Search results for " Processing"
showing 10 items of 7549 documents
Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains
2015
Purpose: Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms. Methods:…
Suppression of phase ambiguity in digital holography by using partial coherence or specimen rotation
2008
In this paper we present two approaches for extracting the surface profile as well as obtaining 3D imaging of near field objects by usage of partial coherence and digital holography. In the first approach a light source with given temporal partial coherence is used to illuminate a near field object. The reflected light is interfered with the reference source. By computing the local contrast of the generated fringes one may estimate the 3D topography and the profile of the object. This approach extracts the 3D information from a single image, and its accuracy does not depend on triangulation angle like in fringe projection methods. The second approach is tomography based. There we illuminate…
Single-trial-based Temporal Principal Component Analysis on Extracting Event-related Potentials of Interest for an Individual Subject
2021
Abstract Temporal principal component analysis (t-PCA) has been widely used to extract event-related potentials (ERPs) at the group level of multiple subjects’ ERP data. The key assumption of group t-PCA analysis is that desired ERPs of all subjects share the same waveforms (i.e., temporal components), whereas waveforms of different subjects’ ERPs can be variant in phases, peak latencies and so on, to some extent. Additionally, several PCA-extracted components coming from the same ERP dataset failed to be statistically analysed simultaneously because their polarities and amplitudes were indeterminate. To fill these gaps, a novel technique was proposed and employed to extract desired ERP fro…
Multi axis representation and Euclidean distance of muscle fatigue indexes during evoked contractions
2014
International audience; In this article, we proposed a new representation of muscular fatigue during evoked muscle contractions based on fatigue indexes such as peak to peak amplitude, RMS of the M wave, mean and median frequency and fatigue index calculated from continuous wavelet transform (I CWT). These new representations of muscle fatigue using multi axis represented and Euclidean distance give better insights on changes in physiological characteristics during muscle fatigue. This technique provides a fatigue index using several muscle characteristics. The use of other kinds of fatigue characteristics as force could also be possible.
Measuring Functional Connectivity of Human Intra-Cortex Regions with Total Correlation
2021
The economy of brain organization makes the primate brain consume less energy but efficiency. The neurons densely wired each other dependent on both anatomy structure connectivity and functional connectivity. Here, I only describe functional connectivity with Functional Magnetic Resonance Imaging (fMRI) data. Most importantly, how to quantitative measure information share or separate among functional brain regions, what’s worse, fMRI data exist large dimensional problems or “curse dimensionality” [1]. However, the multivariate total correlation method can perfectly address the above problems. In this paper, two things measured with the information-theoretic technique - total correlation [2,…
Digital Acquisition and Processing of Video Angiocardiograms
1986
Angiocardiographic diagnosis is still mainly based on the visual assessment of radiographic projection images recorded on photographic film. Considerable amounts of contrast material have to be selectively injected into the circulation in order to make the regions of diagnostic relevance visible in the superposition of the shadows of tissue and bone structures displayed in these transmission images. In addition, selective angiocardiography requires exact positioning of the catheter, a time-consuming procedure which is not without risk. The processing of the angiographie films obtained is difficult to maintain at a constant high quality level, and this introduces an disadvantageous delay bet…
Increasing Stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition
2018
Tensor decomposition has been widely employed for EEG signal processing in recent years. Constrained and regularized tensor decomposition often attains more meaningful and interpretable results. In this study, we applied sparse nonnegative CANDECOMP/PARAFAC tensor decomposition to ongoing EEG data under naturalistic music stimulus. Interesting temporal, spectral and spatial components highly related with music features were extracted. We explored the ongoing EEG decomposition results and properties in a wide range of sparsity levels, and proposed a paradigm to select reasonable sparsity regularization parameters. The stability of interesting components extraction from fourteen subjects’ dat…
A boosting approach for prostate cancer detection using multi-parametric MRI
2015
International audience; Prostate cancer has been reported as the second most frequently diagnosed men cancers in the world. In the last decades, new imaging techniques based on MRI have been developed in order to improve the diagnosis task of radiologists. In practise, diagnosis can be affected by multiple factors reducing the chance to detect potential lesions. Computer-aided detection and computer-aided diagnosis have been designed to answer to these needs and provide help to radiologists in their daily duties. In this study, we proposed an automatic method to detect prostate cancer from a per voxel manner using 3T multi-parametric Magnetic Resonance Imaging (MRI) and a gradient boosting …
Towards data-driven medical imaging using natural language processing in patients with suspected urolithiasis.
2020
Abstract Objective The majority of radiological reports are still written as free text and lack structure. Further evaluation of free-text reports is difficult to achieve without a great deal of manual effort, and is not possible in everyday clinical practice. This study aims to automatically capture clinical information and positive hit rates from narrative radiological reports of suspected urolithiasis using natural language processing (NLP). Methods Narrative reports of low dose computed tomography (CT) of the retroperitoneum from April 2016 to July 2018 (n = 1714) were analyzed using NLP. These free-text reports were automatically structured based on RadLex concepts. Manual feedback was…
Comparison of frequency domain measures based on spectral decomposition for spontaneous baroreflex sensitivity assessment after Acute Myocardial Infa…
2021
Abstract The objective of this study is to present a new method to assess in the frequency domain the directed interactions between the spontaneous variability of systolic arterial pressure (SAP) and heart period (HP) from their linear model representation, and to apply it for studying the baroreflex control of arterial pressure in healthy physiological states and after acute myocardial infarction (AMI). The method is based on pole decomposition of the model transfer function and on the following evaluation of causal measures of coupling and gain from the poles associated to low frequency (0.04−0.15 Hz) oscillatory components. It is compared with traditional non-causal approaches for the sp…