Academic literature on the topic 'Imagerie par flux vectoriel'
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Journal articles on the topic "Imagerie par flux vectoriel"
Paul, J. F. "Évaluation des flux en imagerie par résonnance magnétique cardiaque : l’imagerie de flux 4D." Annales de Cardiologie et d'Angéiologie 69, no. 5 (November 2020): 273–75. http://dx.doi.org/10.1016/j.ancard.2020.09.011.
Full textLeclère, Franck M. P., Michel Schoofs, Florent Auger, Bruno Buys, and Serge Mordon. "Évaluation du flux sanguin par imagerie en résonance magnétique fonctionnelle après anastomoses artérielles assistées par laser diode 1,9μm." Annales de Chirurgie Plastique Esthétique 56, no. 6 (December 2011): 540–47. http://dx.doi.org/10.1016/j.anplas.2010.03.001.
Full textZavard, Guillaume, Jean-François Catanzariti, Marion Lacoste, Khalid Ambarki, Stephane Verdun, Martin Catala, Andre Thevenon, Vincent TIFFREAU, and Sebastien Verclytte. "Etude medulloscol: evaluation du flux du liquide cerebrospinal par imagerie par resonance magnetique nucleaire dans la scoliose idiopathique de l'adolescence." Journal of Neuroradiology 49, no. 2 (March 2022): 140–41. http://dx.doi.org/10.1016/j.neurad.2022.01.044.
Full textDejoux, Jean-François, Gérard Dedieu, Olivier Hagolle, Danièle Ducrot, Jean-Claude Menaut, Eric Ceschia, Frédéric Baup, et al. "Kalideos OSR MiPy : un observatoire pour la recherche et la démonstration des applications de la télédétection à la gestion des territoires." Revue Française de Photogrammétrie et de Télédétection, no. 197 (April 22, 2014): 17–30. http://dx.doi.org/10.52638/rfpt.2012.79.
Full textDelay, L., M. Tanter, and S. Pezet. "Neuro-imagerie fonctionnelle ultrasonore : vers une meilleure compréhension de la physiologie et de la physiopathologie des douleurs aiguës et chroniques." Douleur et Analgésie, 2022. http://dx.doi.org/10.3166/dea-2022-0237.
Full textDissertations / Theses on the topic "Imagerie par flux vectoriel"
Ling, Hang Jung. "Écoulement intraventriculaire en échocardiographie Doppler avec réseaux de neurones fondés sur la physique." Electronic Thesis or Diss., Lyon, INSA, 2024. http://www.theses.fr/2024ISAL0087.
Full textThe heart, as the central organ of the cardiovascular system, is responsible for pumping blood to all the body’s cells and tissues. Assessing cardiac health is crucial for the early detection and prevention of cardiovascular diseases. Echocardiography, due to its portability and affordability, is commonly used to evaluate the heart’s efficiency during filling (diastolic function) and ejection (systolic function). While systolic function is typically assessed using parameters like the ejection fraction, diastolic function is often measured through mitral valve and annular velocities, which can sometimes result in inconsistent diagnoses. Intraventricular vector flow mapping (iVFM) offers an alternative approach by reconstructing vector blood flow from color Doppler acquisitions. This method allows for the evaluation of intracardiac blood flow patterns and vortex characteristics, providing potentially more accurate quantification of diastolic function. However, iVFM involves time-consuming preprocessing steps, such as left ventricular segmentation and aliasing correction. This thesis introduces deep learning (DL) techniques to automate these processes. First, 3D DL models were developed to achieve temporally consistent left ventricular segmentation. Next, DL-based methods were applied to address aliasing artifacts through segmentation and deep unfolding techniques. Finally, iVFM was performed using physics-informed neural networks (PINNs) and a physics-guided supervised method. The proposed neural network approaches demonstrated performance on par with the original iVFM technique, with the added benefit of the physics-guided method being independent of explicit boundary conditions. These findings underscore the potential application of PINNs in ultrafast color Doppler imaging with the integration of fluid dynamics equations to enhance reconstruction accuracy. Automating the iVFM pipeline with neural networks enhances its reliability, paving the way for clinical applications and the exploration of new flow-based biomarkers
WECKER, DIDIER. "Imagerie de flux par resonance magnetique nucleaire." Université Louis Pasteur (Strasbourg) (1971-2008), 1989. http://www.theses.fr/1989STR13070.
Full textYzet, Thierry. "Débitmétrie hépatique par IRM de flux : validation et application clinique." Amiens, 2009. http://www.theses.fr/2009AMIED005.
Full textFlow measurements using Phase Contrast Magnetic Resonance Imaging was evaluated at the hepatic level for the portal trunk and the proper hepatic artery. After modification of a medical image processing software developed in-situ, this method of flow IRM was validated for healthy subjects and was compared to Doppler examinations. The variabilities of velocities and flow measurements significantly appear weaker and more reproducible using IRM compared to Doppler ultrasound examination. The application of the technique for pathological populations made it possible to confirm commonly known physiological data and thus allow a non-invasive functional exploration in clinical practice during a standard morphological MRI examination. New developments then appear possible: quantification and evolution of the hepatic fibrosis stages or clinical responses to anti-antigenic therapies as possible examples
Yakam, Simen Francis. "Contribution à l'étude de l'écoulement veineux par imagerie de flux R. M. N." Toulouse, INPT, 1994. http://www.theses.fr/1994INPT107H.
Full textLevilly, Sébastien. "Quantification de biomarqueurs hémodynamiques en imagerie cardiovasculaire par résonance magnétique de flux 4D." Thesis, Ecole centrale de Nantes, 2020. http://www.theses.fr/2020ECDN0007.
Full textIn cardiovascular imaging, a biomarker is quantitative information correlated with an existing or growing cardiovascular pathology. Biomarkers are generally obtained by anatomy and blood flow imaging. Recently, the 4D Flow MRI sequence opened new opportunities in measuring the blood flow within a 3D volume along the cardiac cycle. However, this sequence is a compromise between signalto-noise ratio, resolution and acquisition time. Allocated time being limited, velocity measurements are noisy and low resolution. In that context, biomarkers' quantification is challenging. This thesis's purpose is to enhance biomarkers' quantification and particularly for the wall shear stress (WSS). Two strategies have been investigated to reach that objective. A first solution allowing the spatiotemporal filtering of the velocity field has been proposed. It revealed the importance of the wall for the velocity field modelization. A second approach, being the major contribution of this work, focused on the design of a WSS quantification algorithm. This algorithm, named PaLMA, is based on the local modelization of the wall to build a velocity model near a point of interest. The WSS is computed from the velocity model. This algorithm embeds an a posteriori regularization step to improve the WSS quantification. Besides, a blurring model of 4D Flow MRI is used for the first time in the WSS quantification context. Finally, this algorithm has been validated over synthetic datasets, with carotids' complex flows, concerning the signal-to-noise ratio, the resolution, and the segmentation. The performances of PaLMA are superior to a reference solution in that domain, within a clinical routine context
Jeannot, Valérie. "Contribution à l'utilisation de rhodamines pour le ciblage intracellulaire : synthèse de rhodamnes aliphatiques et étude par imagerie de fluorescence." Perpignan, 1996. http://www.theses.fr/1996PERP0338.
Full textLoubeyre, Pierre. "Imagerie des vaisseaux par résonance magnétique : des méthodes sensibles au flux à celles dépendantes de la relaxation sanguine." Lyon 1, 1996. http://www.theses.fr/1996LYO1T075.
Full textCorreia, Mafalda Filipa Rodrigues. "From 2D to 3D cardiovascular ultrafast ultrasound imaging : new insights in shear wave elastography and blood flow imaging." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCC158.
Full textThis thesis was focused on the development of novel cardiovascular imaging applications based on 2-D and 3-D ultrafast ultrasound imaging. More specifically, new technical and clinical developments of myocardial shear wave elastography and ultrafast blood flow imaging are presented in this manuscript.At first, myocardial shear wave elastography was developed for transthoracic imaging and improved by a non-linear imaging approach to non-invasively and locally assess shear wave velocity measurements, and consequently tissue stiffness in the context of cardiac imaging. This novel imaging approach (Ultrafast Harmonic Coherent Compounding) was tested and validated in-vitro and the in vivo feasibility was performed in humans for biomechanical evaluation of the cardiac muscle wall, the myocardium. Then, we have translated shear wave elastography to the clinical practice within two clinical trials, each one with a different population (adults and children). In both clinical trials, we have studied the capability of shear wave elastography to assess quantitatively myocardial stiffness in healthy volunteers and in patients suffering from hypertrophic cardiomyopathy. The results in the adult population indicated that shear wave elastography may become an effective imaging tool to assess cardiac muscle stiffness in clinical practice and help the characterization of hypertrophic cardiomyopathy. Likewise, we have also translated Shear Wave Elastography into four-dimensions and we have developed a new approach to map tissue elastic anisotropy in 3-D. 3-D Elastic Tensor Imaging allowed us to estimate quantitatively in a single acquisition the elastic properties of fibrous tissues. This technique was tested and validated in vitro in transverse isotropic models. The in-vivo feasibility of 3D elastic tensor imaging was also assessed in a human skeletal muscle.In parallel, we have developed a novel imaging technique for the non-invasive and non-radiative imaging of coronary circulation using ultrafast Doppler. This approach allowed us to image blood flow of the coronary circulation with high sensitivity. A new adaptive filter based on the singular value decomposition was used to remove the clutter signal of moving tissues. Open-chest swine experiments allowed to evaluate and validate this technique and results have shown that intramural coronary circulation, with diameters up to 100 µm, could be assessed. The in-vivo transthoracic feasibility was also demonstrated in humans in pediatric cardiology.Finally, we have developed a novel imaging modality to map quantitatively the blood flow in 3-D: 3-D ultrafast ultrasound flow imaging. We demonstrated that 3-D ultrafast ultrasound flow imaging can assess non-invasively, user-independently and directly volumetric flow rates in large arteries within a single heartbeat. We have evaluated and validated our technique in vitro in arterial phantoms using a 2-D matrix-array probe and a customized, programmable research 3-D ultrafast ultrasound system, and the in-vivo feasibility was demonstrated in human carotid arteries
Ramona, Mathieu. "Classification automatique de flux radiophoniques par machines à vecteurs de support." Phd thesis, Paris, Télécom ParisTech, 2010. https://pastel.hal.science/pastel-00529331.
Full textWe present here a system for speech/music audio classification, that relies on the excellent statistical properties of Support Vector Machines. This problems raises three questions : how can the SVM, by essence discriminative, be used effeciently on a problem involving more than two classes, how can an audio signal be characterized in a relevant way, and how can the temporel issue be adressed ? We propose a hybrid system for multi-class classification, based on a combination of One-vs-One and dendogram-based approaches, and allowing the estimation of posterior probabilities. The latter are used for the application of post-processing methods that take into account the neighboring frames' inter-dependancies. We thus propose a classification scheme based on the application of Hidden Markov Models on the posterior probabilities, along with an approach based on change detection between segments with "homogeneous" acoustic content. Concerning the audio signal characterization, since it involves a great amount of audio descriptors, we propose new algorithms for feature selection, based on the recent Kernel Alignement criterion. This criterion is also used for the kernel selection step in the classification process. The proposed algorithms are compared to the state-of-the-art, and constitute a relevant alternative in terms of computational cost and storage. The system built from these contributions has been used for a participation to the ESTER 2 evaluation campaign, that we present, along with our results
Ramona, Mathieu. "Classification automatique de flux radiophoniques par Machines à Vecteurs de Support." Phd thesis, Télécom ParisTech, 2010. http://pastel.archives-ouvertes.fr/pastel-00529331.
Full textBook chapters on the topic "Imagerie par flux vectoriel"
Rousseau, H., R. Moreno, M. Midulla, B. Marcheix, and F. Nicoud. "Imagerie des flux aortiques par IRM Application clinique sur la pathologie aortique thoracique." In Les Syndromes aortiques aigus, 37–47. Paris: Springer Paris, 2009. http://dx.doi.org/10.1007/978-2-287-79929-7_3.
Full textRousseau, H., R. Moreno, A. Baali, M. Chau, M. Midulla, B. Marcheix, A. Salvayre, and F. Nicoud. "Imagerie des flux aortiques par IRM et mécanique des fuides: applications cliniques sur la pathologie aortique thoracique." In Imagerie en coupes du coeur et des vaisseaux, 27–38. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0154-4_2.
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