1,721,211 research outputs found
Progress in neuro-imaging of brain tumors
No full textPURPOSE OF REVIEW: Magnetic resonance imaging (MRI) is routinely employed in the diagnosis and clinical management of brain tumors. This review provides an overview of the advancements in the field of MRI, with a particular focus on the quantitative assessment by advanced physiological magnetic resonance techniques in light of the new molecular classification of brain tumor. RECENT FINDINGS: Understanding how molecular phenotypes of brain tumors are reflected in noninvasive imaging is the goal of radiogenomics, which aims at determining the association between imaging features and molecular markers in neuro-oncology. Advanced MRI techniques such as diffusion magnetic resonance imaging and perfusion-weighted imaging add important structural, hemodynamic, and physiological information for tumor diagnosis and classification, as well as to stratify tumor response. Magnetic resonance spectroscopy is able to depict with unprecedented accuracy metabolic biomarkers, which are relevant for molecular subtyping. Ultra-high-field imaging enhances anatomical detail and enables to explore new horizon in tumor imaging. SUMMARY: The noninvasive MRI-based assessment of tumor malignancy and molecular status may offer the opportunity to predict prognosis and to select patients who may be candidates for individualized targeted therapies, providing more sensitive tools for their follow-up
Approximated Iterative QLP for Change Detection in Hyperspectral Images
No full textWe propose a matrix factorization algorithm based on the iterative Stewart’s QLP decomposition. In particular, provided a given threshold, only an automatically selected subspace is used to approximate the original dense matrix. The algorithm is validated on the change detection task for Hyperspectral Images (HSI). The extraction of information from HSI is an important field of research relevant to many applications. In the aerospace sector, for example, it is useful to monitor changes of the Earth surface, or to find salient information from urban geo-spatial data. Therefore, low rank approximation techniques play a fundamental role
Empirical density estimation based on spline quasi-interpolation with applications to copulas clustering modeling
Full text linkDensity estimation is a fundamental technique employed in various fields to model and to understand the underlying distribution of data. The primary objective of density estimation is to estimate the probability density function of a random variable. This process is particularly valuable when dealing with univariate or multivariate data and is essential for tasks such as clustering, anomaly detection, and generative modeling. In this paper we propose the monovariate approximation of the density using spline quasi interpolation and we apply it in the context of clustering modeling. The used clustering technique is based on the construction of suitable multivariate distributions which rely on the estimation of the monovariate empirical densities (marginals). Such an approximation is achieved by using the proposed spline quasi-interpolation, while the joint distributions to model the sought clustering partition is constructed with the use of copulas functions. In particular, since copulas can capture the dependence between the features of the data independently from the marginal distributions, a finite mixture copula model is proposed. The presented algorithm is validated on artificial and real datasets
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Splines Parameterization of Planar Domains by Physics-Informed Neural Networks
Full text linkThe generation of structured grids on bounded domains is a crucial issue in the development of numerical models for solving differential problems. In particular, the representation of the given computational domain through a regular parameterization allows us to define a univalent mapping, which can be computed as the solution of an elliptic problem, equipped with suitable Dirichlet boundary conditions. In recent years, Physics-Informed Neural Networks (PINNs) have been proved to be a powerful tool to compute the solution of Partial Differential Equations (PDEs) replacing standard numerical models, based on Finite Element Methods and Finite Differences, with deep neural networks; PINNs can be used for predicting the values on simulation grids of different resolutions without the need to be retrained. In this work, we exploit the PINN model in order to solve the PDE associated to the differential problem of the parameterization on both convex and non-convex planar domains, for which the describing PDE is known. The final continuous model is then provided by applying a Hermite type quasi-interpolation operator, which can guarantee the desired smoothness of the sought parameterization. Finally, some numerical examples are presented, which show that the PINNs-based approach is robust. Indeed, the produced mapping does not exhibit folding or self-intersection at the interior of the domain and, also, for highly non convex shapes, despite few faulty points near the boundaries, has better shape-measures, e.g., lower values of the Winslow functional
Contribution of magnetic resonance imaging to the diagnosis and monitoring of multiple sclerosis [Diagnosi precoce e monitoraggio nella sclerosi multipla: Il contributo della risonanza magnetica]
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