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Discrete wavelet transform

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https://www.readbyqxmd.com/read/28406919/what-are-the-assets-and-weaknesses-of-hfo-detectors-a-benchmark-framework-based-on-realistic-simulations
#1
Nicolas Roehri, Francesca Pizzo, Fabrice Bartolomei, Fabrice Wendling, Christian-George Bénar
High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors...
2017: PloS One
https://www.readbyqxmd.com/read/28406916/applications-of-fractional-lower-order-s-transform-time-frequency-filtering-algorithm-to-machine-fault-diagnosis
#2
Junbo Long, Haibin Wang, Daifeng Zha, Peng Li, Huicheng Xie, Lili Mao
Stockwell transform(ST) time-frequency representation(ST-TFR) is a time frequency analysis method which combines short time Fourier transform with wavelet transform, and ST time frequency filtering(ST-TFF) method which takes advantage of time-frequency localized spectra can separate the signals from Gaussian noise. The ST-TFR and ST-TFF methods are used to analyze the fault signals, which is reasonable and effective in general Gaussian noise cases. However, it is proved that the mechanical bearing fault signal belongs to Alpha(α) stable distribution process(1 < α < 2) in this paper, even the noise also is α stable distribution in some special cases...
2017: PloS One
https://www.readbyqxmd.com/read/28381053/lithographic-source-optimization-based-on-adaptive-projection-compressive-sensing
#3
Xu Ma, Dongxiang Shi, Zhiqiang Wang, Yanqiu Li, Gonzalo R Arce
This paper proposes to use the a-priori knowledge of the target layout patterns to design data-adaptive compressive sensing (CS) methods for efficient source optimization (SO) in lithography systems. A set of monitoring pixels are selected from the target layout based on blue noise random patterns. The SO is then formulated as an under-determined linear problem to improve image fidelity according to the monitoring pixels. Adaptive projections are then designed, based on the a-priori knowledge of the target layout, in order to further reduce the dimension of the optimization problem, while trying to retain the SO performance...
March 20, 2017: Optics Express
https://www.readbyqxmd.com/read/28365843/real-time-detection-of-organic-contamination-events-in-water-distribution-systems-by-principal-components-analysis-of-ultraviolet-spectral-data
#4
Jian Zhang, Dibo Hou, Ke Wang, Pingjie Huang, Guangxin Zhang, Hugo Loáiciga
The detection of organic contaminants in water distribution systems is essential to protect public health from potential harmful compounds resulting from accidental spills or intentional releases. Existing methods for detecting organic contaminants are based on quantitative analyses such as chemical testing and gas/liquid chromatography, which are time- and reagent-consuming and involve costly maintenance. This study proposes a novel procedure based on discrete wavelet transform and principal component analysis for detecting organic contamination events from ultraviolet spectral data...
April 1, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28343061/automated-diabetic-macular-edema-dme-grading-system-using-dwt-dct-features-and-maculopathy-index
#5
U Rajendra Acharya, Muthu Rama Krishnan Mookiah, Joel E W Koh, Jen Hong Tan, Sulatha V Bhandary, A Krishna Rao, Yuki Hagiwara, Chua Kuang Chua, Augustinus Laude
The cause of diabetic macular edema (DME) is due to prolonged and uncontrolled diabetes mellitus (DM) which affects the vision of diabetic subjects. DME is graded based on the exudate location from the macula. It is clinically diagnosed using fundus images which is tedious and time-consuming. Regular eye screening and subsequent treatment may prevent the vision loss. Hence, in this work, a hybrid system based on Radon transform (RT), discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed for an automated detection of DME...
March 19, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28324937/data-driven-estimation-of-blood-pressure-using-photoplethysmographic-signals
#6
Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang
Noninvasive measurement of blood pressure by optical methods receives considerable interest, but the complexity of the measurement and the difficulty of adjusting parameters restrict applications. We develop a method for estimating the systolic and diastolic blood pressure using a single-point optical recording of a photoplethysmographic (PPG) signal. The estimation is data-driven, we use automated machine learning algorithms instead of mathematical models. Combining supervised learning with a discrete wavelet transform, the method is insensitive to minor irregularities in the PPG waveform, hence both pulse oximeters and smartphone cameras can record the signal...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28316861/complexity-analysis-of-electroencephalogram-dynamics-in-patients-with-parkinson-s-disease
#7
Guotao Liu, Yanping Zhang, Zhenghui Hu, Xiuquan Du, Wanqing Wu, Chenchu Xu, Xiangyang Wang, Shuo Li
In this study, a new combination scheme has been proposed for detecting Parkinson's disease (PD) from electroencephalogram (EEG) signal recorded from normal subjects and PD patients. The scheme is based on discrete wavelet transform (DWT), sample entropy (SampEn), and the three-way decision model in analysis of EEG signal. The EEG signal is noisy and nonstationary, and, as a consequence, it becomes difficult to distinguish it visually. However, the scheme is a well-established methodology in analysis of EEG signal in three stages...
2017: Parkinson's Disease
https://www.readbyqxmd.com/read/28295824/wavelet-entropy-of-bold-time-series-an-application-to-rolandic-epilepsy
#8
Lalit Gupta, Jacobus F A Jansen, Paul A M Hofman, René M H Besseling, Anton J A de Louw, Albert P Aldenkamp, Walter H Backes
PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated...
March 11, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28284000/a-method-for-microcalcifications-detection-in-breast-mammograms
#9
Abbas H Hassin Alasadi, Ahmed Kadem Hamed Al-Saedi
Breast cancer is the most cause of death for women above age 40 around the world. In this paper, we propose a method to detect microcalcifications in digital mammography images using two-dimensional Discrete Wavelets Transform and image enhancement techniques for removing noise as well as to get a better contrast. The initial step is applying a preprocessing techniques to improve the edge of the breast and then segmentation process (Region of interest) for eliminating some regions in the image, which are not useful for the mammography interpretation...
April 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28278203/a-high-performance-seizure-detection-algorithm-based-on-discrete-wavelet-transform-dwt-and-eeg
#10
Duo Chen, Suiren Wan, Jing Xiang, Forrest Sheng Bao
In the past decade, Discrete Wavelet Transform (DWT), a powerful time-frequency tool, has been widely used in computer-aided signal analysis of epileptic electroencephalography (EEG), such as the detection of seizures. One of the important hurdles in the applications of DWT is the settings of DWT, which are chosen empirically or arbitrarily in previous works. The objective of this study aimed to develop a framework for automatically searching the optimal DWT settings to improve accuracy and to reduce computational cost of seizure detection...
2017: PloS One
https://www.readbyqxmd.com/read/28269716/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#11
Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib
Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269119/analysis-of-embolic-signals-with-directional-dual-tree-rational-dilation-wavelet-transform
#12
Gorkem Serbes, Nizamettin Aydin
The dyadic discrete wavelet transform (dyadic-DWT), which is based on fixed integer sampling factor, has been used before for processing piecewise smooth biomedical signals. However, the dyadic-DWT has poor frequency resolution due to the low-oscillatory nature of its wavelet bases and therefore, it is less effective in processing embolic signals (ESs). To process ESs more effectively, a wavelet transform having better frequency resolution than the dyadic-DWT is needed. Therefore, in this study two ESs, containing micro-emboli and artifact waveforms, are analyzed with the Directional Dual Tree Rational-Dilation Wavelet Transform (DDT-RADWT)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268540/robust-watermarking-in-non-roi-of-medical-images-based-on-dct-dwt
#13
M Jamali, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian
Increasing demand and utilization of telemedicine require transmission of medical information and images over internet. Since authenticity of received images is crucial and patient's information should be included with minimum changes in images, robust watermarking schemes are needed. In this paper, we propose a robust watermark method that embeds patient's information outside the region of interest (ROI) in medical image. In order to find appropriate regions for embedding, we use saliency as a means of measuring importance of regions and find blocks having minimum overlap with the ROI...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268417/combined-accelerometer-and-emg-analysis-to-differentiate-essential-tremor-from-parkinson-s-disease
#14
Nooshin Haji Ghassemi, Franz Marxreiter, Cristian F Pasluosta, Patrick Kugler, Johannes Schlachetzki, Axel Schramm, Bjoern M Eskofier, Jochen Klucken
In this study, we intended to differentiate patients with essential tremor (ET) from tremor dominant Parkinson disease (PD). Accelerometer and electromyographic signals of hand movement from standardized upper extremity movement tests (resting, holding, carrying weight) were extracted from 13 PD and 11 ET patients. The signals were filtered to remove noise and non-tremor high frequency components. A set of statistical features was then extracted from the discrete wavelet transformation of the signals. Principal component analysis was utilized to reduce dimensionality of the feature space...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28261818/on-the-impact-of-smoothing-and-noise-on-robustness-of-ct-and-cbct-radiomics-features-for-patients-with-head-and-neck-cancers
#15
Hassan Bagher-Ebadian, Farzan Siddiqui, Chang Liu, Benjamin Movsas, Indrin J Chetty
PURPOSE: We investigated the characteristics of radiomics features extracted from planning CT (pCT) and cone beam CT (CBCT) image datasets acquired for 18 oropharyngeal cancer patients treated with fractionated radiation therapy. Images were subjected to smoothing, sharpening, and noise to evaluate changes in features relative to baseline datasets. METHODS: Textural features were extracted from tumor volumes, contoured on pCT and CBCT images, according to the following eight different classes: intensity based histogram features (IBHF), gray level run length (GLRL), law's textural information (LAWS), discrete orthonormal stockwell transform (DOST), local binary pattern (LBP), two-dimensional wavelet transform (2DWT), Two dimensional Gabor filter (2DGF), and gray level co-occurrence matrix (GLCM)...
March 6, 2017: Medical Physics
https://www.readbyqxmd.com/read/28247307/automated-diagnosis-of-heart-sounds-using-rule-based-classification-tree
#16
Mohamed Esmail Karar, Sahar H El-Khafif, Mohamed A El-Brawany
In order to assist the diagnosis procedure of heart sound signals, this paper presents a new automated method for classifying the heart status using a rule-based classification tree into normal and three abnormal cases; namely the aortic valve stenosis, aortic insufficient, and ventricular septum defect. The developed method includes three main steps as follows. First, one cycle of the heart sound signals is automatically detected and segmented based on time properties of the heart signals. Second, the segmented cycle is preprocessed with the discrete wavelet transform and then largest Lyapunov exponents are calculated to generate the dynamical features of heart sound time series...
April 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28227980/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#17
Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Mohamed A Oransa, Khaled S Sayed, Ayman M Mohamed, Ahmed T Ahmed, Ahmed M Elbaz, Ayman M Eldeib
Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227348/analysis-of-embolic-signals-with-directional-dual-tree-rational-dilation-wavelet-transform
#18
Gorkem Serbes, Nizamettin Aydin, Gorkem Serbes, Nizamettin Aydin, Nizamettin Aydin, Gorkem Serbes
The dyadic discrete wavelet transform (dyadic-DWT), which is based on fixed integer sampling factor, has been used before for processing piecewise smooth biomedical signals. However, the dyadic-DWT has poor frequency resolution due to the low-oscillatory nature of its wavelet bases and therefore, it is less effective in processing embolic signals (ESs). To process ESs more effectively, a wavelet transform having better frequency resolution than the dyadic-DWT is needed. Therefore, in this study two ESs, containing micro-emboli and artifact waveforms, are analyzed with the Directional Dual Tree Rational-Dilation Wavelet Transform (DDT-RADWT)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226716/robust-watermarking-in-non-roi-of-medical-images-based-on-dct-dwt
#19
M Jamali, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, M Jamali, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, K Ward, S M R Soroushmehr, M Jamali, S Samavi, K Najarian, N Karimi
Increasing demand and utilization of telemedicine require transmission of medical information and images over internet. Since authenticity of received images is crucial and patient's information should be included with minimum changes in images, robust watermarking schemes are needed. In this paper, we propose a robust watermark method that embeds patient's information outside the region of interest (ROI) in medical image. In order to find appropriate regions for embedding, we use saliency as a means of measuring importance of regions and find blocks having minimum overlap with the ROI...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226610/data-driven-estimation-of-blood-pressure-using-photoplethysmographic-signals
#20
Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang, Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang, Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang
Noninvasive measurement of blood pressure by optical methods receives considerable interest, but the complexity of the measurement and the difficulty of adjusting parameters restrict applications. We develop a method for estimating the systolic and diastolic blood pressure using a single-point optical recording of a photoplethysmographic (PPG) signal. The estimation is data-driven, we use automated machine learning algorithms instead of mathematical models. Combining supervised learning with a discrete wavelet transform, the method is insensitive to minor irregularities in the PPG waveform, hence both pulse oximeters and smartphone cameras can record the signal...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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