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Tracking of lung tumors is imperative for improved radiotherapy treatment. However, the motion of the thoracic organs makes it a complicated task. 4D CT images acquired prior to treatment provide valuable information regarding the motion of organs and tumor, since it is manually annotated. In order to track tumors using treatment-day X-ray images (kV images), we need to find the correspondence with...
In this paper, we investigate the incorporation of independent component analysis (ICA) with Q-ball imaging (QBI) to extract information on the diffusion orientation distribution function (ODF) from an inner voxel. In our approach, the ICA algorithm is applied to a mixture of ODFs which are constructed based on the analytical QBI solution. The numerical simulation results demonstrate that the proposed...
The Basal Ganglia (BG) are a group of nuclei, in the brain of mammalians and other vertebrates, strongly connected with the cerebral cortex, thalamus and other brain areas. The BG are associated with several brain functions including learning and motor control. When there is cortical activation, there is a strong synchronization between BG and cortex, i.e. when a given task is being executed or in...
Mass spectrometry-based metabolomics is getting mature and playing an ever important role in the systematic understanding of biological process in conjunction with other members of “-omics” family. However, the identification of metabolites in untargeted metabolomics profiling remains a challenge. In this paper, we propose a support vector machine (SVM)-based spectral matching algorithm to combine...
The default mode network (DMN) has been previously identified as a set of brain regions activated during internally directed cognition. The objective of this study was to investigate patterns of brain activation during switching between a goal-directed task and a rest period obtained from clinical functional magnetic resonance imaging (fMRI) paradigms in complex partial seizures (CPS) and age-matched...
A new class of wavelet functions called data-based autocorrelation wavelets is developed for analyzing Magnetic Resonance Spectroscopic (MRS) signals by means of the continuous wavelet transform (CWT), instead of the traditional wavelet like Morlet wavelet. These new wavelets are derived from the normalized autocorrelation function from metabolite data and then used for detecting the presence of a...
This work proposes a clustering technique to analyze evoked potential signals. The proposed method uses an orthogonal subspace model to enhance the single-trial signals of a session and simultaneously a subspace measure to group the trials into clusters. The ensemble averages of the signals of the different clusters are compared with ensemble averages of visually selected trials which are free of...
Time-frequency representations (TFR) are one of the most popular characterization methods for non-stationary biosignals. Despite of their potential advantages, these representations suffer of large quantity of redundant and irrelevant data which makes them difficult to use for classification purposes. In this work, a methodology for reduction of irrelevant and redundant data is explored. This approach...
A new method for the quantification of amplitude variations in biomedical signals through moving approximate entropy is presented. Unlike the usual method to calculate the approximate entropy (ApEn), in which the tolerance value (r) varies based on the standard deviation of each moving window, in this work ApEn has been computed using a fixed value of r. We called this method, moving approximate entropy...
Sleep is an active and regulated process with restorative functions for physical and mental conditions. Based on recordings of brain waves and the analysis of characteristic patterns and waveforms it is possible to distinguish wakefulness and five sleep stages. Sleep and the sleep stages modulate autonomous nervous system functions such as body temperature, respiration, blood pressure, and heart rate...
The paper aims to investigate how humans deal with unstable objects under the possibility of choosing different strategy of interaction. The presented task consisted in balancing a 1 degree of freedom (DoF) elastic inverted pendulum by means of 2 DoF of the wrist (fexion/extension and pronation/supination). The pendulum was simulated using a virtual environment and the haptic feedback was generated...
The activation of neural ensembles in the cortex is correlated with behavioral states and a change in neuronal functional connectivity patterns is expected. In this paper, we investigate this dynamic nature of functional connectivity in the cortex. Because of the time scale of behavior, a robust method with limited sample size is desirable. In light of this, we utilize mean square contingency (MSC)...
The aim of this work is to understand how the variations in grayscale values of B-mode ultrasound (US) images can be used as an approach for non-invasive temperature estimation. In order to obtain real-time monitoring of HIFU treatment, an US imaging system and HIFU were synchronized. Images were acquired using an electronic convex imaging probe. An 8% BSA tissue-mimicking polyacrylamide gel was used...
Miniaturizing area and power consumptions of cochlear prosthetic devices is strongly required for full implantation. In this paper, several speech encoding strategies are studied and compared in order to find a compact speech processor that allows for full implantation and is able to convey both time and frequency components of the incoming speech to a set of electrical pulse stimuli. The study covers...
Modeling heartbeat variability remains a challenging signal-processing goal in the presence of highly non-stationary cardiovascular control dynamics. We propose a novel differential autoregressive modeling approach within a point process probability framework for analyzing R-R interval and blood pressure variations. We apply the proposed model to both synthetic and experimental heartbeat intervals...
In this paper, we proposed a tunnel morph model for bio-signal waveform in measuring their similarity. Firstly, the formal specifications of bio-signal waveforms are given. And then, a series of model establishing related definitions are presented. These definitions contain waveform segmentation; waveforms distance measurement, and tunnel width computation. Moreover, on the base of the model, a similarity...
This paper uses an entropy based metric to study the somatosensory evoked potential (SEP) in rodents afflicted with focal demyelination spinal cord injury (SCI). It has been shown that amplitude characteristics of the SEP signal are a strong indicator of the integrity of the spinal cord sensory pathways. Compared to conventional correlation based metrics, the metric used in this paper exploits the...
Abnormal physiological networks of brain areas in disease can be identified by applying specialized multivariate computational algorithms based on principal component analysis to functional image data. Here we demonstrate the reproducibility of network patterns derived using positron emission tomography (PET) data in independent populations of parkinsonian patients for a large, clinically validated...
In this work, the anterior-posterior displacement of the center of pressure was modeled as a fractional Brownian motion to analyze the effect of fatigue of plantar flexor muscles by isometric contraction. A sample of 17 young, healthy adults was evaluated by stabilometric test, 2 min before and after a plantar flexion, sustained until exhaustion. For each test, the model was applied to four consecutive...
Analysis of Event Related Potentials (ERPs) produced by brain activities can provide insight into the timing of underlying brain function. ERPs can be classified by their time/frequency characteristics and spatial location on the scalp. Traditionally, ERPs are manually located by temporally and spatially averaged EEG signals. This process is error prone and sensitive to a priori assumptions. Our proposed...
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