FDG-PET-based brain network analysis: a brief review of metabolic connectivity.

Background: Over the past decades, the analysis metabolic connectivity patterns has received significant attention in exploring the underlying mechanism of human behaviors, and the neural underpinnings of brain neurological disorders. Brain network can be considered a powerful tool and play an important role in the analysis and understanding of brain metabolic patterns. With the advantages and emergence of metabolic-based network analysis, this study aims to systematically review how brain properties, under various conditions, can be studied using Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) images and graph theory, as well as applications of this approach.

Long-term remission following esketamine nasal spray sessions in a patient with severe and highly treatment-resistant depression: a single-case report.

About 30% of patients with major depressive disorder have treatment-resistant depression (TRD). Recently, intranasal esketamine was approved as a treatment option after the failure of two antidepressant trials. We report a patient with multiresistant depression that was successfully and safely treated with esketamine nasal spray.

Correlation between fluorodeoxyglucose positron emission tomography brain hypometabolism and posttraumatic stress disorder symptoms in temporal lobe epilepsy.

The relationship between posttraumatic stress disorder (PTSD) and focal epilepsy is poorly understood. It has been hypothesized that there is a complex and reciprocal potential reinforcement of the symptoms of each condition. In this study, we investigated whether there are PTSD-specific brain changes in temporal lobe epilepsy (TLE).

Molecular imaging in Parkinsonism: The essential for clinical practice and future perspectives.

Nuclear medicine with positron emission tomography (PET) and single photon emission computed tomography (SPECT) develops powerful tools in molecular imaging to help clinicians in the challenging diagnosis of parkinsonism. These techniques can provide biomarkers for neurodegenerative parkinsonism and to distinguish Parkinson disease (PD) from atypical parkinsonism. This review summarizes the main SPECT and PET contributions to the diagnosis of parkinsonism.

Single Photon Emission Computed Tomography/Positron Emission Tomography Molecular Imaging for Parkinsonism: A Fast-Developing Field.

The early differential diagnosis of Parkinson disease and atypical parkinsonism is a major challenge. The use of single photon emission computed tomography (SPECT)/positron emission tomography (PET) molecular imaging to investigate parkinsonism is a fast-developing field. Imaging biomarker research may potentially lead to more accurate disease detection, enabling earlier diagnosis and treatment.

Efficient time of arrival estimation in the presence of multipath propagation.

Most of acoustical experiments face multipath propagation issues. The times of arrival of different ray paths on a sensor can be very close. To estimate them, high resolution algorithms have been developed.

Deconvolution of several versions of a scene perturbed by different defocus blurs: influence of kernel diameters on restoration quality and on robustness to kernel estimation.

It has been shown many times that using different versions of a scene perturbed with different blurs improved the quality of a restored image compared with using a single blurred image. We focus on large defocus blurs, and we first consider a case in which two different blurring kernels are used. We analyze with numerical simulations the influence of the relative diameter of both kernels on the quality of restoration.

Minimum description length synthetic aperture radar image segmentation.

We present a new minimum description length (MDL) approach based on a deformable partition--a polygonal grid--for automatic segmentation of a speckled image composed of several homogeneous regions. The image segmentation thus consists in the estimation of the polygonal grid, or, more precisely, its number of regions, its number of nodes and the location of its nodes. These estimations are performed by minimizing a unique MDL criterion which takes into account the probabilistic properties of speckle fluctuations and a measure of the stochastic complexity of the polygonal grid.

Information-theory-based snake adapted to inhomogeneous intensity variations.

A new snake-based segmentation technique of a single object (simply connected) in the presence of inhomogeneous Gaussian noise is proposed, in which the mean in each region is modeled as a polynomial function of the coordinates and which is thus adapted to inhomogeneous illumination. It is shown that the minimization of the stochastic complexity of the image, which can be implemented efficiently, allows one to automatically estimate not only the number and the position of the nodes of the polygonal contour used to describe the object but also the degree of the polynomials that model the variations of the mean.

Visibility interference fringes optimization on a single beam in the case of partially polarized and partially coherent light.

We analyze the optimal visibility one can obtain in interference experiments with partially polarized light when one acts on only one of the two interfering beams. This is a practical situation that can appear when one does not want to modify or attenuate one of the beams, such as in homodyne detection. It is shown that the optimal configuration usually does not correspond to light with the same degrees of polarization for the two interfering beams.

Estimation precision of the degree of polarization from a single speckle intensity image.

We address the problem of the estimation of the degree of polarization from a single intensity image. For that purpose, one considers the case of coherent active imagery that leads to speckle fluctuations and assumes that the measured intensity image corresponds to a fully developed speckle for each polarized component of the electric field. In particular, we determine the Cramer-Rao bound of the degree of polarization estimation and propose to illustrate this result by analyzing the variance of different simple estimators.

Cramer-Rao lower bound for the estimation of the degree of polarization in active coherent imagery at low photon levels.

The degree of polarization (DOP) is an important tool in many optical measurement and imaging applications. We address the problem of its estimation in images that are perturbed with both speckle and photon noise, by determining the Cramer-Rao lower bounds (CRLBs) when the illuminated materials are purely depolarizing. We demonstrate that the CRLBs are simply the sum of the CRLBs due to speckle noise and Poisson noise.

Shannon entropy of partially polarized and partially coherent light with Gaussian fluctuations.

We propose to analyze Shannon entropy properties of partially coherent and partially polarized light with Gaussian probability distributions. It is shown that the Shannon entropy is a sum of simple functions of the intensity, of the degrees of polarization, and of the intrinsic degrees of coherence that have been recently introduced. This analysis clearly demonstrates the contribution of partial polarization and of partial coherence to the characterization of disorder of the light provided by the Shannon entropy, which is a standard measure of randomness.

Linear relations of partially polarized and coherent electromagnetic fields.

We show that having a Wolf degree of coherence of unit modulus or having intrinsic degrees of coherence of unit modulus imply different relations between the electric fields of the light. The mean square meaning of such relations is discussed. On the one hand, we demonstrate that if the intrinsic degrees of coherence are equal to 1, then there is a linear relation between the electrical fields.

Nonparametric statistical snake based on the minimum stochastic complexity.

We propose a nonparametric statistical snake technique that is based on the minimization of the stochastic complexity (minimum description length principle). The probability distributions of the gray levels in the different regions of the image are described with step functions with parameters that are estimated. The segmentation is thus obtained by minimizing a criterion that does not include any parameter to be tuned by the user.

Some practical issues in anomaly detection and exploitation of regions of interest in hyperspectral images.

We address method of detection of anomalies in hyperspectral images that consists in performing the detection when the spectral signatures of the targets are unknown. We show that, in real hyperspectral images, use of the full spectral resolution may not be necessary for detection but that the correlation properties of spectral fluctuations have to be taken into account in the design of the detection algorithm. Anomaly detectors are useful for detecting regions of interest (ROIs), but, as they are prone to false alarms, one must analyze the ROIs obtained further to decide whether they correspond to real targets.

Coherence polarization filtering and relation with intrinsic degrees of coherence.

It is demonstrated for stationary fields that when the polarization state of the electric field can be modified arbitrarily the maximal value of the modulus of the degree of coherence proposed by Wolf [Phys. Lett. A312, 263 (2003)] is equal to the largest intrinsic degree of coherence.

Kullback relative entropy and characterization of partially polarized optical waves.

Different properties of partially polarized light are discussed using the Kullback relative entropy, which provides a physically meaningful measure of proximity between probability density functions (PDFs). For optical waves with a Gaussian PDF, the standard degree of polarization is a simple function of the Kullback relative entropy between the considered optical light and a totally depolarized light of the same intensity. It is shown that the Kullback relative entropies between different PDFs allow one to define other properties such as a degree of anisotropy and a degree of non-Gaussianity.

Invariant polarimetric contrast parameters of light with Gaussian fluctuations in three dimensions.

We propose a rigorous definition of the minimal set of parameters that characterize the difference between two partially polarized states of light whose electric fields vary in three dimensions with Gaussian fluctuations. Although two such states are a priori defined by eighteen parameters, we demonstrate that the performance of processing tasks such as detection, localization, or segmentation of spatial or temporal polarization variations is uniquely determined by three scalar functions of these parameters. These functions define a "polarimetric contrast" that simplifies the analysis and the specification of processing techniques on polarimetric signals and images.

Mutual information-based degrees of coherence of partially polarized light with Gaussian fluctuations.

The spatiotemporal coherence properties of partially polarized light with Gaussian probability distributions are analyzed using the mutual information that is a standard measure of statistical dependence. This approach leads to intrinsic degrees of coherence that have powerful invariance properties and that provide new information in comparison with other recently introduced degrees of coherence.

Cramer-Rao lower bounds on the estimation of the degree of polarization in coherent imaging systems.

We analyze the estimation precision of the parameter of the orthogonal state contrast image (OSCI) under coherent illumination. This parameter represents the degree of polarization of the light if the materials that compose the scene are purely depolarizing. Two different estimation modes are considered, depending on the uniformity of the illumination of the scene.

Minimal stochastic complexity snake-based technique adapted to an unknown noise model.

We propose a polygonal snake segmentation technique adapted to objects that can be composed of several regions with gray-level fluctuations described by a priori unknown probability laws. This approach is based on a histogram equalization and on the minimization of a criterion without parameter to be tuned by the user. We demonstrate the efficiency of this approach, which has low computational cost, on synthetic and real images perturbed by different types of optical noise.

Polarization degree of optical waves with non-Gaussian probability density functions: Kullback relative entropy-based approach.

The definition of degree of polarization for non-Gaussian partially polarized light is analyzed. A general framework based on the Kullback relative entropy is developed, and properties that enlighten the physical meaning of the degree of polarization are established. In particular, it is shown how the degree of polarization is related to the measure of proximity between probability density functions and to the measure of disorder provided by the Shannon entropy.

Estimation of the degree of polarization in active coherent imagery by using the natural representation.

We address the problem of degree of polarization estimation in polarization diversity images. We consider active imaging techniques with laser illumination, which have the appealing feature of revealing contrasts that do not appear in conventional intensity images. These techniques provide two images of the same scene that are perturbed with speckle noise.

Entropy of partially polarized light and application to statistical processing techniques.

We have analyzed entropy properties of coherent and partially polarized light in an arbitrary number of spatial dimensions. We show that for Gaussian fields, the Shannon entropy is a simple function of the intensity and of the Barakat degree of polarization. In particular, we provide a probabilistic interpretation of this definition of the degree of polarization.