Search results for "tomate"
showing 10 items of 261 documents
A Novel Approach to Propagation Pattern Analysis in Intracardiac Atrial Fibrillation Signals
2010
The purpose of this study is to investigate propagation patterns in intracardiac signals recorded during atrial fibrillation (AF) using an approach based on partial directed coherence (PDC), which evaluates directional coupling between multiple signals in the frequency domain. The PDC is evaluated at the dominant frequency of AF signals and tested for significance using a surrogate data procedure specifically designed to assess causality. For significantly coupled sites, the approach allows also to estimate the delay in propagation. The methods potential is illustrated with two simulation scenarios based on a detailed ionic model of the human atrial myocyte as well as with real data recordi…
Semi-automated and interactive segmentation of contrast-enhancing masses on breast DCE-MRI using spatial fuzzy clustering
2022
Abstract Multiparametric Magnetic Resonance Imaging (MRI) is the most sensitive imaging modality for breast cancer detection and is increasingly playing a key role in lesion characterization. In this context, accurate and reliable quantification of the shape and extent of breast cancer is crucial in clinical research environments. Since conventional lesion delineation procedures are still mostly manual, automated segmentation approaches can improve this time-consuming and operator-dependent task by annotating the regions of interest in a reproducible manner. In this work, a semi-automated and interactive approach based on the spatial Fuzzy C-Means (sFCM) algorithm is proposed, used to segme…
Introducing ARTMO's Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape.
2022
Accurate plant-type (PT) detection forms an important basis for sustainable land management maintaining biodiversity and ecosystem services. In this sense, Sentinel-2 satellite images of the Copernicus program offer spatial, spectral, temporal, and radiometric characteristics with great potential for mapping and monitoring PTs. In addition, the selection of a best-performing algorithm needs to be considered for obtaining PT classification as accurate as possible . To date, no freely downloadable toolbox exists that brings the diversity of the latest supervised machine-learning classification algorithms (MLCAs) together into a single intuitive user-friendly graphical user interface (GUI). To…
Application of Nanogen microarray technology for forensic SNP analysis
2006
Abstract The NanoChip® Molecular Biology Workstation using electronic microarrays is an approach for rapid and high throughput analysis of SNPs. This instrument is fully automated and uses a microchip for electronic addressing of capture probes to specific array sites followed by electronic hybridisation of the single stranded PCR products, and passive hybridisation of fluorescently labelled reporter probes. Discrimination is achieved by applying thermal stringency to denature the mismatched reporters. 48 SNP assays have been designed using the ‘capture down’ assay which applies a thermal ‘touch down’ strategy to obtain the best reporter probe discrimination.
Potencialidades de Google Maps en la investigación social aplicada
2019
In recent years, Google has devoted resources to build a complete map of the world. They constantly scan the territory, collecting a large amount of data that provides updated and complete geographic information. This allows us to have an interoperable map that provides the end user with a search tool, not only of routes but also of shops, equipment and any type of geo-referenced information. In addition, Google Maps provides a series of Application Programming Interface (API), which provides a library of set of subroutines, functions and procedures (in object-oriented programming) that can be used by other software to automate the extraction of information of the Google platform. These fre…
Expanding the Variety of Zirconium‐based Inorganic Building Units for Metal–Organic Frameworks
2019
Two new zirconium-based metal-organic frameworks with the composition [Zr6 O4 (OH)4 (OAc)6 (BDC)3 ] (CAU-26) and [Zr5 O4 (OH)4 (OAc)4 (BDC)2 ] (CAU-27) are reported, which were synthesized from acetic acid, a rarely utilized but green and sustainable solvent (BDC2- : 1,4-benzenedicarboxylate). Structure determination aided by automated electron diffraction tomography revealed that CAU-26 is composed of layers of well-known {Zr6 O8 } clusters interconnected by terephthalate ions. In contrast CAU-27 exhibits a three-dimensional structure with a so far unknown type of one-dimensional inorganic building unit (IBU), which can be rationalized as condensed polyhedron-sharing chains of {Zr6 O8 } cl…
T-pattern detection and analysis for the discovery of hidden features of behaviour
2018
Abstract Background The behaviour of all living beings consists of hidden patterns in time; consequently, its nature and its underlying dynamics are intrinsically difficult to be perceived and detected by the unaided observer. Method Such a scientific challenge calls for improved means of detection, data handling and analysis. By using a powerful and versatile technique known as T-pattern detection and analysis (TPA) it is possible to unveil hidden relationships among the behavioural events in time. Results TPA is demonstrated to be a solid and versatile tool to study the deep structure of behaviour in different experimental contexts, both in human and non human subjects. Conclusion This re…
Computer-aided detection of cerebral microbleeds in susceptibility-weighted imaging.
2014
Susceptibility-weighted imaging (SWI) is recognized as the preferred MRI technique for visualizing cerebral vasculature and related pathologies such as cerebral microbleeds (CMBs). Manual identification of CMBs is time-consuming, has limited reliability and reproducibility, and is prone to misinterpretation. In this paper, a novel computer-aided microbleed detection technique based on machine learning is presented: First, spherical-like objects (potential CMB candidates) with their corresponding bounding boxes were detected using a novel multi-scale Laplacian of Gaussian technique. A set of robust 3-dimensional Radon- and Hessian-based shape descriptors within each bounding box were then ex…
Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds
1998
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.
Software for automated application of a reference-based method fora posterioridetermination of the effective radiographic imaging geometry
2005
Objectives: Presentation and validation of software developed for automated and accurate application of a reference-based algorithm (reference sphere method: RSM) inferring the effective imaging geometry from quantitative radiographic image analysis. Methods: The software uses modern pattern recognition and computer vision algorithms adapted for the particular application of automated detection of the reference sphere shadows (ellipses) with subpixel accuracy. It applies the RSM algorithm to the shadows detected, thereby providing threedimensional Cartesian coordinates of the spheres. If the three sphere centres do not lie on one line, they uniquely determine the imaging geometry. Accuracy …