Structural and functional interplay in anxiety related classification: a graph signal processing approach

International audienceAnxiety disorders are one of the most common mental health conditions with a high rate of everyday life disability. Connectivity is steadily gaining relevance to increase our knowledge of psychiatric diseases. Graph signal processing (GSP) is a new framework to integrate structural connectivity and brain function. We propose here a graph-based analysis using GSP metrics and classification procedure, to identify anxiety biomarkers. Results suggest that the joint consideration of structure-function features improves their discriminatory accuracy, and our understanding of the pathophysiology of anxiety

A regularized nonnegative canonical polyadic decomposition algorithm with preprocessing for 3D fluorescence spectroscopy

International audienceWe consider blind source separation in chemical analysis focussing on the 3D fluorescence spectroscopy framework. We present an alternative method to process the Fluorescence Excitation-Emission Matrices (FEEM): first, a preprocessing is applied to eliminate the Raman and Rayleigh scattering peaks that clutter the FEEM. To improve its robustness versus possible improper settings, we suggest to associate the classical Zepp's method with a morphological image filtering technique. Then, in a second stage, the Canonical Polyadic (CP or Cande-comp/Parafac) decomposition of a nonnegative 3-way array has to be computed. In the fluorescence spectroscopy context, the constituent vectors of the loading matrices should be nonnegative (since standing for spectra and concentrations). Thus, we suggest a new NonNegative third order CP decomposition algorithm (NNCP) based on a non linear conjugate gradient optimisation algorithm with regularization terms and periodic restarts. Computer simulations performed on real experimental data are provided to enlighten the effectiveness and robustness of the whole processing chain and to validate the approach

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Imaging biomarker discovery in major depressive disorder with diffusion MRI multi-compartment models

International audienc

Structural and functional interplay in anxiety related classification: a graph signal processing approach

International audienceAnxiety disorders are one of the most common mental health conditions with a high rate of everyday life disability. Connectivity is steadily gaining relevance to increase our knowledge of psychiatric diseases. Graph signal processing (GSP) is a new framework to integrate structural connectivity and brain function. We propose here a graph-based analysis using GSP metrics and classification procedure, to identify anxiety biomarkers. Results suggest that the joint consideration of structure-function features improves their discriminatory accuracy, and our understanding of the pathophysiology of anxiety

A convolutional Wasserstein distance for tractography evaluation : complementary study to state-of-the-art measures

International audienceEvaluation and comparison of tractograms are crucial and open problems that need to be solved in order to evaluate the false positives rate and variability of tractography algorithms. In this context, a lot of measures have been developed and are typically used to judge the quality of a tractogram. They however do not rely on the same quantities extracted from the tractograms to compare and may thus not evaluate the same aspects of tractogram quality. To evaluate this aspect and the measures redundancy or complementarity, we perform a quantitative analysis of the most common ones, both on simulated data and in real circumstances. We also propose a new evaluation measure based on optimal transport theory. We show that, when used in conjunction, these measures can provide a more in depth comparison of tractograms and thus a more complete evaluation

A convolutional Wasserstein distance for tractography evaluation : complementary study to state-of-the-art measures

International audienceEvaluation and comparison of tractograms are crucial and open problems that need to be solved in order to evaluate the false positives rate and variability of tractography algorithms. In this context, a lot of measures have been developed and are typically used to judge the quality of a tractogram. They however do not rely on the same quantities extracted from the tractograms to compare and may thus not evaluate the same aspects of tractogram quality. To evaluate this aspect and the measures redundancy or complementarity, we perform a quantitative analysis of the most common ones, both on simulated data and in real circumstances. We also propose a new evaluation measure based on optimal transport theory. We show that, when used in conjunction, these measures can provide a more in depth comparison of tractograms and thus a more complete evaluation

Hyperoxia Challenge in Healthy and Anemic Subjects using BOLD MRI

International audienceThis study explores the brain's response to 100% oxygen inhalation in anemic subjects using BOLD MRI. Hyperoxic challenge has previously been used to identify brain regions with increased oxygen extraction fraction from inadequate perfusion. After controlling for changes in peripheral oxygen saturation, hyperoxic BOLD response was not significantly different between sickle cell disease patients, non-sickle anemic patients and healthy controls. Therefore, our results suggest that chronically anemic patients do not have increased oxygen extraction fraction from inadequate resting oxygen delivery under resting conditions

A convolutional Wasserstein distance for tractography evaluation : complementary study to state-of-the-art measures

International audienceEvaluation and comparison of tractograms are crucial and open problems that need to be solved in order to evaluate the false positives rate and variability of tractography algorithms. In this context, a lot of measures have been developed and are typically used to judge the quality of a tractogram. They however do not rely on the same quantities extracted from the tractograms to compare and may thus not evaluate the same aspects of tractogram quality. To evaluate this aspect and the measures redundancy or complementarity, we perform a quantitative analysis of the most common ones, both on simulated data and in real circumstances. We also propose a new evaluation measure based on optimal transport theory. We show that, when used in conjunction, these measures can provide a more in depth comparison of tractograms and thus a more complete evaluation

Imaging biomarker discovery in major depressive disorder with diffusion MRI multi-compartment models

International audienc