1,720,957 research outputs found
Parametric Detection and Classification of Compact Conductivity Contrasts With Electrical Impedance Tomography
Electrical impedance tomography is a noninvasive and cost-effective imaging method that is increasingly attractive in the field of medical diagnostics. Several health conditions, such as stroke and solid tumors, are characterized by compact conductivity anomalies surrounded by a fairly regular background. Commonly employed voxel-by-voxel reconstruction methods for impedance imaging share the disadvantages of high computational cost and substantial sensitivity to measurement noise and imperfections in the electrical model describing the domain of interest. We present a special purpose algorithm for automatic detection and identification of compact conductivity variations. The technique exploits a priori structural information and, by reconstructing only the limited number of parameters required to describe a compact conductivity contrast, does not depend on a critical regularization parameter. The most demanding kernels are implemented to run on graphics processing units to accelerate computation. The parametric reconstruction is quicker and more robust than widely employed approaches with respect to measurement noise and imperfections in the electrical model, as shown by computational analysis performed on a segmented head domain and experimental measurements acquired on a cylindrical phantom. When the goal is quick detection of compact conductivity contrasts in complex 3-D domains, the inclusion of specific constraints relating to the problem considered leads to enhanced quality of reconstruction, making the presented technique a promising alternative to common voxel-by-voxel reconstruction methods
Creamino: a Cost-Effective, Open-Source EEG-based BCI System
This paper presents an open source framework called Creamino. It consists of an Arduino-based cost-effective quick-setup EEG platform built with off-the shelf components and a set of software modules that easily allow users to connect this system to Simulink or BCI-oriented tools (such as BCI2000 or OpenViBE) and set up a wide number of neuroscientific experiments. Creamino is capable of processing multiple EEG channels in real-time and operates under Windows, Linux and Mac OS X in real-time on a standard PC. Its objective is to provide a system that can be readily fabricated and used for neurophysiological experiments and, at the same time, can serve as the basis for development of novel BCI platforms by accessing and modifying its open source hardware and software libraries. Schematics, gerber files, bill of materials, source code, software modules, demonstration videos and instructions on how to use these modules are available free of charge for research and educational purposes online at https://github.com/ArcesUnibo/creamino. Application cases show how the system can be used for neuroscientific or BCI experiments. Thanks to its low production cost and its compatibility with open-source BCI tools, the system presented is particularly suitable for use in BCI research and educational applications
Parallel Solver for Diffuse Optical Tomography on Realistic Head Models with Scattering and Clear Regions
Diffuse optical tomography is an imaging technique, based on evaluation of how light propagates within the human head to obtain the functional information about the brain. Precision in reconstructing such an optical properties map is highly affected by the accuracy of the light propagation model implemented, which needs to take into account the presence of clear and scattering tissues. We present a numerical solver based on the radiosity-diffusion model, integrating the anatomical information provided by a structural MRI. The solver is designed to run on parallel heterogeneous platforms based on multiple GPUS and CPUs. We demonstrate how the solver provides a 7 times speed-up over an isotropic-scattered parallel Monte Carlo engine based on a radiative transport equation for a domain composed of 2 million voxels, along with a significant improvement in accuracy. The speed-up greatly increases for larger domains, allowing us to compute the light distribution of a full human head ( approx 3 million voxels) in 116 s for the platform used
Algorithms and Methods for Imaging of Brain Activity from Non-Invasive Techniques
The imaging of brain activity, also called “Functional Neuroimaging”, is used to understand the relationship between activity in certain brain areas and specific functions. These techniques include fMRI (functional Magnetic Resonance Imaging), PET (Positron Emittance Tomography), EIT (Electrical Impedance Tomography), EEG (ElectroEncephaloGraphy) and DOT (Diffuse Optical Tomography) and are widely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In these contexts, usage of classical solutions (fMRI and PET) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons, portable low cost techniques are objects of the proposed thesis’s research, with focus on DOT and EEG.
The main contribution of this thesis focuses on the implementation of a numerical solver for DOT based on the radiosity-diffusion model, integrating the anatomical information provided by a structural MRI.In particular, we obtained a 7x speed-up over an single run of isotropic-scattered parallel Monte Carlo engine for a domain of 2 million voxels, with an accuracy comparable to 10 runs of anisotropic scattered Monte Carlo in the same geometry. The speed-up significantly increases for larger domains, allowing one to compute the light distribution of a full human head (about 3 million voxels) in 116 seconds for the platform used.
The secondary contribution of this thesis focuses on EEG and it concerns the implementation of software libraries for time-domain source localization in the scope of an open-source framework called Creamino, which can be used to simplify and speed-up the design of BCI systems. It consists of firmware and software libraries that allow designers to connect new EEG platforms to software tools for BCI
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
We 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
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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