STFT or CWT for the detection of Doppler ultrasound embolic signals

Gonçalves, Ivo B.; Leiria, Ana; Moura, M. M. M.

doi:10.1002/cnm.2546

Cited by 7 publications

(3 citation statements)

References 26 publications

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“…11. Time-frequency (TF) representations of Doppler ultrasound signals are used for emboli detection [6,11]. In TF-based detection systems, first DWT or DWPT are used for de-noising as preprocessing stage.…”

Section: Processing Real Quadrature Blood Flow Signalsmentioning

confidence: 99%

Directional dual-tree complex wavelet packet transforms for processing quadrature signals

Serbes

Gülçür

Aydin

2014

Med Biol Eng Comput

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Quadrature signals containing in-phase and quadrature-phase components are used in many signal processing applications in every field of science and engineering. Specifically, Doppler ultrasound systems used to evaluate cardiovascular disorders noninvasively also result in quadrature format signals. In order to obtain directional blood flow information, the quadrature outputs have to be preprocessed using methods such as asymmetrical and symmetrical phasing filter techniques. These resultant directional signals can be employed in order to detect asymptomatic embolic signals caused by small emboli, which are indicators of a possible future stroke, in the cerebral circulation. Various transform-based methods such as Fourier and wavelet were frequently used in processing embolic signals. However, most of the times, the Fourier and discrete wavelet transforms are not appropriate for the analysis of embolic signals due to their non-stationary time-frequency behavior. Alternatively, discrete wavelet packet transform can perform an adaptive decomposition of the time-frequency axis. In this study, directional discrete wavelet packet transforms, which have the ability to map directional information while processing quadrature signals and have less computational complexity than the existing wavelet packet-based methods, are introduced. The performances of proposed methods are examined in detail by using single-frequency, synthetic narrow-band, and embolic quadrature signals.

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Section: Processing Real Quadrature Blood Flow Signalsmentioning

confidence: 99%

Directional dual-tree complex wavelet packet transforms for processing quadrature signals

Serbes

Gülçür

Aydin

2014

Med Biol Eng Comput

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“…In literature, short time Fourier transform and continuous wavelet transform [10] based emboli detection systems have been previously proposed. In [11], as an emboli detection system, discrete wavelet transform (DWT) was employed in feature extraction and the obtained features are given to a trapezoidal fuzzy logic classifier.…”

Section: Introductionmentioning

confidence: 99%

A micro emboli vs non-emboli classification system based on the directional dual tree rational dilation wavelet transform

Serbes

Şakar

Aydin

2015

2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)

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Transcranial Doppler (TCD) is a widely used, non-invasive, rapid and reproducible monitoring method for observing the condition of middle cerebral artery. Micro embolic signals, which appear in various clinical scenarios such as; carotid stenosis, aortic arch plaques, atrial fibrillation, myocardial infarction, patent foramen ovale and valvular stenosis, can be detected by the analysis of TCD signals. Discrete wavelet transform based methods were frequently used in literature for micro embolic signal detection. However, in all the previously used complex/non-complex discrete wavelet transform based methods, low Q-factor wavelets were employed for feature extraction. Low Q-factor wavelets have been successfully used for processing piecewise smooth signals but for the embolic signals, a discrete wavelet transform with better frequency resolution is needed. Therefore in this study, a novel Directional Dual Tree Rational Dilation Wavelet Transform (DDT-RADWT), in which the Q-factor of the analysis and synthesis filters can be adjusted due to the properties of signal of interest, is used as the feature extractor. DDT-RADWT is applied to a dataset consisting of 130 micro embolic signals and 130 non-embolic signals (65 artifacts and 65 Doppler speckles) and the obtained coefficients are used as features. In the proposed method, in order to utilize from the different frequency characteristics of micro embolic, artifact and Doppler speckle signals, the DDT-RADWT is applied with high Q-factor filters. The extracted coefficients are given to k-NN and SVM classifiers with the aim of discriminating two classes of micro embolic signals and non-embolic signals. The results show that higher general accuracy and micro embolic signal detection accuracies are obtained with high Q-factor wavelet analysis.

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“…Simulation of middle cerebral artery Doppler signals is carried out by I.B. Gonçalves et al in order to detect the presence of emboli in blood circulation. D. Pinho et al propose an automatic method to segment and track red blood cells flowing through microchannels.…”

mentioning

confidence: 99%

Special issue on computational methods for biomedical image processing and analysis

2013

Numer Methods Biomed Eng

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STFT or CWT for the detection of Doppler ultrasound embolic signals

Cited by 7 publications

References 26 publications

Directional dual-tree complex wavelet packet transforms for processing quadrature signals

Directional dual-tree complex wavelet packet transforms for processing quadrature signals

A micro emboli vs non-emboli classification system based on the directional dual tree rational dilation wavelet transform

Special issue on computational methods for biomedical image processing and analysis

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