Search results for "image processing"
showing 10 items of 3285 documents
Augmented Reality in minimally invasive otologic surgery and transmodiolar cochlear implantation
2021
Optimal exposure is necessary for minimally invasive otologic surgery. Augmented reality allows to enrich the real environment by adding data without replacing it by a virtual environment and to view this information on a single screen by combining the vision of the operating field and the imaging. This technique is very little described in otology in the literature. This project aims to develop augmented reality solutions for otological surgeries and transmodiolar implantation. To prepare this augmented reality project, we studied the visualization of the middle ear by a virtual endoscope based on preoperative high resolution CT-scans. Then, we worked on the application of augmented realit…
Modeling of neuron-astrocyte interaction : application to signal and image processing
2022
The introduction of the tripartite synapse and the discovery of calcium wave propagation motivated our research to explore the potential of astrocytes as active components in brain circuits. For decades, astrocytes have been considered passive cells whose primary function is metabolic and structural support to neurons; however, recent physiological measurements suggest that astrocytes modulate neural communication, strengthen synaptic efficacy, enhance synchronization, and promote homeostasis. Inspired by these biological functions, this research aimed to implement astrocytes in artificial spiking networks for deep learning applications. First, we modeled the biological interaction between …
Mathematical models for Multi Container Loading Problems with practical constraints
2019
Abstract We address the multi container loading problem of a company that serves its customers’ orders by building pallets with the required products and loading them into trucks. The problem is solved by using integer linear models. To be useful in practice, our models consider three types of constraints: geometric constraints, so that pallets lie completely inside the trucks and do not overlap; weight constraints, defining the maximum weights supported by a truck and by each axle, as well as the position of the centre of gravity of the cargo; and dynamic stability constraints. These last constraints forbid empty spaces between pallets to avoid cargo displacement when the truck is moving, …
A Framework to Evaluate Autonomic Behaviours for Intelligent Truck Parking
2016
This paper presents a multi-agent platform to evaluate different strategies to manage the negotiated management of parking spaces in road rest areas. The system dynamically adapts itself to the preferences and needs of the drivers of goods about parking requests. The system is shown to be robust to incidents regarding the closure of road rest areas and allows a conversational interaction of new parking requests through an Android based mobile application.
IoT-MAAC: Multiple Attribute Access Control for IoT environments
2020
Access Control is an important security service that should be considered in IoT environments in order to offer reliable IoT services. Access control in IoT environments concerns not only the access of IoT users to IoT services and objects, but also the access of IoT objects to IoT gateways. In this paper, we specify an access control mechanism that considers the access of IoT objects to IoT gateways in order to enhance the reliability of IoT data provided by the IoT objects. Our proposed access control mechanism, called IoT-MAAC (Multi Attribute Access Control), allows retrieving requested data from the most reliable and secured IoT objects among the available objects in the IoT environmen…
18F-FDG PET for breast cancer : combined analysis of tumour perfusion and metabolism for tumour characterisation and neoadjuvant chemotherapy respons…
2020
Neoadjuvant chemotherapy (NAC) is a common treatment in patients with locally advanced or large breast cancer at diagnosis. A pathological complete response (pCR) at the end of NAC is recognized as a good surrogate marker of relapse-free survival. An early identification of the pathological response has then become a key parameter to monitor new therapeutic strategies. Studies, focusing on predictive biomarkers identification, have shown that early changes in tumour metabolism, assessed by Positron Emission Tomography (PET) using 2-desoxy-2-18F-fluoro-D-glucose (18F-FDG), allow the early assessment of the pathological response at the end of treatment. However, given the diversity of breast …
A DGS gesture dictionary for modelling on mobile devices
2017
ABSTRACTInteractive or Dynamic Geometry System (DGS) is a tool that help to teach and learn geometry using a computer-based interactive environment. Traditionally, the interaction with DGS is based on keyboard and mouse events where the functionalities are accessed using a menu of icons. Nevertheless, recent findings suggest that such a traditional model of interaction has a steep learning curve and is inadequate to develop DGS for devices with multi-touch screens. Thus, we propose a new interaction model for DGS based on a gesture dictionary which enables the construction and manipulation of geometric objects without the need of accessing a menu of icons. The dictionary is divided into thr…
Pervasive access to MRI bias artifact suppression service on a grid.
2009
Bias artifact corrupts magnetic resonance images in such a way that the image is afflicted by illumination variations. Some of the authors proposed the Exponential Entropy Driven - Homomorphic Unsharp Masking (E2D-HUM) algorithm that corrects this artifact without any a priori hypothesis about the tissues or the Magnetic Resonance image modality. Moreover, E2D-HUM does not care about the body part under examination and does not require any particular training task. People who want to use this algorithm, which is Matlab-based, have to set their own computers in order to execute it. Furthermore, they have to be Matlab-skilled to exploit all the features of the algorithm. In our work we propos…
The Average State Complexity of the Star of a Finite Set of Words Is Linear
2008
We prove that, for the uniform distribution over all sets Xof m(that is a fixed integer) non-empty words whose sum of lengths is n, $\mathcal{D}_X$, one of the usual deterministic automata recognizing X*, has on average $\mathcal{O}(n)$ states and that the average state complexity of X*is i¾?(n). We also show that the average time complexity of the computation of the automaton $\mathcal{D}_X$ is $\mathcal{O}(n\log n)$, when the alphabet is of size at least three.
On achieving near-optimal “Anti-Bayesian” Order Statistics-Based classification fora asymmetric exponential distributions
2013
Published version of a Chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_44 This paper considers the use of Order Statistics (OS) in the theory of Pattern Recognition (PR). The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean - which is distinct from the optimal Bayesian paradigm. In [2], we showed that the results could be extended for a few sym…