Search results for "image processing"
showing 10 items of 3285 documents
An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks
2020
Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a…
Adaptation of the Model for Assessment of Telemedicine (MAST) for IoT Telemedicine Services
2017
Internet of Things (IoT) based solutions and services may be used to support and extend the independent living of older adults in their living environments by responding to real needs of caregivers, service providers and public authorities. Telemedicine and telehealth platforms are among the various types of IoT services that could support the provision of health services. Current Health Technology Assessment (HTA) models that are used for the evaluation of telehealth and telemedicine services do not consider IoT aspects. HTA models would ideally need to be extended to include IoT platforms, for an optimal introduction of IoT in everyday provision of health and care services. This paper pre…
Knowledge-based modelling applied to synucleinopathies
2015
International audience; The adoption of telemedicine technologies has enabled collaborative programs involving a variety of links among distributed medical structures and health officials and professionals. The use for telemedicine for transmission of medical data and the possibility for several distant physicians to share their knowledge on given medical cases provides clear benefits, but also raises several unsolved conceptual and technical challenges. The seamless exchange and access of medical information between medical structures, health professionals, and patients is a prerequisite for the harmonious development of this new medical practice. This paper proposes a new approach of sema…
Imaging synaptic zinc release in living nervous tissue
2001
Zinc enriched neurons have a pool of synaptic vesicles which contain free or loosely-bound zinc ions. The movement of the vesicular zinc ions into the synaptic clefts has been previously studied by microdialysis, fluorescence postmortem staining for zinc and radioactive zinc isotope. In this study the zinc fluorescence probe N-6-metoxy-p-toluensulfonamide quinoline (TSQ) has been applied as a tracer of synaptic release of zinc ions. This fluorochrome permeates cell membranes and when exposed to living brain slices gives rise to a staining pattern similar to that seen with autometallography. In the living brain slices, fluorescence emission persists after exposure to calcium saturated ethyle…
Latest developments in rock art recording: towards an integral documentation of Levantine rock art sites combining 2D and 3D recording techniques
2013
This paper presents a further step in the integral documentation of prehistoric rock art, combining 2D and 3D digital recording techniques. Image processing and digital enhancement techniques are an invaluable aid to obtain high quality and accurate 2D recordings, especially when working with faint motifs or complex superimpositions. But what constitutes a real breakthrough is the possibility of combining 2D digital tracings with metric 3D models, providing a whole set of metric outputs that improve our understanding of the motifs in their context and, at the same time, can be used to deliver accurate metric reproductions. The Levantine rock art at Cingle de la Mola Remigia (Ares del Maestr…
Biomechanics of human ascending aorta and aneurysm rupture risk assessment
2021
Ascending aortic aneurysms (AsAA) and aortic dissections are life-threatening cardiovascular diseases. The main criteria for determining surgical intervention of AsAA are the maximum diameter or the increasing annual rate of the aneurysm. The mortality of the untreated aortic dissection can be 21% to 74%, depending on the delay of hospital admission.Our study aims to characterize the biomechanical properties of the ascending aorta and propose a patient-specific approach to assess the risks of rupture. The purpose of this PhD work is multifold.On the one hand, biaxial tensile tests were performed on AsAA samples obtained from one hundred patients with surgery of AsAA. The impact on the diffe…
Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora
2020
In this paper, we tackle the problem of the irony and sarcasm detection for the Italian language to contribute to the enrichment of the sentiment analysis field. We analyze and compare five deep-learning systems. Results show the high suitability of such systems to face the problem by achieving 93% of F1-Score in the best case. Furthermore, we briefly analyze the model architectures in order to choose the best compromise between performances and complexity.
Graph-based exploration and clustering analysis of semantic spaces
2019
Abstract The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that …
A Controllable Text Simplification System for the Italian Language
2021
Text simplification is a non-trivial task that aims at reducing the linguistic complexity of written texts. Researchers have studied the problem by proposing new methodologies for addressing the English language, but other languages, like the Italian one, are almost unexplored. In this paper, we give a contribution to the enhancement of the Automated Text Simplification research by presenting a deep learning-based system, inspired by a state of the art system for the English language, capable of simplifying Italian texts. The system has been trained and tested by leveraging the Italian version of Newsela; it has shown promising results by achieving a SARI value of 30.17.
Cost-driven framework for progressive compression of textured meshes
2019
International audience; Recent advances in digitization of geometry and radiometry generate in routine massive amounts of surface meshes with texture or color attributes. This large amount of data can be compressed using a progressive approach which provides at decoding low complexity levels of details (LoDs) that are continuously refined until retrieving the original model. The goal of such a progressive mesh compression algorithm is to improve the overall quality of the transmission for the user, by optimizing the rate-distortion trade-off. In this paper, we introduce a novel meaningful measure for the cost of a progressive transmission of a textured mesh by observing that the rate-distor…