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In this paper, we present three different compartmental models to model the pharmacokinetics of Indocyanine green (ICG) in cancerous tumors. We introduce a systematic and robust method to analyze ICG pharmacokinetics based on extended Kalman filtering (EKF) framework. We introduced information theoretic criteria for best compartmental model selection in terms of statistical fit. We tested our approach...
Rate filters are used to estimate the mean event rate of many biomedical signals that can be modeled as point processes. Historically these filters have been designed using principles from two distinct fields. Signal processing principles are used to optimize the filter's frequency response. Kernel estimation principles are typically used to optimize the asymptotic statistical properties. This paper...
Recent improvements in the accessibility of high-throughput genotyping have brought a great deal of attention to disease association and susceptibility studies. This paper explores possibility of applying combinatorial methods to disease susceptibility prediction. The proposed combinatorial methods as well as standard statistical methods are applied to publicly available genotype data on Crohn's disease...
Based on Poisson variability, the strength of cross-correlation of two spike trains was quantified by a cross-correlation index (CCI). Discriminant analysis with CCI was used to quantify the contribution of cross-correlation in stimulus feature discrimination in an ensemble of retinal ganglion cells. Compared with simulated Poisson cell pair, it was found that cross-correlation carried useful information...
To explore the characteristics of thermo-source of breast tumors on thermal texture maps. Compared with the histological results, thermo-source characteristics on TTM in 106 cases with breast mass, who would undergo breast surgery, were analyzed according to the parameters such as the depth, morphology, structure, and temperatures of abnormal heat foci in order to find the differences between benign...
The identification of protein-protein interactions along with their spatial and temporal localization is vital data for assigning functional information to proteins. Historically, these data sets obtained from fluorescence microscopy, have been analyzed manually, a process that is both time consuming and tedious. The development of an automated system that can measure the location dynamics of the...
A novel parametric method, based on the non-Gaussian AR model, is proposed for the partition of non-stationary EEG data into a finite set of third-order stationary segments. With the assumption of piecewise third-order stationarity of the signal, a series of parametric bispectral estimations of the non-stationary EEG data can be performed so as to describe the time-varying non-Gaussian nonlinear characteristics...
This paper describes a three-stage system for the detection of neonatal seizures. The first stage detects 5-s seizure segments using signal processing and pattern recognition techniques. In the second stage, the seizure segments overlapping with artifactual segments are marked for post-processing using rules. Rules add intelligence to the spatio-temporal clustering in the third stage, by incorporating...
Visualization plays a central role in the presentation and interpretation of medical image data. Radiologists and surgeons must be able to accurately interpret the data for diagnosis and surgical planning. The data obtained from many imaging systems can contain functional as well as structural information producing 4D datasets. In some cases this can extend to 5D when the image provides spectral information...
1H magnetic resonance spectra (MRS) of biofluids contain rich biochemical information about the metabolic status of an organism. Through the application of pattern recognition and classification algorithms, such data have been shown to provide information for disease diagnosis as well as the effects of potential therapeutics. In this paper we describe a novel approach, using non-negative matrix factorization...
The gating of ion channels has widely been modeled by assuming the transition between open and closed states is a memoryless process. Nevertheless, the statistical analysis of an ionic current signal recorded from voltage dependence K+ single channel is presented. Calculating the sample autocorrelation function of the ionic current based on the digitized signals, rather than the sequence of open and...
This paper aimed at developing an index, called sleep index, to assess the quality of sleep in normal and obstructive sleep apnea (OSA) subjects. The sleep index was designed to be directly proportional to the summation of product of the number seconds spent in each stage of sleep and the selected weighting coefficient of each sleep stage. It was also inversely proportional to the product of total...
In patients suffering from various sleep disorders and some elderly patients, sleep is disturbed with frequent but brief arousal. These events do not cause behavioral awakening, but can lead to excessive day time sleepiness. These brief arousals or microarousals (MAs) can be identified on a standard polysomnogram as a transient abrupt change of frequency, typically in the alpha and extended beta (16-40...
An effective and clinically relevant parameter for differentiating ischemic optic neuropathy (ION) and optic neuritis (ON) patients using the visual evoked potentials (VEPs) has been identified. In this study, statistical analysis has been carried out on time domain parameters of the VEP waveforms recorded for ION (17 patients) and ON (35 patients) groups. The ratio of the amplitude of P100 component...
This paper aims to search parameters characterizing the MTF curve of retina-brain system of the human eye for distinguishing eye disease use. Suppose the MTF can be expressed by (for symmetric MTF) or (for asymmetric MTF). Let y = ln(MTF), x = lnf, the above formula can be transformed into y = k1x+... (for symmetric MTF) or y = k1'x+...(for asymmetric MTF ). Parameters kis( or ki's) are determined...
This paper presents an approach for automatically delineating the borders of human primary visual cortex and finding ridges of maximal response due to static phase-encoding stimuli on fMRI t-statistical maps via dynamic programming. The sensitivity of such an approach to the choice of initial starting and ending points and the identification of the ridge path over a wide response region are addressed...
In fMRI dataset, the population of actived voxels is always much less than the total population of the voxels, and that produced an ill-balanced dataset. Some methods, such as limiting the analysis to the gray matter voxels where the BOLD signal is expected and removing the voxels that is absolutely non-actived based on statistical criteria, have been used to treat the ill-balanced dataset. In this...
This paper presents an application of fractal analysis to characterization of global cerebral blood flow and immunohistopathology for ischemic stroke research on animal experiments. A brain's vasculature has features of a branching tree and can be modeled as a fractal system. Fractal analysis can be then employed to assess cerebral blood flow and immuno-positives on a whole brain section. Fractal...
We proposed an efficient method for classification of diffused liver diseases based on Gabor wavelet. It is well known that Gabor wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction and presentation. This property has been explored here as the proposed method outperforms the classification rate obtained by using dyadic wavelets...
This paper presents a method to segment brain tissue from T1-weighted magnetic resonance (MR) images. A modified BayesShrink method is utilized to filter the image in wavelet transform domain before segmentation, where the shrinkage strength is automatically adjusted with respect to noise level. Then the fuzzy c-means clustering is applied to segment brain tissue into cerebrospinal fluid, gray matter...
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