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Wavelet analysis

Giuliano Grossi, Raffaella Lanzarotti, Jianyi Lin
In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error...
2017: PloS One
Jiachao Zhang, Keigo Hirakawa
This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. Quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details such as edge and textures...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Abhijit Bhattacharyya, Ram Bilas Pachori
OBJECTIVE: This paper investigates the multivariate oscillatory nature of electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure detection. METHODS: The empirical wavelet transform (EWT) has been explored for the multivariate signals in order to determine the joint instantaneous amplitudes and frequencies in signal adaptive frequency scales. The proposed multivariate extension of EWT has been studied on multivariate multi-component synthetic signal, as well as on multivariate EEG signals of CHB-MIT scalp EEG database...
January 9, 2017: IEEE Transactions on Bio-medical Engineering
V V Aleksandrin, A A Kubatiev
Hypovolemic shock leads to severe cerebral ischemia and increases spectral amplitudes of cerebral blood flow oscillations in respiratory frequency range.
January 2017: Bulletin of Experimental Biology and Medicine
YoungJae Song, Francisco Sepulveda
OBJECTIVE: Self-paced EEG-based BCIs (SP-BCIs) have traditionally been avoided due to two sources of uncertainty: (1) precisely when an intentional command is sent by the brain, i.e., the command onset detection problem, and (2) how different the intentional command is when compared to non-specific (or idle) states. Performance evaluation is also a problem and there are no suitable standard metrics available. In this paper we attempted to tackle these issues. APPROACH: Self-paced covert sound-production cognitive tasks (i...
February 2017: Journal of Neural Engineering
Liwei Xu, Bitian Wang, Gongcheng Xu, Wei Wang, Zhian Liu, Zengyong Li
Noninvasive and accurate assessment of driving fatigue in relation to brain activity during long-term driving can contribute to traffic safety and accident prevention. This study evaluated functional connectivity (FC) in relevant brain regions. Synergistic mechanisms in different brain regions were detected by a novel simulator, which combined semi-immersive virtual reality technology and functional near-infrared spectroscopy. Each subject was instructed to complete driving tasks coupled with a mental calculation task...
January 10, 2017: Neuroscience Letters
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
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 ..
Matthew M Mallette, Gary J Hodges, Gregory W McGarr, David A Gabriel, Stephen S Cheung
Previous work has demonstrated that spectral analysis is a useful tool to non-invasively ascertain the mechanisms of control of the cutaneous circulation. The majority of work using spectral analysis has focused on local control mechanisms, with none examining reflex control. Skin blood flow was analysed using spectral analysis on the dorsal aspect of the forearm of 7 males and 7 females during passive heat stress, with mean forearm and local temperature at the site of measurement maintained at thermoneutral (33°C) to minimize the effect of local control mechanisms...
January 5, 2017: Microvascular Research
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
Yuqian Li, Xin Liu, Feng Wei, Diana M Sima, Sofie Van Cauter, Uwe Himmelreich, Yiming Pi, Guang Hu, Yi Yao, Sabine Van Huffel
Proton Magnetic Resonance Spectroscopic Imaging ((1)H MRSI) has shown great potential in tumor diagnosis since it provides localized biochemical information discriminating different tissue types, though it typically has low spatial resolution. Magnetic Resonance Imaging (MRI) is widely used in tumor diagnosis as an in vivo tool due to its high resolution and excellent soft tissue discrimination. This paper presents an advanced data fusion scheme for brain tumor diagnosis using both MRSI and MRI data to improve the tumor differentiation accuracy of MRSI alone...
December 27, 2016: Computers in Biology and Medicine
Baolin Zhang, Xinglin Tong, Pan Hu, Qian Guo, Zhiyuan Zheng, Chaoran Zhou
Optical fiber Fabry-Perot (F-P) sensors have been used in various on-line monitoring of physical parameters such as acoustics, temperature and pressure. In this paper, a wavelet phase extracting demodulation algorithm for optical fiber F-P sensing is first proposed. In application of this demodulation algorithm, search range of scale factor is determined by estimated cavity length which is obtained by fast Fourier transform (FFT) algorithm. Phase information of each point on the optical interference spectrum can be directly extracted through the continuous complex wavelet transform without de-noising...
December 26, 2016: Optics Express
Yao-Ran Huo, Hong-Jie He, Fan Chen, Heng-Ming Tai
The existing adaptive single-pixel imaging methods suffer from a waste of sampling resources. The sampling resources are not used adequately for superior localization of significant coefficients and reconstruction. In this paper, an adaptive single-pixel imaging method via the guided coefficients in the Haar wavelet tree is proposed. The goal is to achieve high quality imaging with less sampling resources. The guided coefficients are selected from the unsampled coefficients by a proposed same-scale prediction method based on the sampled coefficients...
January 1, 2017: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
Mohammad Ali Parto Dezfouli, Mohsen Parto Dezfouli, Alireza Ahmadian, Alejandro F Frangi, Melika Esmaeili Rad, Hamidreza Saligheh Rad
MRS is an analytical approach used for both quantitative and qualitative analysis of human body metabolites. The accurate and robust quantification capability of proton MRS ((1) H-MRS) enables the accurate estimation of living tissue metabolite concentrations. However, such methods can be efficiently employed for quantification of metabolite concentrations only if the overlapping nature of metabolites, existing static field inhomogeneity and low signal-to-noise ratio (SNR) are taken into consideration. Representation of (1) H-MRS signals in the time-frequency domain enables us to handle the baseline and noise better...
January 4, 2017: NMR in Biomedicine
P Hu, J Wang, H Zhong, Z Zhou, L Shen, W Hu, Z Zhang
PURPOSE: To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. METHODS: 40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs...
June 2016: Medical Physics
Lingguo Bu, Ming Zhang, Jianfeng Li, Fangyi Li, Heshan Liu, Zengyong Li
PURPOSE: To reveal the physiological mechanism of the decline in cognitive function after sleep deprivation, a within-subject study was performed to assess sleep deprivation effects on phase synchronization, as revealed by wavelet phase coherence (WPCO) analysis of prefrontal tissue oxyhemoglobin signals. MATERIALS AND METHODS: Twenty subjects (10 male and 10 female, 25.5 ± 3.5 years old) were recruited to participate in two tests: one without sleep deprivation (group A) and the other with 24 h of sleep deprivation (group B)...
2017: PloS One
Xiaowei Zhuang, Zhengshi Yang, Tim Curran, Richard Byrd, Rajesh Nandy, Dietmar Cordes
Canonical correlation analysis (CCA) has been used in functional Magnetic Resonance Imaging (fMRI) for improved detection of activation by incorporating time series from multiple voxels in a local neighborhood. To improve the specificity of local CCA methods, spatial constraints were previously proposed. In this study, constraints are generalized by introducing a family model of spatial constraints for CCA to further increase both sensitivity and specificity in fMRI activation detection. The proposed locally-constrained CCA (cCCA) model is formulated in terms of a multivariate constrained optimization problem and solved efficiently with numerical optimization techniques...
December 29, 2016: NeuroImage
Omkar Singh, Ramesh Kumar Sunkaria
This paper presents new methods for baseline wander correction and powerline interference reduction in electrocardiogram (ECG) signals using empirical wavelet transform (EWT). During data acquisition of ECG signal, various noise sources such as powerline interference, baseline wander and muscle artifacts contaminate the information bearing ECG signal. For better analysis and interpretation, the ECG signal must be free of noise. In the present work, a new approach is used to filter baseline wander and power line interference from the ECG signal...
December 29, 2016: Australasian Physical & Engineering Sciences in Medicine
Satishkumar S Chavan, Abhishek Mahajan, Sanjay N Talbar, Subhash Desai, Meenakshi Thakur, Anil D'cruz
Neurocysticercosis (NCC) is a parasite infection caused by the tapeworm Taenia solium in its larvae stage which affects the central nervous system of the human body (a definite host). It results in the formation of multiple lesions in the brain at different locations during its various stages. During diagnosis of such symptomatic patients, these lesions can be better visualized using a feature based fusion of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This paper presents a novel approach to Multimodality Medical Image Fusion (MMIF) used for the analysis of the lesions for the diagnostic purpose and post treatment review of NCC...
December 18, 2016: Computers in Biology and Medicine
Taro Kamigaki, Liling Chaw, Alvin G Tan, Raita Tamaki, Portia P Alday, Jenaline B Javier, Remigio M Olveda, Hitoshi Oshitani, Veronica L Tallo
INTRODUCTION: The seasonality of influenza and respiratory syncytial virus (RSV) is well known, and many analyses have been conducted in temperate countries; however, this is still not well understood in tropical countries. Previous studies suggest that climate factors are involved in the seasonality of these viruses. However, the extent of the effect of each climate variable is yet to be defined. MATERIALS AND METHODS: We investigated the pattern of seasonality and the effect of climate variables on influenza and RSV at three sites of different latitudes: the Eastern Visayas region and Baguio City in the Philippines, and Okinawa Prefecture in Japan...
2016: PloS One
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