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Discrete wavelet transform

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https://www.readbyqxmd.com/read/28227980/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#1
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
#2
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
#3
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
#4
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
https://www.readbyqxmd.com/read/28226587/combined-accelerometer-and-emg-analysis-to-differentiate-essential-tremor-from-parkinson-s-disease
#5
Nooshin Haji Ghassemi, Franz Marxreiter, Cristian F Pasluosta, Patrick Kugler, Johannes Schlachetzki, Axel Schramm, Bjoern M Eskofier, Jochen Klucken, Nooshin Haji Ghassemi, Franz Marxreiter, Cristian F Pasluosta, Patrick Kugler, Johannes Schlachetzki, Axel Schramm, Bjoern M Eskofier, Jochen Klucken, Johannes Schlachetzki, Nooshin Haji Ghassemi, Cristian F Pasluosta, Patrick Kugler, Franz Marxreiter, 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/28207900/classification-and-identification-of-rhodobryum-roseum-limpr-and-its-adulterants-based-on-fourier-transform-infrared-spectroscopy-ftir-and-chemometrics
#6
Zhen Cao, Zhenjie Wang, Zhonglin Shang, Jiancheng Zhao
Fourier-transform infrared spectroscopy (FTIR) with the attenuated total reflectance technique was used to identify Rhodobryum roseum from its four adulterants. The FTIR spectra of six samples in the range from 4000 cm-1 to 600 cm-1 were obtained. The second-derivative transformation test was used to identify the small and nearby absorption peaks. A cluster analysis was performed to classify the spectra in a dendrogram based on the spectral similarity. Principal component analysis (PCA) was used to classify the species of six moss samples...
2017: PloS One
https://www.readbyqxmd.com/read/28194648/epileptic-seizure-classifications-of-single-channel-scalp-eeg-data-using-wavelet-based-features-and-svm
#7
Suparerk Janjarasjitt
In this study, wavelet-based features of single-channel scalp EEGs recorded from subjects with intractable seizure are examined for epileptic seizure classification. The wavelet-based features extracted from scalp EEGs are simply based on detail and approximation coefficients obtained from the discrete wavelet transform. Support vector machine (SVM), one of the most commonly used classifiers, is applied to classify vectors of wavelet-based features of scalp EEGs into either seizure or non-seizure class. In patient-based epileptic seizure classification, a training data set used to train SVM classifiers is composed of wavelet-based features of scalp EEGs corresponding to the first epileptic seizure event...
February 13, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28191461/three-class-mammogram-classification-based-on-descriptive-cnn-features
#8
M Mohsin Jadoon, Qianni Zhang, Ihsan Ul Haq, Sharjeel Butt, Adeel Jadoon
In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases). In our model we have presented two methods, namely, convolutional neural network-discrete wavelet (CNN-DW) and convolutional neural network-curvelet transform (CNN-CT). An augmented data set is generated by using mammogram patches. To enhance the contrast of mammogram images, the data set is filtered by contrast limited adaptive histogram equalization (CLAHE)...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28173806/ecg-signal-performance-de-noising-assessment-based-on-threshold-tuning-of-dual-tree-wavelet-transform
#9
Oussama El B'charri, Rachid Latif, Khalifa Elmansouri, Abdenbi Abenaou, Wissam Jenkal
BACKGROUND: Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. METHODS: The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet...
February 7, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28158122/high-resolution-wavelet-fractal-compressed-optical-coherence-tomography-images
#10
Mekhalfa Faiza, Saba Adabi, Berkani Daoud, Mohammad R N Avanaki
Three-dimensional (3D) optical coherence tomography (OCT) images could assist specialists in the diagnosis of a disease in a tissue by providing morphological information from it. Since the size of such images is usually extremely large, an appropriate image compression method can help in the storage and transmission of these images. Fractal image compression provides very high compression ratios, and discrete wavelet transform (DWT) retains frequency and spatial information in the signal. In order to combine these two techniques, fractal coding has to be performed in the wavelet domain...
February 1, 2017: Applied Optics
https://www.readbyqxmd.com/read/28113627/reduced-reference-quality-assessment-based-on-the-entropy-of-dwt-coefficients-of-locally-weighted-gradient-magnitudes
#11
S Alireza Golestaneh, Lina Karam
Perceptual image quality assessment (IQA) attempts to use computational models to estimate the image quality in accordance with subjective evaluations. Reduced-reference (RR) image quality assessment (IQA) methods make use of partial information or features extracted from the reference image for estimating the quality of distorted images. Finding a balance between the number of RR features and accuracy of the estimated image quality is essential and important in IQA. In this paper we propose a training-free low-cost RRIQA method that requires a very small number of RR features (6 RR features)...
August 24, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28113594/epileptic-focus-localization-using-discrete-wavelet-transform-based-on-interictal-intracranial-eeg
#12
Duo Chen, Suiren Wan, Forrest Sheng Bao
Over the past decade, with the development of machine learning, Discrete Wavelet Transform (DWT) has been widely used in computer-aided epileptic EEG signal analysis as a powerful timefrequency tool. But some important problems have not yet been benefitted from DWT, including epileptic focus localization, a key task in epilepsy diagnosis and treatment. Additionally, the parameters and settings for DWT are chosen empirically or arbitrarily in previous work. In this work, we propose a framework to use DWT and Support Vector Machine (SVM) for epileptic focus localization problem based on EEG...
August 30, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28113243/highly-reliable-key-generation-from-electrocardiogram-ecg
#13
Nima Karimian, Zimu Guo, Mark Tehranipoor, Domenic Forte
Traditional passwords are inadequate as cryptographic keys, as they are easy to forge and are vulnerable to guessing. Human biometrics have been proposed as a promising alternative due to their intrinsic nature. Electrocardiogram (ECG) is an emerging biometric that is extremely difficult to forge and circumvent, but has not yet been heavily investigated for cryptographic key generation. ECG has challenges with respect to immunity to noise, abnormalities, etc. In this paper, we propose a novel key generation approach that extracts keys from real valued ECG features with high reliability and entropy in mind...
September 8, 2016: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28097047/quantifying-the-on-and-off-contributions-to-the-flash-erg-with-the-discrete-wavelet-transform
#14
Mathieu Gauvin, Maja Sustar, John M Little, Jelka Brecelj, Jean-Marc Lina, Pierre Lachapelle
PURPOSE: Discrete wavelet transform (DWT) analyses suggest that the 20- and 40-Hz components of the short-flash photopic electroretinogram (ERG) are closely related to the ON and OFF pathways, respectively. With the DWT, we examined how the ERG ON and OFF components are modulated by the stimulus intensity and/or duration. METHODS: Discrete wavelet transform descriptors (20, 40 Hz and 40:20-Hz ratio) were extracted from ERGs evoked to 25 combinations of flash durations (150-5 ms) and strengths (0...
January 2017: Translational Vision Science & Technology
https://www.readbyqxmd.com/read/28086909/fast-detection-and-data-compensation-for-electrodes-disconnection-in-long-term-monitoring-of-dynamic-brain-electrical-impedance-tomography
#15
Ge Zhang, Meng Dai, Lin Yang, Weichen Li, Haoting Li, Canhua Xu, Xuetao Shi, Xiuzhen Dong, Feng Fu
BACKGROUND: Electrode disconnection is a common occurrence during long-term monitoring of brain electrical impedance tomography (EIT) in clinical settings. The data acquisition system suffers remarkable data loss which results in image reconstruction failure. The aim of this study was to: (1) detect disconnected electrodes and (2) account for invalid data. METHODS: Weighted correlation coefficient for each electrode was calculated based on the measurement differences between well-connected and disconnected electrodes...
January 7, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28070749/an-automated-microemboli-detection-and-classification-system-using-backscatter-rf-signals-and-differential-evolution
#16
Karim Ferroudji, Nabil Benoudjit, Ayache Bouakaz
Embolic phenomena, whether air or particulate emboli, can induce immediate damages like heart attack or ischemic stroke. Embolus composition (gaseous or particulate matter) is vital in predicting clinically significant complications. Embolus detection using Doppler methods have shown their limits to differentiate solid and gaseous embolus. Radio-frequency (RF) ultrasound signals backscattered by the emboli contain additional information on the embolus in comparison to the traditionally used Doppler signals...
January 9, 2017: Australasian Physical & Engineering Sciences in Medicine
https://www.readbyqxmd.com/read/28066844/tight-graph-framelets-for-sparse-diffusion-mri-q-space-representation
#17
Pew-Thian Yap, Bin Dong, Yong Zhang, Dinggang Shen
In diffusion MRI, the outcome of estimation problems can often be improved by taking into account the correlation of diffusion-weighted images scanned with neighboring wavevectors in q-space. For this purpose, we propose in this paper to employ tight wavelet frames constructed on non-flat domains for multi-scale sparse representation of diffusion signals. This representation is well suited for signals sampled regularly or irregularly, such as on a grid or on multiple shells, in q-space. Using spectral graph theory, the frames are constructed based on quasi-affine systems (i...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28063666/development-of-a-clinical-applicable-graphical-user-interface-to-automatically-detect-exercise-oscillatory-ventilation-the-vodex-tool
#18
Justien Cornelis, Tim Denis, Paul Beckers, Christiaan Vrints, Dirk Vissers, Maggy Goossens
BACKGROUND: Cardiopulmonary exercise testing (CPET) gained importance in the prognostic assessment of especially patients with heart failure (HF). A meaningful prognostic parameter for early mortality in HF is exercise oscillatory ventilation (EOV). This abnormal respiratory pattern is recognized by hypo- and hyperventilation during CPET. Up until now, assessment of EOV is mainly done upon visual agreement or manual calculation. The purpose of this research was to automate the interpretation of EOV so this prognostic parameter could be readily investigated during CPET...
December 29, 2016: International Journal of Cardiology
https://www.readbyqxmd.com/read/28048555/su-c-207b-01-a-novel-graphics-processing-units-gpu-implementation-of-discrete-wavelet-transformation
#19
A Liu, M Chen, S Jiang, W Lu
PURPOSE: To design and implement a GPU-based discrete wavelet transformation (DWT) to be used in medical image reconstruction, image processing, and data compression. DWTs are widely used in medical physics, but the computation of DWTs is time consuming for large volumetric data. An efficient parallel implementation of DWTs is essential for many time sensitive applications, such as 4DCT. METHODS: We choose Daubechies wavelet transformations as a benchmark, implementing both DWT and inverse DWT (IDWT)...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28006015/skipping-selected-steps-of-dwt-computation-in-lossless-jpeg-2000-for-improved-bitrates
#20
Roman Starosolski
In order to improve bitrates of lossless JPEG 2000, we propose to modify the discrete wavelet transform (DWT) by skipping selected steps of its computation. We employ a heuristic to construct the skipped steps DWT (SS-DWT) in an image-adaptive way and define fixed SS-DWT variants. For a large and diverse set of images, we find that SS-DWT significantly improves bitrates of non-photographic images. From a practical standpoint, the most interesting results are obtained by applying entropy estimation of coding effects for selecting among the fixed SS-DWT variants...
2016: PloS One
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