Search results for "recognition"
showing 10 items of 3607 documents
Fusingin vivoandex vivoNMR sources of information for brain tumor classification
2011
In this study we classify short echo-time brain magnetic resonance spectroscopic imaging (MRSI) data by applying a model-based canonical correlation analyses algorithm and by using, as prior knowledge, multimodal sources of information coming from high-resolution magic angle spinning (HR-MAS), MRSI and magnetic resonance imaging. The potential and limitations of fusing in vivo and ex vivo nuclear magnetic resonance sources to detect brain tumors is investigated. We present various modalities for multimodal data fusion, study the effect and the impact of using multimodal information for classifying MRSI brain glial tumors data and analyze which parameters influence the classification results…
Exploring Frequency-dependent Brain Networks from ongoing EEG using Spatial ICA during music listening
2019
AbstractRecently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during free-listening to music. We used a data-driven method t…
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:…
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…
Information-theoretic assessment of cardiovascular-brain networks during sleep
2015
This study was aimed at detecting the structure of the physiological network underlying the regulation of the cardiovascular and brain systems during normal sleep. To this end, we measured from the polysomnographic recordings of 10 healthy subjects the normalized spectral power of heart rate variability in the high frequency band (HF) and the EEG power in the δ, θ, α, σ, and β bands. Then, the causal statistical dependencies within and between these six time series were assessed in terms of internal information (conditional self entropy, CSE) and information transfer (transfer entropy, TE) computed via a linear method exploiting multiple regression models and a nonlinear method combining ne…
An automatic method for metabolic evaluation of gamma knife treatments
2015
Lesion volume delineation of Positron Emission Tomography images is challenging because of the low spatial resolution and high noise level. Aim of this work is the development of an operator independent segmentation method of metabolic images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Twenty-four cerebral tumors are segmented to evaluate the functional follow-up after Gamma Knife radiotherapy treatment. Experimental results show that the segmentation algorithm is accurate and has real-time performance. In addition, it can reflect metabolic changes useful to evaluate radiotherapy response in treated patients.
Truncation effects on muscular fatigue indexes based on M waves analysis
2012
International audience; In this paper, we investigate muscular fatigue. We propose a new fatigue index based on the continuous wavelet transform (CWT) and compare it with the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles (electromyogram) acquired during an electrically stimulated contraction (ES). The stimulator and electromyogram system, which were presented in a previous work, allows real-time analysis. The extracted fatigue parameters are compared between each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustness of the index obtained using CWT.
SIFT Texture Description for Understanding Breast Ultrasound Images
2014
Texture is a powerful cue for describing structures that show a high degree of similarity in their image intensity patterns. This paper describes the use of Self-Invariant Feature Transform (SIFT), both as low-level and high-level descriptors, applied to differentiate the tissues present in breast US images. For the low-level texture descriptors case, SIFT descriptors are extracted from a regular grid. The high-level texture descriptor is build as a Bag-of-Features (BoF) of SIFT descriptors. Experimental results are provided showing the validity of the proposed approach for describing the tissues in breast US images.
Recognition of Cardiac Arrhythmia by Means of Beat Clustering on ECG-Holter Recordings
2012
The follow-up of some cardiac diseases may be achieved by ECG-holter record analysis. A heartbeat clustering method can be used to reduce the usually high computational cost of such Holter analysis. This study describes a method aimed at cardiac arrhythmia recognition based on this approach, by means of unsupervised inspection of morphologically similar heartbeat groups. Singular Value Decomposition (SVD) is used as the feature selection method since the complexity increases exponentially with the number of features. A modification of the k-means algorithm was developed for centroid computation, taking into account heartbeat length changes. Experimental set consisted of ECG records from the…
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.