Search results for "Computer-assisted"
showing 10 items of 1186 documents
Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.
2010
The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. M…
Bandwidth Resource Management for Neural Signal Telemetry
2009
Recent advances in modern neurocomputing have shown the utmost necessity of wireless communication systems that allow real-time (RT) monitoring of neural signals meeting several requirements such as source compression and high fidelity of the received signal. Neural recordings require multielectrode probes with up to hundreds of electrodes and transmission of signals wirelessly over a limited bandwidth (BW). In this paper, a RT resource management algorithm is proposed so that adequate source compression is applied to each channel in order to fit them into the available BW. Performance of the algorithm is analyzed using dynamically changing BW and neural recordings with different neural act…
Design of Bimodal Ligands of Neurotensin Receptor 1 for Positron Emission Tomography Imaging and Fluorescence-Guided Surgery of Pancreatic Cancer
2020
International audience; Neurotensin receptor 1 (NTSR1) is overexpressed in most human pancreatic ductal adenocarcinomas. It makes it an attractive target for the development of pancreatic cancer imaging agents. In this study, we sought to develop a bimodal PET-fluorescent imaging agent capable of specifically targeting these receptors. Starting from the structure of a known NTSR1 agonist, a series of tracers was synthesized, radiometalated with gallium-68 and evaluated in vitro and in vivo, in mice bearing an AsPC-1 xenograft. PET imaging allowed us to identify the compound [ 68 Ga]Ga-NODAGA-Lys(Cy5**)-AEEAc-[Me-Arg 8 , Tle 12 ]-NT(7-13) as the one with the most promising biodistribution pr…
Polarization attraction using counter-propagating waves in optical fiber at telecommunication wavelengths
2008
International audience; In this work, we report the experimental observation of a polarization attraction process which can occur in optical fibers at telecommunication wavelengths. More precisely, we have numerically and experimentally shown that a polarization attractor, based on the injection of two counter-propagating waves around 1.55 mu m into a 2-m long high nonlinear fiber, can transform any input polarization state into a unique well-defined output polarization state.
Propagation pattern analysis during atrial fibrillation based on sparse modeling.
2012
In this study, sparse modeling is introduced for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence function, derived from fitting a multivariate autoregressive model to the observed signal using least-squares (LS) estimation. The propagation pattern analysis incorporates prior information on sparse coupling as well as the distance between the recording sites. Two optimization methods are employed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO), and a novel method named the distance-adaptive group LASSO (dLASSO). Using si…
Propagation pattern analysis during atrial fibrillation based on the adaptive group LASSO.
2012
The present study introduces sparse modeling for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence (PDC) function, derived from fitting a multivariate autoregressive model to the observed signals. A sparse optimization method is proposed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO). In simulations aLASSO was found superior to the commonly used least-squares (LS) estimation with respect to estimation performance. The normalized error between the true and estimated model parameters dropped from 0.200.04 for LS estimatio…
Combining Inter-Subject Modeling with a Subject-Based Data Transformation to Improve Affect Recognition from EEG Signals
2019
Existing correlations between features extracted from Electroencephalography (EEG) signals and emotional aspects have motivated the development of a diversity of EEG-based affect detection methods. Both intra-subject and inter-subject approaches have been used in this context. Intra-subject approaches generally suffer from the small sample problem, and require the collection of exhaustive data for each new user before the detection system is usable. On the contrary, inter-subject models do not account for the personality and physiological influence of how the individual is feeling and expressing emotions. In this paper, we analyze both modeling approaches, using three public repositories. T…
Testing the effects of pre-processing on voxel based morphometry analysis
2015
Voxel based morphometry (VBM) is an automated analysis technique which allows voxel-wise comparison of mainly grey-matter volumes between two magnetic resonance images (MRI). Two main analysis processes in VBM are possible. One is cross-sectional data analysis, where one group is compared with another to depict see the regions in the brain, which show changes in their grey-matter volume. Second is longitudinal data analysis, where MRIs, taken at different time points, are compared to see the regions in the brain that show changes in their grey matter volume for one time point with respect to another time point. Both types of analyses require pre-processing steps before performing the statis…
Optimal control design of preparation pulses for contrast optimization in MRI
2017
Abstract This work investigates the use of MRI radio-frequency (RF) pulses designed within the framework of optimal control theory for image contrast optimization. The magnetization evolution is modeled with Bloch equations, which defines a dynamic system that can be controlled via the application of the Pontryagin Maximum Principle (PMP). This framework allows the computation of optimal RF pulses that bring the magnetization to a given state to obtain the desired contrast after acquisition. Creating contrast through the optimal manipulation of Bloch equations is a new way of handling contrast in MRI, which can explore the theoretical limits of the system. Simulation experiments carried out…
DNP in MRI: an in-bore approach at 1.5 T.
2011
Abstract We have used liquid state (“Overhauser”) Dynamic Nuclear Polarization (DNP) to significantly enhance the signal to noise ratio (SNR) of Magnetic Resonance Imaging (MRI). For the first time this was achieved by hyperpolarizing directly in the MRI-scanner field of 1.5 T in continuous flow mode and immediately delivering the hyperpolarized substance to the imaging site to ensure maximum contrast between hyperpolarized sample and sample at thermal polarization. We achieve a maximum absolute signal enhancement factor of 98; while the hyperpolarized sample is transported at a flow rate of up to 30 ml/h yielding an average flow speed up to 470 mm/s over a distance of approximately 80 mm. …