Academic literature on the topic 'Imagerie en champ lumineux'
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Journal articles on the topic "Imagerie en champ lumineux"
Fragola, A., L. Aigouy, S. Grésillon, and Y. De Wilde. "Imagerie de fluorescence en champ proche." Journal de Physique IV (Proceedings) 12, no. 5 (June 2002): 303–5. http://dx.doi.org/10.1051/jp4:20020172.
Full textGeismar, Y., M. N. Delyfer, O. Auzerie, B. Gontier, and J. F. Korobelnik. "Rétinoschisis sénile bilatéral : imagerie grand champ." Journal Français d'Ophtalmologie 38, no. 7 (September 2015): 669. http://dx.doi.org/10.1016/j.jfo.2014.08.011.
Full textDion, E., J. Coumbaras, N. Faye, R. Sassi, C. Caudron, A. Belkacem, R. Marsico, B. Coustet, and R. Boulos. "IRM ouverte a champ vertical : perspectives en imagerie osteo-articulaire." Journal de Radiologie 89, no. 10 (October 2008): 1321. http://dx.doi.org/10.1016/s0221-0363(08)75964-x.
Full textBlanc-Durand, P. "Instrumentation « CZT grand champ et intelligence artificielle en imagerie médicale »." Médecine Nucléaire 43, no. 5-6 (October 2019): 409–10. http://dx.doi.org/10.1016/j.mednuc.2019.07.009.
Full textRomanowicz, Barbara. "Imagerie globale de la Terre par les ondes sismiques." Reflets de la physique, no. 56 (January 2018): 4–9. http://dx.doi.org/10.1051/refdp/201856004.
Full textTonnelet, R., M. Labrousse, J. M. Escanye, B. Chen, A. Sewonu, O. Morel, J. Felblinger, M. Lhuaire, and M. Braun. "Micro-imagerie par résonance magnétique à haut champ : nouvel outil de l’anatomiste." Morphologie 97, no. 318-319 (October 2013): 96–97. http://dx.doi.org/10.1016/j.morpho.2013.09.089.
Full textGuillaume, L., T. Joris, and M. Claudon. "Evaluation d’un capteur plan grand champ en imagerie pediatrique : etude de productivite." Journal de Radiologie 86, no. 10 (October 2005): 1313. http://dx.doi.org/10.1016/s0221-0363(05)75405-6.
Full textMoussali, Nadia, Omar Amriss, and Naima Elbenna. "Indications of magnetic resonance imaging." Batna Journal of Medical Sciences (BJMS) 2, no. 2 (December 30, 2012): 196–99. http://dx.doi.org/10.48087/bjmstf.2015.2221.
Full textSuma, Sophie. "Que nous dit la maison de La petite maison dans la prairie ?" Radar, no. 7 (June 15, 2022): 107–14. http://dx.doi.org/10.57086/radar.508.
Full textBenni, D., L. Qu-Knafo, and A. Giocanti-Aurégan. "Séquelle de vascularite et de capillaropathie occlusive « en dentelle » en imagerie ultra grand champ." Journal Français d'Ophtalmologie 41, no. 6 (June 2018): 581–82. http://dx.doi.org/10.1016/j.jfo.2017.10.011.
Full textDissertations / Theses on the topic "Imagerie en champ lumineux"
Proust, Clément. "Vers un modèle unifié pour l'affichage autostéréoscopique d'images." Mémoire, Université de Sherbrooke, 2016. http://hdl.handle.net/11143/8961.
Full textHerzog, Charlotte. "imagerie plénoptique : de la lumière visible aux rayons X." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0116.
Full textPlenoptic imaging is a technique that acquires spatial and angular information of the light rays incoming from a scene. After a single acquisition, numerical data treatment allows image manipulation such as synthetic aperture, changing viewpoint, refocusing at different depths, and consequently 3D reconstruction of the scene. Visible plenoptic has been widely studied. However, transposition from visible to X-rays has never been done and remains challenging. X-ray plenoptic would be beneficial to the X-ray imaging panorama. A single acquisition should be sufficient to reconstruct a volume, against 1000’s for X-ray tomography that is the today reference in 3D X-ray imaging.In this thesis, we consider plenoptic camera composed of a main lens, a microlens array and a detector. So far, two different configurations have been developed: the traditional and the focused plenoptic setups. Although these configurations are usually studied separately, they only differ by the distances between the optical elements. These two configurations were studied in detail to choose the most suitable for X-ray imaging, considering the constraints of X-ray optics. We observed a full continuity between the two systems. Therefore, we extended the previous work to more general formulas about optical configuration and theoretical resolutions. Theory about resolution along the depth axis was refined, as depth reconstruction and extraction are the main interest of X-ray plenoptic. Specific study was done on the evolution of contrast along depth as being a key parameter for depth reconstruction. We realized that contrast decreases when moving away from a privileged depth. This is important to consider as it can affect image reconstruction and quality of depth extraction.We also worked on refocusing algorithms. The refocusing algorithms are usually developed for each configuration separately. We worked to go beyond this separation. We developed a new algorithm valid for any configurations. Moreover, our algorithm is based on real distances between the optical elements, allowing generating images at any distances from the plenoptic camera. We defined a new parameterization between object and image spaces. Using geometrical optics, we calculated the matrix transformation between the two spaces. This allows back-projecting data from the acquired raw image to the object space, and reconstructing the pixels one by one, until the whole object. With this algorithm, we were able to simulate the process of image acquisition, and create synthetic plenoptic data. Reconstruction of these data was used to quantify the accuracy of the novel algorithm and prove its consistency.The refocusing algorithm allows reconstructing the depth planes one by one. Each refocused plane contains information about the whole 3D scene that has to be disentangled. The elements physically present at the refocused depth are intrinsically sharp, whereas the ones located at other depths are blurred. We used this contrast property to extract depth from the refocused images. We tested several existing methods derived from the field of depth from focus and studied their efficiency when applied to our images.In collaboration with European teams, we realized the first X-ray plenoptic camera that was tested at P05 beamline of PETRA III synchrotron. Based on the theoretical work developed in this thesis, we defined the best optical configuration, mounted the plenoptic camera, acquired X-ray plenoptic images, numerically refocused them using the new algorithm and verified the experimental resolutions and contrasts. Depth from focus techniques applied on the refocused stack allow to retrieve the expected depth plane. These are the first images acquired with an X-ray plenoptic camera
Stepanov, Milan. "Selected topics in learning-based coding for light field imaging." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG050.
Full textThe current trend in imaging technology is to go beyond the 2D representation of the world captured by a conventional camera. Light field technology enables us to capture richer directional cues. With the recent availability of hand-held light field cameras, it is possible to capture a scene from various perspectives with ease at a single exposure time, enabling new applications such as a change of perspective, focusing at different depths in the scene, and editing depth-of-field.Whereas the new imaging model increases frontiers of immersiveness, quality of experience, and digital photography, it generates huge amounts of data demanding significant storage and bandwidth resources. To overcomethese challenges, light fields require the development of efficient coding schemes.In this thesis, we explore deep-learning-based approaches for light field compression. Our hybrid coding scheme combines a learning-based compression approach with a traditional video coding scheme and offers a highly efficient tool for lossy compression of light field images. We employ an auto-encoder-based architecture and an entropy constrained bottleneck to achieve particular operability of the base codec. In addition, an enhancement layer based on a traditional video codec offers fine-grained quality scalability on top of the base layer. The proposed codec achieves better performance compared to state-of-the-art methods; quantitative experiments show, on average, more than 30% bitrate reduction compared to JPEG Pleno and HEVC codecs.Moreover, we propose a learning-based lossless light field codec that leverages view synthesis methods to obtain high-quality estimates and an auto-regressive model that builds probability distribution for arithmetic coding. The proposed method outperforms state-of-the-art methods in terms of bitrate while maintaining low computational complexity.Last but not least, we investigate distributed source coding paradigm for light field images. We leverage the high modeling capabilities of deep learning methods at two critical functional blocks in the distributed source coding scheme: for the estimation of Wyner-Ziv views and correlation noise modeling. Our initial study shows that incorporating a deep learning-based view synthesis method into a distributed coding scheme improves coding performance compared to the HEVC Intra. We achieve further gains by integrating the deep-learning-based modeling of the residual signal
Couillaud, Julien. "Formation d'image : estimation du champ lumineux et matrice de filtres couleurs." Mémoire, Université de Sherbrooke, 2012. http://hdl.handle.net/11143/5987.
Full textMorel, Sophie. "Imagerie grand champ en anatomopathologie." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAY075/document.
Full textThis PhD project aims to develop a simple, fast (35 minutes), wide-field (up to 2.5 cm x 2.5 cm) multiscale (µm-cm) imaging method for stained and unstained tissue slides for digital pathology application. We present a solution based on lensfree imaging. It is a simple, low-cost technique that enables wide field imaging (10-30 mm²) of sparse objects, like viruses, bacteria or cells. In this project, we adapted lensfree imaging for dense objects observation, like stained or unstained tissue slides. The sample is illuminated under multiple illumination wavelengths, and a new multiwavelength holographic reconstruction algorithm was developed in order to reconstruct the modulus and phase of dense objects. Each image covers 10 mm² field of view, and is reconstructed in 1.1 second. An image of the whole tissue slide covers 6.25 cm². It is recorded in 35 minutes by scanning the sample over the sensor. The reconstructed images are multiscale, allowing the user to observe the overall tissue structure and to zoom down to the single cell level (3-4 µm). The method was tested on various stained and unstained pathology samples. Besides tissue slides, multiwavelength lensfree imaging shows encouraging results for meningitis diagnosis, bacteria population monitoring for identification and antibiotic susceptibility testing, and cell culture monitoring
Guyon, Olivier. "Imagerie interférométrique grand champ et applications." Paris 6, 2002. http://www.theses.fr/2002PA066170.
Full textStephan, Jean. "Architecture 3D et microclimat lumineux de l'arbre." Phd thesis, Clermont-Ferrand 2, 2007. http://www.theses.fr/2007CLF21754.
Full textLAHRECH, AHMED. "Imagerie infrarouge par microscopie en champ proche optique." Paris 11, 1999. http://www.theses.fr/1999PA112291.
Full textLe, Brusq E. "Imagerie microonde: influence de la polarimétrie du champ diffracté." Phd thesis, Université de Nice Sophia-Antipolis, 2003. http://tel.archives-ouvertes.fr/tel-00454615.
Full textChanet, Nicolas. "Imagerie par résonance magnétique à champ cyclé in vivo." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS574/document.
Full textFast Field Cycling Magnetic Resonance Imaging (FFC-MRI) has the ability to separate two key processes that both depends on the main field intensity B0. On one hand, signal acquisition and localization and on the other hand NMR relaxation, basis of MRI contrast. The equipment thus combines a standard MR scanner with a secondary system to rapidly switch the magnetic field B0 as compared to relaxation times. FFC enables to measure the evolution of NMR relaxation as a function of magnetic field B0, namely the NMR dispersion (NMRD) profile. Combining it with MRI the NMRD profile can be localized in vivo, together with the usual characterization at fixed B0. The NMRD profile of water carries information on molecular mobility in the surrounding biological tissues, and is thus another source of contrast. The objective of this PhD project was to further develop and evaluate the potential of FFC-MRI between 1 T and 2 T in a cancer model. This work required original instrumental and methodological developments to integrate FFC in MRI. First a precise measurement of magnetic field time profile was developed, as well as the compensation of eddy currents and of irreproducible transients in the secondary system. Moreover acquisition sequences with better signal to noise efficiency and applicable for longitudinal as well as transverse relaxation were implemented. Finally a kidney tumor mouse model was explored with FFC MRI
Book chapters on the topic "Imagerie en champ lumineux"
CALLOT, Virginie, and Alexandre VIGNAUD. "Imagerie à ultra-haut champ." In Les enjeux de l’IRM, 345–78. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9113.ch12.
Full textDAUL, Christian, and Walter BLONDEL. "Imagerie endoscopique multimodale et multispectrale à champ de vue étendu." In Imageries optiques non conventionnelles pour la biologie, 207–45. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9132.ch7.
Full text"Complément DXX Les déplacements lumineux : un outil pour manipuler les atomes et le champ." In Mécanique quantique - Tome III, 585–96. EDP Sciences, 2017. http://dx.doi.org/10.1051/978-2-7598-2151-8.c032.
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