennett, HH
    IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, 2000, : 390 - 392
  • [22] EEG analysis using wavelet-based information tools
    Rosso, O. A.
    Martin, M. T.
    Figliola, A.
    Keller, K.
    Plastino, A.
    JOURNAL OF NEUROSCIENCE METHODS, 2006, 153 (02) : 163 - 182
  • [23] TIME FREQUENCY ANALYSIS OF ICTAL MEG SIGNALS USING WAVELET-BASED MAXIMUM ENTROPY OF THE MEAN (wMEM)
    Cisneros-Franco, J. M.
    Lina, J-M
    Grova, C.
    Kobayashi, E.
    EPILEPSIA, 2013, 54 : 161 - 162
  • [24] Wavelet-based denoising from multiple noisy realizations: preliminary experiments
    Vautrot, P
    Ricordeau, A
    Bonnet, N
    NONLINEAR IMAGE PROCESSING XI, 2000, 3961 : 34 - 44
  • [25] On-line chatter detection using wavelet-based parameter estimation
    Choi, Taejun
    Shin, Yung C.
    American Society of Mechanical Engineers, Manufacturing Engineering Division, MED, 2000, 11 : 141 - 147
  • [26] Adaptive pulsar time delay estimation using wavelet-based RLS
    Kang, Zhiwei
    He, Hongcai
    Liu, Jin
    Ma, Xin
    Gui, Mingzhen
    OPTIK, 2018, 171 : 266 - 276
  • [27] On-line chatter detection using wavelet-based parameter estimation
    Choi, T
    Shin, YC
    JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2003, 125 (01): : 21 - 28
  • [28] Wavelet-based estimation of hemodynamic response function from fMRI data
    Srikanth, R.
    Ramakrshnan, A. G.
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2006, 16 (02) : 125 - 138
  • [29] Fatigue life analysis using wavelet-based signal decomposition
    Abd Rahim, Airee Afiq
    Abdullah, Shahrum
    Singh, Salvinder Singh Karam
    Nuawi, Mohammad Zaki
    INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY, 2021, 63 (03): : 138 - 147
  • [30] Comparing time series using wavelet-based semblance analysis
    Cooper, G. R. J.
    Cowan, D. R.
    COMPUTERS & GEOSCIENCES, 2008, 34 (02) : 95 - 102