Multifrequency transducer for microemboli classification and sizing

被引:6
|
作者
Palanchon, P [1 ]
Bouakaz, A
Klein, J
de Jong, N
机构
[1] Erasmus Med Ctr Rotterdam, Dept Cardiol, Ctr Thorax, NL-3000 DR Rotterdam, Netherlands
[2] Erasmus Med Ctr, Dept Anesthesiol, NL-3000 DR Rotterdam, Netherlands
关键词
harmonic-subharmonic-emboli-characterization;
D O I
10.1109/TBME.2005.857641
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The classification of circulating microemboli as gaseous or particulate matter is essential to establish the relevance of the detected embolic signals. Until now, Doppler techniques have failed to determine unambiguously the nature of circulating microemboli. Recently, a new approach based on the analysis of radio frequency (RF) signal and using the nonlinear characteristics of gaseous bubbles to classify emboli was investigated. The main limitation of these studies was the requirement of two separate transducers for transmission and reception. This paper presents a multi-frequency transducer with two independent transmitting elements and a separate receiving part with a wide frequency band. The transmitting elements are positioned in a concentric design and cover a frequency band between 100 and 600 kHz. The receiving part consists of a polyvinylidene fluoride layer. The new transducer has been tested in vitro using gaseous emboli. It could correctly classify and size air emboli with diameters ranging from 10 mu m to 105 mu m.
引用
收藏
页码:2087 / 2092
页数:6
相关论文
共 50 条
  • [41] Edge-preserving classification of multifrequency multipolarization SAR images
    Andreadis, A
    Benelli, G
    Garzelli, A
    INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, PROCEEDINGS - VOL III, 1996, : 899 - 901
  • [42] Novel supervised classification approach for multifrequency polarimetric SAR data
    Biao You
    Bin Xu
    Jian Yang
    Chunmao Yeh
    Jianshe Song
    Journal of Systems Engineering and Electronics, 2015, 26 (06) : 1216 - 1221
  • [43] Novel supervised classification approach for multifrequency polarimetric SAR data
    You, Biao
    Xu, Bin
    Yang, Jian
    Yeh, Chunmao
    Song, Jianshe
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2015, 26 (06) : 1216 - 1221
  • [44] Decision Fusion of Classifiers for Multifrequency PolSAR and Optical Data Classification
    Kasapoglu, N. Gokhan
    Eltoft, Torbjorn
    PROCEEDINGS OF 6TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SPACE TECHNOLOGIES (RAST 2013), 2013, : 411 - 416
  • [45] Optimized Wishart Network for an Efficient Classification of Multifrequency PolSAR Data
    Gadhiya, Tushar
    Roy, Anil K.
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 15 (11) : 1720 - 1724
  • [46] A Reconstruction-Classification Method for Multifrequency Electrical Impedance Tomography
    Malone, Emma
    dos Santos, Gustavo Sato
    Holder, David
    Arridge, Simon
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2015, 34 (07) : 1486 - 1497
  • [47] Classification of Tropical Vegetation Using Multifrequency Partial SAR Polarimetry
    Lardeux, Cedric
    Frison, Pierre-Louis
    Tison, Celine
    Souyris, Jean-Claude
    Stoll, Benoit
    Fruneau, Benedicte
    Rudant, Jean-Paul
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2011, 8 (01) : 133 - 137
  • [48] Tensorization of Multifrequency PolSAR Data for Classification Using an Autoencoder Network
    De, Shaunak
    Ratha, Debanshu
    Ratha, Dikshya
    Bhattacharya, Avik
    Chaudhuri, Subhasis
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 15 (04) : 542 - 546
  • [49] Support Vector Machine for Multifrequency SAR Polarimetric Data Classification
    Lardeux, Cedric
    Frison, Pierre-Louis
    Tison, Celine
    Souyris, Jean-Claude
    Stoll, Benoit
    Fruneau, Benedicte
    Rudant, Jean-Paul
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (12): : 4143 - 4152
  • [50] Local Renewable Energy Communities: Classification and Sizing
    Canizes, Bruno
    Costa, Joao
    Bairrao, Diego
    Vale, Zita
    ENERGIES, 2023, 16 (05)