Search results for "Independent Component Analysis."
showing 10 items of 82 documents
Source separation on hyperspectral cube applied to dermatology
2010
International audience; This paper proposes a method of quantification of the components underlying the human skin that are supposed to be responsible for the effective reflectance spectrum of the skin over the visible wavelength. The method is based on independent component analysis assuming that the epidermal melanin and the dermal haemoglobin absorbance spectra are independent of each other. The method extracts the source spectra that correspond to the ideal absorbance spectra of melanin and haemoglobin. The noisy melanin spectrum is fixed using a polynomial fit and the quantifications associated with it are reestimated. The results produce feasible quantifications of each source compone…
Non-negative matrix factorization Vs. FastICA on mismatch negativity of children
2009
In this presentation two event-related potentials, mismatch negativity (MMN) and P3a, are extracted from EEG by non-negative matrix factorization (NMF) simultaneously. Typically MMN recordings show a mixture of MMN, P3a, and responses to repeated standard stimuli. NMF may release the source independence assumption and data length limitations required by Fast independent component analysis (FastICA). Thus, in theory NMF could reach better separation of the responses. In the current experiment MMN was elicited by auditory duration deviations in 102 children. NMF was performed on the time-frequency representation of the raw data to estimate sources. Support to Absence Ratio (SAR) of the MMN co…
An Efficient Method for the Visualization of Spectral Images Based on a Perception-Oriented Spectrum Segmentation
2010
We propose a new method for the visualization of spectral images. It involves a perception-based spectrum segmentation using an adaptable thresholding of the stretched CIE standard observer colormatching functions. This allows for an underlying removal of irrelevant channels, and, consequently, an alleviation of the computational burden of further processings. Principal Components Analysis is then used in each of the three segments to extract the Red, Green and Blue primaries for final visualization. A comparison framework using two different datasets shows the efficiency of the proposed method.
Applying fully tensorial ICA to fMRI data
2016
There are two aspects in functional magnetic resonance imaging (fMRI) data that make them awkward to analyse with traditional multivariate methods - high order and high dimension. The first of these refers to the tensorial nature of observations as array-valued elements instead of vectors. Although this can be circumvented by vectorizing the array, doing so simultaneously loses all the structural information in the original observations. The second aspect refers to the high dimensionality along each dimension making the concept of dimension reduction a valuable tool in the processing of fMRI data. Different methods of tensor dimension reduction are currently gaining popUlarity in literature…
Atlas construction and image analysis using statistical cardiac models
2010
International audience; This paper presents a brief overview of current trends in the construction of population and multi-modal heart atlases in our group and their application to atlas-based cardiac image analysis. The technical challenges around the construction of these atlases are organized around two main axes: groupwise image registration of anatomical, motion and fiber images and construction of statistical shape models. Application-wise, this paper focuses on the extraction of atlas-based biomarkers for the detection of local shape or motion abnormalities, addressing several cardiac applications where the extracted information is used to study and grade different pathologies. The p…
Removing ocular artifacts from magnetoencephalographic data on naturalistic reading of continuous texts
2022
Naturalistic reading paradigms and stimuli consisting of long continuous texts are essential for characterizing the cortical basis of reading. Due to the highly dynamic nature of the reading process, electrophysiological brain imaging methods with high spatial and temporal resolution, such as magnetoencephalography (MEG), are ideal for tracking them. However, as electrophysiological recordings are sensitive to electromagnetic artifacts, data recorded during naturalistic reading is confounded by ocular artifacts. In this study, we evaluate two different pipelines for removing ocular artifacts from MEG data collected during continuous, naturalistic reading, with the focus on saccades and blin…
Semi-blind Source Extraction Methods: Application to the measurement of non-contact physiological signs
2018
Non-contact physiological measurements are highlydesirable in many biomedical fields such asdiagnosis of infants, geriartic patients, patients withextreme physical trauma, and fitness and well-being.Remote photoplethysmography is increasingly beingused for non-contact measurement of heart rate fromvideos which is one of the most common biomedicalproperty required for most medical diagnosis. Oneof the common techniques for performing remotephotoplethysmography involves using Blind SourceSeparation (BSS) methods to extract the cardiacsignal from video data.In this context, the objective of this thesis is todevelop different methods in the field of extractionand separation of sources by improv…
Characterization of the seismic dynamical state through joint analysis of earthquakes and seismic noise: the example of Ischia Volcanic Island (Italy)
2020
This work is devoted to the study of both earthquakes and background seismic noise at Ischia Island (Italy) recorded pre and post the Md 4.0 earthquake occurred on 21 August 2017 (18:57 UTC). We compare and characterize noise and earthquakes in terms of Independent Component Analysis, energy and polarization properties. The earthquakes' waveforms and the background noise are decomposed into a few independent components with two main common signals peaked around 1–2 and 3–4 Hz, respectively. A slight increase of the energy of the background seismic noise is observed comparing samples recorded in 2016 and 2017, whereas no variations are detected in 2017 pre and post the main ear…
Gating Patterns to Proprioceptive Stimulation in Various Cortical Areas : An MEG Study in Children and Adults using Spatial ICA
2020
Proprioceptive paired-stimulus paradigm was used for 30 children (10–17 years) and 21 adult (25–45 years) volunteers in magnetoencephalography (MEG). Their right index finger was moved twice with 500-ms interval every 4 ± 25 s (repeated 100 times) using a pneumatic-movement actuator. Spatial-independent component analysis (ICA) was applied to identify stimulus-related components from MEG cortical responses. Clustering was used to identify spatiotemporally consistent components across subjects. We found a consistent primary response in the primary somatosensory (SI) cortex with similar gating ratios of 0.72 and 0.69 for the children and adults, respectively. Secondary responses with similar …
Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression
2021
To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscil…