Search results for "STED"

COMMENT ON THE SPACE TRANSLATION METHOD AS USED IN LASER-ASSISTED COLLISION PROBLEMS

1982

Advanced computation in cardiovascular physiology: New challenges and opportunities

2021

Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While these advanced tools have demonstrated excellent diagnostic capabilities, the high complexity of these computational 'black boxes’ may severely limit scientific inference, especially in terms of biological insight about both physiology and pathological aberrations. This theme issue highlights current challenges and opportunities of advanced computational tools for processing dynamical data reflecting autonomic nervous system dynamics, with a speci…

Semi-automated evaluation tool for retinal vasculopathy.

2009

The ocular fundus is the only area of human body where vascular system is visible using relatively simple instrumentation. Furthermore, there is medical suggestive evidence of a direct relationship between certain measures of vascular characteristics in the ocular fundus (arteriolar and venular calibers and focal arteriolar narrowing) and cardiovascular diseases. In order to establish such relationship on sound statistical basis a method must be provided to measure the needed values in an easy, yet precise and repeatable way. This paper presents a system to assist physicians in signaling and storing the data associated to signs of vascular deterioration and vascular calibers in non-mydriati…

Bias artifact suppression on MR volumes.

2007

RF-Inhomogeneity correction is a relevant research topic in the field of Magnetic Resonance Imaging (MRI). A volume corrupted by this artifact exhibits nonuni- form illumination both inside a single slice and between adjacent ones. In this work a bias correction technique is presented, which suppresses this artifact on MR vol- umes scanned from different body parts without any a-priori hypothesis on the artifact model. Theoretical foundations of the method are reported together with experimental results and a comparison is presented with both the 2D version of the algorithm and other techniques that are widely used in MRI literature.

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology

2021

[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…

Image Inpainting Methods Evaluation and Improvement

2014

With the upgrowing of digital processing of images and film archiving, the need for assisted or unsupervised restoration required the development of a series of methods and techniques. Among them, image inpainting is maybe the most impressive and useful. Based on partial derivative equations or texture synthesis, many other hybrid techniques have been proposed recently. The need for an analytical comparison, beside the visual one, urged us to perform the studies shown in the present paper. Starting with an overview of the domain, an evaluation of the five methods was performed using a common benchmark and measuring the PSNR. Conclusions regarding the performance of the investigated algorith…

Matlab-based interface for the simultaneous acquisition of force measures and Doppler ultrasound muscular images

2012

This paper tackles the design of a graphical user interface (GUI) based on Matlab (MathWorks Inc., MA), a worldwide standard in the processing of biosignals, which allows the acquisition of muscular force signals and images from a ultrasound scanner simultaneously. Thus, it is possible to unify two key magnitudes for analyzing the evolution of muscular injuries: the force exerted by the muscle and section/length of the muscle when such force is exerted. This paper describes the modules developed to finally show its applicability with a case study to analyze the functioning capacity of the shoulder rotator cuff.

Statistical geometric affinity in human brain electric activity

2007

10 pages, 9 figures.-- PACS nrs.: 87.19.La; 05.45.Tp.-- ISI Article Identifier: 000246890100105

Measuring the agreement between brain connectivity networks.

2016

Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing th…

Quantification and automatized adaptive detection of in vivo and in vitro neuronal bursts based on signal complexity.

2015

In this paper, we propose employing entropy values to quantify action potential bursts in electrophysiological measurements from the brain and neuronal cultures. Conventionally in the electrophysiological signal analysis, bursts are quantified by means of conventional measures such as their durations, and number of spikes in bursts. Here our main aim is to device metrics for burst quantification to provide for enhanced burst characterization. Entropy is a widely employed measure to quantify regularity/complexity of time series. Specifically, we investigate the applicability and differences of spectral entropy and sample entropy in the quantification of bursts in in vivo rat hippocampal meas…