Relevant bibliographies by topics / Image de microscopie

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Image de microscopie'

Author: Grafiati
Published: 15 March 2025

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Journal articles on the topic "Image de microscopie"

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Kinosita, K., H. Itoh, S. Ishiwata, K. Hirano, T. Nishizaka, and T. Hayakawa. "Dual-view microscopy with a single camera: real-time imaging of molecular orientations and calcium." Journal of Cell Biology 115, no. 1 (October 1, 1991): 67–73. http://dx.doi.org/10.1083/jcb.115.1.67.

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A new microscope technique, termed "W" (double view video) microscopy, enables simultaneous observation of two different images of an object through a single video camera or by eye. The image pair may, for example, be transmission and fluorescence, fluorescence at different wavelengths, or mutually perpendicular components of polarized fluorescence. Any video microscope can be converted into a dual imager by simple insertion of a small optical device. The continuous appearance of the dual image assures the best time resolution in existing and future video microscopes. As an application, orientations of actin protomers in individual, moving actin filaments have been imaged at the video rate. Asymmetric calcium influxes into a cell exposed to an intense electric pulse have also been visualized.
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Bouchon, Patrick, and Yannick de Wilde. "Rayonnement thermique infrarouge de nano-antennes plasmoniques individuelles." Photoniques, no. 105 (November 2020): 32–36. http://dx.doi.org/10.1051/photon/202010532.

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Nous exploitons les fluctuations thermiques pour étudier les résonances de nano-antennes plasmoniques métal-isolant-métal (MIM) individuelles dont les modes électromagnétiques sont excités en chauffant les nanostructures. La spectroscopie infrarouge par modulation spatiale permet de mesurer le spectre du rayonnement thermique de champ lointain d’une antenne unique en s’affranchissant de la contribution dominante du fond environnant. Des mesures de microscopie à effet tunnel à rayonnement thermique fournissent quant à elles une image super-résolue de la structure spatiale du rayonnement thermique de champ proche.
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Braat, J. "Calcul efficace de l'intensité image en microscopie confocale appliqué à la lecture d'un disque optique." Annales de Physique 24, no. 3 (1999): 31–42. http://dx.doi.org/10.1051/anphys:199903004.

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Wan, Xinjun, and Xuechen Tao. "Design of a Cell Phone Lens-Based Miniature Microscope with Configurable Magnification Ratio." Applied Sciences 11, no. 8 (April 9, 2021): 3392. http://dx.doi.org/10.3390/app11083392.

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Application of cell-phone-based microscopes has been hindered by limitations such as inferior image quality, fixed magnification and inconvenient operation. In this paper, we propose a reverse cell phone lens-based miniature microscope with a configurable magnification ratio. By switching the objectives of three camera lens and applying the digital zooming function of the cell phone, a cell phone microscope is built with the continuously configurable magnification ratio between 0.8×–11.5×. At the same time, the miniature microscope can capture high-quality microscopic images with a maximum resolution of up to 575 lp/mm and a maximum field of view (FOV) of up to 7213 × 5443 μm. Furthermore, by moving the tube lens module of the microscope out of the cell phone body, the built miniature microscope is as compact as a <20 mm side length cube, improving operational experience profoundly. The proposed scheme marks a big step forward in terms of the imaging performance and user operational convenience for cell phone microscopes.
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Jin, Lingbo, Yubo Tang, Yicheng Wu, Jackson B. Coole, Melody T. Tan, Xuan Zhao, Hawraa Badaoui, et al. "Deep learning extended depth-of-field microscope for fast and slide-free histology." Proceedings of the National Academy of Sciences 117, no. 52 (December 14, 2020): 33051–60. http://dx.doi.org/10.1073/pnas.2013571117.

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Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells—a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.
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Tetard, Martin, Ross Marchant, Giuseppe Cortese, Yves Gally, Thibault de Garidel-Thoron, and Luc Beaufort. "Technical note: A new automated radiolarian image acquisition, stacking, processing, segmentation and identification workflow." Climate of the Past 16, no. 6 (December 2, 2020): 2415–29. http://dx.doi.org/10.5194/cp-16-2415-2020.

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Abstract. Identification of microfossils is usually done by expert taxonomists and requires time and a significant amount of systematic knowledge developed over many years. These studies require manual identification of numerous specimens in many samples under a microscope, which is very tedious and time-consuming. Furthermore, identification may differ between operators, biasing reproducibility. Recent technological advances in image acquisition, processing and recognition now enable automated procedures for this process, from microscope image acquisition to taxonomic identification. A new workflow has been developed for automated radiolarian image acquisition, stacking, processing, segmentation and identification. The protocol includes a newly proposed methodology for preparing radiolarian microscopic slides. We mount eight samples per slide, using a recently developed 3D-printed decanter that enables the random and uniform settling of particles and minimizes the loss of material. Once ready, slides are automatically imaged using a transmitted light microscope. About 4000 specimens per slide (500 per sample) are captured in digital images that include stacking techniques to improve their focus and sharpness. Automated image processing and segmentation is then performed using a custom plug-in developed for the ImageJ software. Each individual radiolarian image is automatically classified by a convolutional neural network (CNN) trained on a Neogene to Quaternary radiolarian database (currently 21 746 images, corresponding to 132 classes) using the ParticleTrieur software. The trained CNN has an overall accuracy of about 90 %. The whole procedure, including the image acquisition, stacking, processing, segmentation and recognition, is entirely automated via a LabVIEW interface, and it takes approximately 1 h per sample. Census data count and classified radiolarian images are then automatically exported and saved. This new workflow paves the way for the analysis of long-term, radiolarian-based palaeoclimatic records from siliceous-remnant-bearing samples.
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Perrot, J. L., A. Biron, E. Couty, L. Tognetti, C. Couzan, R. Rossi, P. Rubegni, and E. Cinotti. "Premiers cas de corrélation parfaite à l’échelle cellulaire entre image de microscopie confocale in vivo et dermatoscopie." Annales de Dermatologie et de Vénéréologie 145, no. 12 (December 2018): S186. http://dx.doi.org/10.1016/j.annder.2018.09.261.

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Davidson, Michael W. "Pioneers in Optics: Joseph Jackson Lister and Maksymilian Pluta." Microscopy Today 19, no. 3 (April 28, 2011): 54–56. http://dx.doi.org/10.1017/s1551929511000277.

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Though microscopes and telescopes had been invented in the late sixteenth century, various optical difficulties meant that the devices were more commonly considered novelties than useful scientific instruments for many years. Chief among these problems were aberrations in the images caused by optical errors from the lenses. Many scientists had attempted to rectify such difficulties, but the nineteenth-century amateur microscopist Joseph Jackson Lister is credited with making some of the most important advances toward correcting image aberrations and establishing the microscope as a powerful means of carrying out serious scientific investigations.
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Chen, Xiaodong, Bin Zheng, and Hong Liu. "Optical and Digital Microscopic Imaging Techniques and Applications in Pathology." Analytical Cellular Pathology 34, no. 1-2 (2011): 5–18. http://dx.doi.org/10.1155/2011/150563.

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The conventional optical microscope has been the primary tool in assisting pathological examinations. The modern digital pathology combines the power of microscopy, electronic detection, and computerized analysis. It enables cellular-, molecular-, and genetic-imaging at high efficiency and accuracy to facilitate clinical screening and diagnosis. This paper first reviews the fundamental concepts of microscopic imaging and introduces the technical features and associated clinical applications of optical microscopes, electron microscopes, scanning tunnel microscopes, and fluorescence microscopes. The interface of microscopy with digital image acquisition methods is discussed. The recent developments and future perspectives of contemporary microscopic imaging techniques such as three-dimensional and in vivo imaging are analyzed for their clinical potentials.
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Jia Renqing, 贾仁庆, 殷高方 Yin Gaofang, 赵南京 Zhao Nanjing, 徐敏 Xu Min, 胡翔 Hu Xiang, 黄朋 Huang Peng, 梁天泓 Liang Tianhong, et al. "浮游藻类细胞显微多聚焦图像融合方法." Acta Optica Sinica 43, no. 12 (2023): 1210001. http://dx.doi.org/10.3788/aos222153.

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Dissertations / Theses on the topic "Image de microscopie"

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Toledo, Acosta Bertha Mayela. "Multimodal image registration in 2D and 3D correlative microscopy." Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S054/document.

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Cette thèse porte sur la définition d'un schéma de recalage automatique en microscopie corrélative 2D et 3D, en particulier pour des images de microscopie optique et électronique (CLEM). Au cours des dernières années, la CLEM est devenue un outil d'investigation important et puissant dans le domaine de la bio-imagerie. En utilisant la CLEM, des informations complémentaires peuvent être collectées à partir d'un échantillon biologique. La superposition des différentes images microscopiques est généralement réalisée à l'aide de techniques impliquant une assistance manuelle à plusieurs étapes, ce qui est exigeant et prend beaucoup de temps pour les biologistes. Pour faciliter et diffuser le procédé de CLEM, notre travail de thèse est axé sur la création de méthodes de recalage automatique qui soient fiables, faciles à utiliser et qui ne nécessitent pas d'ajustement de paramètres ou de connaissances complexes. Le recalage CLEM doit faire face à de nombreux problèmes dus aux différences entre les images de microscopie électronique et optique et leur mode d'acquisition, tant en termes de résolution du pixel, de taille des images, de contenu, de champ de vision et d'apparence. Nous avons conçu des méthodes basées sur l'intensité des images pour aligner les images CLEM en 2D et 3D. Elles comprennent plusieurs étapes : représentation commune des images LM et EM à l'aide de la transformation LoG, pré-alignement exploitant des mesures de similarité à partir d'histogrammes avec une recherche exhaustive, et un recalage fin basé sur l'information mutuelle. De plus, nous avons défini une méthode de sélection robuste de modèles de mouvement, et un méthode de détection multi-échelle de spots, que nous avons exploitées dans le recalage CLEM 2D. Notre schéma de recalage automatisé pour la CLEM a été testé avec succès sur plusieurs ensembles de données CLEM réelles 2D et 3D. Les résultats ont été validés par des biologistes, offrant une excellente perspective sur l'utilité de nos développements
This thesis is concerned with the definition of an automated registration framework for 2D and 3D correlative microscopy images, in particular for correlative light and electron microscopy (CLEM) images. In recent years, CLEM has become an important and powerful tool in the bioimaging field. By using CLEM, complementary information can be collected from a biological sample. An overlay of the different microscopy images is commonly achieved using techniques involving manual assistance at several steps, which is demanding and time consuming for biologists. To facilitate and disseminate the CLEM process for biologists, the thesis work is focused on creating automatic registration methods that are reliable, easy to use and do not require parameter tuning or complex knowledge. CLEM registration has to deal with many issues due to the differences between electron microscopy and light microscopy images and their acquisition, both in terms of pixel resolution, image size, content, field of view and appearance. We have designed intensity-based methods to align CLEM images in 2D and 3D. They involved a common representation of the LM and EM images using the LoG transform, a pre-alignment step exploiting histogram-based similarities within an exhaustive search, and a fine mutual information-based registration. In addition, we have defined a robust motion model selection method, and a multiscale spot detection method which were exploited in the 2D CLEM registration. Our automated CLEM registration framework was successfully tested on several real 2D and 3D CLEM datasets and the results were validated by biologists, offering an excellent perspective in the usefulness of our methods
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Denimal, Emmanuel. "Détection de formes compactes en imagerie : développement de méthodes cumulatives basées sur l'étude des gradients : Applications à l'agroalimentaire." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCK006/document.

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Les cellules de comptage (Malassez, Thoma …) sont conçues pour permettre le dénombrement de cellules sous microscope et la détermination de leur concentration grâce au volume calibré de la grille apparaissant dans l’image microscopique. Le comptage manuel présente des inconvénients majeurs : subjectivité, non-répétabilité… Il existe des solutions commerciales de comptage automatique dont l’inconvénient est de nécessiter un environnement bien contrôlé qu’il n’est pas possible d’obtenir dans le cadre de certaines études (ex. : le glycérol influe grandement sur la qualité des images). L’objectif du projet est donc double : un comptage des cellules automatisé et suffisamment robuste pour être réalisable, quelles que soient les conditions d’acquisition.Dans un premier temps, une méthode basée sur la transformée de Fourier a été développée pour détecter, caractériser et effacer la grille de la cellule de comptage. Les caractéristiques de la grille extraites par cette méthode servent à déterminer une zone d’intérêt et son effacement permet de faciliter la détection des cellules à compter.Pour réaliser le comptage, la problématique principale est d’obtenir une méthode de détection des cellules suffisamment robuste pour s’adapter aux conditions d’acquisition variables. Les méthodes basées sur les accumulations de gradients ont été améliorées par l’adjonction de structures permettant une détection plus fine des pics d’accumulation. La méthode proposée permet une détection précise des cellules et limite l’apparition de faux positifs.Les résultats obtenus montrent que la combinaison de ces 2 méthodes permet d’obtenir un comptage répétable et représentatif d’un consensus des comptages manuels réalisés par des opérateurs
The counting cells (Malassez, Thoma ...) are designed to allow the enumeration of cells under a microscope and the determination of their concentration thanks to the calibrated volume of the grid appearing in the microscopic image. Manual counting has major disadvantages: subjectivity, non-repeatability ... There are commercial automatic counting solutions, the disadvantage of which is that a well-controlled environment is required which can’t be obtained in certain studies ( eg glycerol greatly affects the quality of the images ). The objective of the project is therefore twofold: an automated cell count and sufficiently robust to be feasible regardless of the acquisition conditions.In a first step, a method based on the Fourier transform has been developed to detect, characterize and erase the grid of the counting cell. The characteristics of the grid extracted by this method serve to determine an area of interest and its erasure makes it easier to detect the cells to count.To perform the count, the main problem is to obtain a cell detection method robust enough to adapt to the variable acquisition conditions. The methods based on gradient accumulations have been improved by the addition of structures allowing a finer detection of accumulation peaks. The proposed method allows accurate detection of cells and limits the appearance of false positives.The results obtained show that the combination of these two methods makes it possible to obtain a repeatable and representative count of a consensus of manual counts made by operators
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Moisan, Frédéric. "Optimisation du contraste image en microscopie optique : application à l'inspection microélectronique." Grenoble 1, 1988. http://tel.archives-ouvertes.fr/tel-00331501.

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Dans le domaine de l'inspection visuelle automatique de circuits intégrés, le contraste des images est un paramètre important. La méthode d'optimisation proposée utilise l'effet des variations de réflexion optique en fonction de la longueur d'onde pour les structures de couches minces. Elle consiste a déterminer le filtrage en longueur d'onde optimisant un "facteur de qualité" de l'image (taux de la dynamique de la camera) à partir des spectres de réflexion des différentes structures présentés sur la plaquette. L'étude est limitée au cas des circuits intégrés à 2 structures, mais l'extension a un nombre quelconque est possible. Les différents moyens d'obtention des spectres de réflexion sont précisés. Des mesures photométriques démontrent la fiabilité de la méthode proposée. Un appareillage optique original permet l'application dans le cadre d'une machine d'inspection automatique
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Moisan, Frédéric. "Optimisation du contraste image en microscopie optique application à l'inspection microélectronique /." Grenoble 2 : ANRT, 1988. http://catalogue.bnf.fr/ark:/12148/cb37616602c.

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Moisan, Frédéric Courtois Bernard. "Optimisation du contraste image en microscopie optique application à l'inspection microélectronique /." S.l. : Université Grenoble 1, 2008. http://tel.archives-ouvertes.fr/tel-00331501.

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Jezierska, Anna Maria. "Image restoration in the presence of Poisson-Gaussian noise." Phd thesis, Université Paris-Est, 2013. http://tel.archives-ouvertes.fr/tel-00906718.

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This thesis deals with the restoration of images corrupted by blur and noise, with emphasis on confocal microscopy and macroscopy applications. Due to low photon count and high detector noise, the Poisson-Gaussian model is well suited to this context. However, up to now it had not been widely utilized because of theoretical and practical difficulties. In view of this, we formulate the image restoration problem in the presence of Poisson-Gaussian noise in a variational framework, where we express and study the exact data fidelity term. The solution to the problem can also be interpreted as a Maximum A Posteriori (MAP) estimate. Using recent primal-dual convex optimization algorithms, we obtain results that outperform methods relying on a variety of approximations. Turning our attention to the regularization term in the MAP framework, we study both discrete and continuous approximation of the $ell_0$ pseudo-norm. This useful measure, well-known for promoting sparsity, is difficult to optimize due to its non-convexity and its non-smoothness. We propose an efficient graph-cut procedure for optimizing energies with truncated quadratic priors. Moreover, we develop a majorize-minimize memory gradient algorithm to optimize various smooth versions of the $ell_2-ell_0$ norm, with guaranteed convergence properties. In particular, good results are achieved on deconvolution problems. One difficulty with variational formulations is the necessity to tune automatically the model hyperparameters. In this context, we propose to estimate the Poisson-Gaussian noise parameters based on two realistic scenarios: one from time series images, taking into account bleaching effects, and another from a single image. These estimations are grounded on the use of an Expectation-Maximization (EM) approach.Overall, this thesis proposes and evaluates various methodologies for tackling difficult image noise and blur cases, which should be useful in various applicative contexts within and beyond microscopy
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Le, Floch Hervé. "Acquisition des images en microscopie electronique a balayage in situ." Toulouse 3, 1986. http://www.theses.fr/1986TOU30026.

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Chaine d'acquisition du signal image du mebis. Etude des sources de bruit associees aux detecteurs a semiconducteur et mise au point d'un processus de realisation de diodes de detection a barriere de surface. Conception d'une carte electronique compatible avec un microordinateur. Cette carte permet la numerisation, le stockage sur disquette et la visualisation des images fournies par le mebis
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Henrot, Simon. "Déconvolution et séparation d'images hyperspectrales en microscopie." Electronic Thesis or Diss., Université de Lorraine, 2013. http://www.theses.fr/2013LORR0187.

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L'imagerie hyperspectrale consiste à acquérir une scène spatiale à plusieurs longueurs d'onde, e.g. en microscopie. Cependant, lorsque l'image est observée à une résolution suffisamment fine, elle est dégradée par un flou (convolution) et une procédure de déconvolution doit être utilisée pour restaurer l'image originale. Ce problème inverse, par opposition au problème direct modélisant la dégradation de l'image observée, est étudié dans la première partie . Un autre problème inverse important en imagerie, la séparation de sources, consiste à extraire les spectres des composants purs de l'image (sources) et à estimer les contributions de chaque source à l'image. La deuxième partie propose des contributions algorithmiques en restauration d'images hyperspectrales. Le problème est formulé comme la minimisation d'un critère pénalisé et résolu à l'aide d'une structure de calcul rapide. La méthode est adaptée à la prise en compte de différents a priori sur l'image, tels que sa positivité ou la préservation des contours. Les performances des techniques proposées sont évaluées sur des images de biocapteurs bactériens en microscopie confocale de fluorescence. La troisième partie est axée sur le problème de séparation de sources, abordé dans un cadre géométrique. Nous proposons une nouvelle condition suffisante d'identifiabilité des sources à partir des coefficients de mélange. Une étude innovante couplant le modèle d'observation avec le mélange de sources permet de montrer l'intérêt de la déconvolution comme étape préliminaire de la séparation. Ce couplage est validé sur des données acquises en spectroscopie Raman
Hyperspectral imaging refers to the acquisition of spatial images at many spectral bands, e.g. in microscopy. Processing such data is often challenging due to the blur caused by the observation system, mathematically expressed as a convolution. The operation of deconvolution is thus necessary to restore the original image. Image restoration falls into the class of inverse problems, as opposed to the direct problem which consists in modeling the image degradation process, treated in part 1 of the thesis. Another inverse problem with many applications in hyperspectral imaging consists in extracting the pure materials making up the image, called endmembers, and their fractional contribution to the data or abundances. This problem is termed spectral unmixing and its resolution accounts for the nonnegativity of the endmembers and abundances. Part 2 presents algorithms designed to efficiently solve the hyperspectral image restoration problem, formulated as the minimization of a composite criterion. The methods are based on a common framework allowing to account for several a priori assumptions on the solution, including a nonnegativity constraint and the preservation of edges in the image. The performance of the proposed algorithms are demonstrated on fluorescence confocal images of bacterial biosensors. Part 3 deals with the spectral unmixing problem from a geometrical viewpoint. A sufficient condition on abundance coefficients for the identifiability of endmembers is proposed. We derive and study a joint observation model and mixing model and demonstrate the interest of performing deconvolution as a prior step to spectral unmixing on confocal Raman microscopy data
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Henrot, Simon. "Déconvolution et séparation d'images hyperspectrales en microscopie." Phd thesis, Université de Lorraine, 2013. http://tel.archives-ouvertes.fr/tel-00931579.

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L'imagerie hyperspectrale consiste à acquérir une scène spatiale à plusieurs longueurs d'onde, de manière à reconstituer le spectre des pixels. Cette technique est utilisée en microscopie pour extraire des informations spectrales sur les spécimens observés. L'analyse de telles données est bien souvent difficile : lorsque l'image est observée à une résolution suffisamment fine, elle est dégradée par l'instrument (flou ou convolution) et une procédure de déconvolution doit être utilisée pour restaurer l'image originale. On parle ainsi de problème inverse, par opposition au problème direct consistant à modéliser la dégradation de l'image observée, étudié dans la première partie de la thèse. Un autre problème inverse important en imagerie consiste à extraire les signatures spectrales des composants purs de l'image ou sources et à estimer les contributions fractionnaires de chaque source à l'image. Cette procédure est qualifiée de séparation de sources, accomplie sous contrainte de positivité des sources et des mélanges. La deuxième partie propose des contributions algorithmiques en restauration d'images hyperspectrales. Le problème de déconvolution est formulé comme la minimisation d'un critère pénalisé et résolu à l'aide d'une structure de calcul rapide. Cette méthode générique est adaptée à la prise en compte de différents a priori sur la solution, tels que la positivité de l'image ou la préservation des contours. Les performances des techniques proposées sont évaluées sur des images de biocapteurs bactériens en microscopie confocale de fluorescence. La troisième partie de la thèse est axée sur la problématique de séparation de sources, abordé dans un cadre géométrique. Nous proposons une nouvelle condition suffisante d'identifiabilité des sources à partir des coefficients de mélange. Une étude innovante couplant le modèle d'observation instrumental avec le modèle de mélange de sources permet de montrer l'intérêt de la déconvolution comme étape préliminaire de la séparation. Ce couplage est validé sur des données acquises en microscopie confocale Raman.
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Sibarita, Jean-Baptiste. "Formation et restauration d'images en microscopie à rayons : application à l'observation d'échantillons biologiques." Phd thesis, Université Joseph Fourier (Grenoble), 1996. http://tel.archives-ouvertes.fr/tel-00345364.

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Technique récente, la microscopie à rayons X offre aujourd'hui une résolution spatiale supérieure à celle de la microscopie optique (20 nm contre 200 nm en microscopie optique confocal laser). Elle offre également un meilleur pouvoir de pénétration que la microscopie électronique (jusqu'à 10 μm contre 1 μm en microscopie électronique à moyenne et haute tension). Ainsi, la microscopie à rayons X mous (longueurs d'onde comprises entre 2,4 et 4,3 nanomètres) permet l'analyse à haute résolution en 2 ou 3 dimensions d'échantillons biologiques placés dans des conditions proches de leur milieu naturel (contrairement aux microscopes électroniques classiques qui imposent une préparation des échantillons). Cependant, la réduction de la dose absorbée par l'échantillon nécessite des durées d'expositions aussi courtes que possible. Or, effectuer une acquisition avec peu de photons se fait au détriment du rapport signal sur bruit des images. Un de nos objectifs a été le développement d'outils pour l'amélioration et la restauration de ces images. La première partie de nos travaux a consisté à déterminer la fonction de transfert du microscope à rayons X en transmission et à comparer les résultats obtenus avec le modèle théorique de la formation des images. Dans la seconde partie, nous avons complété les modèles existants liant le nombre de photons et le contraste, en prenant en compte le mode de formation des images dans le microscope. La troisième partie de ces travaux concerne le développement de techniques de traitement numérique des images dans le but d'améliorer et de restaurer des images obtenues par microscopie à rayons X avec de faibles temps d'exposition. Ces processus ont été appliqués à l'étude par microscopie à rayons X de différents types d'échantillons biologiques
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Books on the topic "Image de microscopie"

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Reimer, Ludwig. Scanning electron microscopy: Physics of image formation and microanalysis. 2nd ed. Berlin: Springer, 1998.

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R, Wootton, Springall D. R, and Polak Julia M, eds. Image analysis in histology: Conventional and confocal microscopy. Cambridge: Published in association with the Royal Postgraduage Medical School, University of London by Cambridge University Press, 1995.

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Lynette, Ruschak, ed. Magnification: A pop-up lift-the-flap book. New York: Lodestar Books, 1993.

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Reimer, Ludwig. Transmission electron microscopy: Physics of image formation and microanalysis. 2nd ed. Berlin: Springer-Verlag, 1989.

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1958-, Wu Qiang, Merchant Fatima, and Castleman Kenneth R, eds. Microscope image processing. Amsterdam: Academic Press, 2008.

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1949-, Williams David B., Pelton Alan R, and Gronsky R, eds. Images of materials. New York: Oxford University Press, 1991.

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Harmuth, Henning F. Dirac's difference equation and the physics of finite differences. Amsterdam: Academic Press, 2008.

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Witkin, Joan. Histology atlas of microscopic images. New York, N.Y.]: [Columbia University Health Sciences], 2003.

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Jens, Rittscher, Machiraju Raghu, and Wong Stephen T. C, eds. Microscopic image analysis for life science applications. Boston [Mass.}: Artech House, 2008.

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Chen, Liang-Chia, Guo-Wei Wu, Sanjeev Kumar Singh, and Wei-Hsin Chein. Diffractive Image Microscopy for 3D Imaging. Singapore: Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-7782-2.

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Book chapters on the topic "Image de microscopie"

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Cinquin, Bertrand, Joyce Y. Kao, and Mark L. Siegal. "i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster." In Bioimage Data Analysis Workflows ‒ Advanced Components and Methods, 147–74. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-76394-7_7.

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AbstractMany of the methods developed for the analysis of bioimages focus on microscopy images on the cellular level. However, bioimages can also be used by biologists to assess non-cellular level morphological phenotypes. Collecting non-cellular images and developing image workflows for them is similar to working with microscopic images, but also has its unique challenges.
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Nakanishi, Tomoko M. "Real-Time Element Movement in a Plant." In Novel Plant Imaging and Analysis, 109–68. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4992-6_4.

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AbstractWe developed an imaging method utilizing the available RIs. We developed two types of real-time RI imaging systems (RRIS), one for macroscopic imaging and the other for microscopic imaging. The principle of visualization was the same, converting the radiation to light by a Cs(Tl)I scintillator deposited on a fiber optic plate (FOS). Many nuclides were employed, including 14C, 18F, 22Na, 28Mg, 32P 33P, 35S, 42K, 45Ca, 48V, 54Mn, 55Fe, 59Fe, 65Zn, 86Rb, 109Cd, and 137Cs.Since radiation can penetrate the soil as well as water, the difference between soil culture and water culture was visualized. 137Cs was hardly absorbed by rice roots growing in soil, whereas water culture showed high absorption, which could provide some reassurance after the Fukushima Nuclear Accident and could indicate an important role of soil in firmly adsorbing the radioactive cesium.28Mg and 42K, whose production methods were presented, were applied for RRIS to visualize the absorption image from the roots. In addition to 28Mg and 42K, many nuclides were applied to image absorption in the roots. Each element showed a specific absorption speed and accumulation pattern. The image analysis of the absorption of Mg is presented as an example. Through successive images of the element absorption, phloem flow in the aboveground part of the plant was analyzed. The element absorption was visualized not only in the roots but also in the leaves, a basic study of foliar fertilization.In the case of the microscopic imaging system, a fluorescence microscope was modified to acquire three images at the same time: a light image, fluorescent image, and radiation image. Although the resolution of the image was estimated to be approximately 50 μm, superposition showed the expression site of the transporter gene and the actual 32P-phosphate absorption site to be the same in Arabidopsis roots.
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Kumar, Amit, Fahimuddin Shaik, B. Abdul Rahim, and D. Sravan Kumar. "Image Enhancement of Leukemia Microscopic Images." In Signal and Image Processing in Medical Applications, 17–37. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0690-6_4.

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Carlton, Robert Allen. "Image Analysis." In Pharmaceutical Microscopy, 173–211. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8831-7_7.

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Inoué, Shinya, and Kenneth R. Spring. "Microscope Image Formation." In Video Microscopy, 13–117. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-5859-0_2.

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Inoué, Shinya. "Microscope Image Formation." In Video Microscopy, 93–148. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4757-6925-8_5.

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Bright, D. S., D. E. Newbury, R. B. Marinenko,, E. B. Steel,, and R. L. Myklebust. "Processing Images and Selecting Regions of Interest." In Images Of Materials, 309–37. Oxford University PressNew York, NY, 1992. http://dx.doi.org/10.1093/oso/9780195058567.003.0011.

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Abstract Over the past decade, the development of laboratory computers has made possible the application of digital imaging techniques to a wide variety of photon, electron, and ion microscopes. Characterization of the microstructure of materials by these microscopy techniques can provide information on morphology, crystal structure, and elemental or molecular chemistry on a spatial scale ranging from micrometers to nanometers. Traditionally, image information from these microscopes was recorded exclusively by analog means such as film. The added dimension of digital imaging, where the image is recorded directly as digitized arrays of signals derived from detectors or is digitized from previously recorded analog images, gives the microscopist/analyst access to a powerful and wide-ranging suite of tools for the acquisition, enhancement, and interpretation of information derived from the microscope. Many of these tools were impractical or impossible in the realm of analog image manipulation. A second burst of development in the digital imaging field is now taking place with the advent of “computer-aided microscopy.” Computer-aided microscopy augments conventional digital imaging techniques with algorithms adapted from various fields of computer science. The aim of this approach is to develop tools that can function automatically to carry out image-analysis tasks that are too complex or time consuming to permit conventional interpretation by direct viewing of the image on a screen.
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Orchard, Guy. "Light microscopy and digital pathology." In Histopathology, edited by Guy Orchard and Brian Nation. Oxford University Press, 2017. http://dx.doi.org/10.1093/hesc/9780198717331.003.0014.

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This chapter examines light microscopy and digital pathology. The principle behind the light microscope is to provide a magnified image of the sample of interest such that what is happening to the samples can be seen at a scale which the eyes alone could not perceive. It is not enough, however, simply to provide a large image of a specimen, as a simple magnifying lens would. Biomedical scientists are typically interested in quite small and fine detailed structures so it is important that the microscopic image contains sufficient resolution of fine detail. The chapter then looks at the compound microscope, phase contrast microscope, polarization microscope, darkfield microscope, fluorescence microscope, and confocal microscopy.
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M, Dr Leo Caroline, Dr Nachiammai N, Dr Harini Priya A.H, and Dr R. Sathish Muthukumar. "FLUORESCENCE MICROSCOPE." In Emerging Trends in Oral Health Sciences and Dentistry. Technoarete Publishers, 2022. http://dx.doi.org/10.36647/etohsd/2022.01.b1.ch030.

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Microscopes are paramount invention in the field of science, which enabled to observe the invisible world around us. Till date different microscopes have been designed to fulfil various purposes. Fluorescence microscope is an advanced microscopic technique which uses the phenomenon of fluorescence to create an image of the specimen. Fluorescence microscope forms an essential part in various molecular techniques. This review explains the principle and working mechanism of fluorescence microscope.
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Howell, Gareth, and Kyle Dent. "Bioimaging: light and electron microscopy." In Tools and Techniques in Biomolecular Science. Oxford University Press, 2013. http://dx.doi.org/10.1093/hesc/9780199695560.003.0017.

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This chapter discusses the use of light and electron microscopy techniques to image biological structures. Bioimaging enables the visualization of different biological processes such as protein transport, the development or effect of disease, and mutations on a cellular and subcellular scale, and provides structural information on cells, organelles, and individual macromolecular complexes. The chapter looks at the technologies commonly used in studying cells and protein structures such as confocal microscopy, deconvolution microscopy, transmission electron microscopy, and scanning electron microscopy. It describes the basic structure of different microscopes and gives an overview of how images are generated and visualized. Furthermore, the discussion covers the common applications of these microscope technologies in modern biological research. It also explores correlative light electron microscopy, a technique that combines fluorescence microscopy and transmission electron microscopy to produce high-resolution images that include localized fluorescence information specific to the protein of interest.
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Conference papers on the topic "Image de microscopie"

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Blochet, Baptiste, and Marc Guillon. "Single-shot phase and polarimetric microscopy." In 3D Image Acquisition and Display: Technology, Perception and Applications, JF2A.2. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/3d.2024.jf2a.2.

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Bueno, Gloria, Jesus Ruiz-Santaquiteria, Noelia Vallez, Jesus Salido, Gabriel Cristóbal, and Oscar Deniz. "Telemicroscopy system applied to digital microscopy with a low-cost automated microscope." In Applications of Digital Image Processing XLVII, edited by Andrew G. Tescher and Touradj Ebrahimi, 1. SPIE, 2024. http://dx.doi.org/10.1117/12.3028227.

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Galliopoulou, Eirini C., Christopher Jones, Lawrence Coghlan, Mariia Zimina, Tomas L. Martin, Peter E. J. Flewitt, Alan Cocks, John Siefert, and Jonathan D. Parker. "Creep Cavitation Imaging and Analysis in 9%Cr-1%Mo P91 Steels." In AM-EPRI 2024, 219–34. ASM International, 2024. http://dx.doi.org/10.31399/asm.cp.am-epri-2024p0219.

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Abstract The current research adopts a novel approach by integrating correlative microscopy and machine learning in order to study creep cavitation in an ex-service 9%Cr 1%Mo Grade 91 ferritic steel. This method allows for a detailed investigation of the early stages of the creep life, enabling identification of features most prone to damage such as precipitates and the ferritic crystal structure. The microscopy techniques encompass Scanning Electron Microscopy (SEM) imaging and Electron Back-scattered Diffraction (EBSD) imaging, providing insights into the two-dimensional distribution of cavitation. A methodology for acquiring and analysing serial sectioning data employing a Plasma Focused Ion Beam (PFIB) microscope is outlined, complemented by 3D reconstruction of backscattered electron (BSE) images. Subsequently, cavity and precipitate segmentation was performed with the use of the image recognition software, DragonFly and the results were combined with the 3D reconstruction of the material microstructure, elucidating the decoration of grain boundaries with precipitation, as well as the high correlation of precipitates and grain boundaries with the initiation of creep cavitation. Comparison between the 2D and 3D results is discussed.
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Ozcan, Aydogan. "Virtual Staining of Label-free Tissue." In Frontiers in Optics, FM3D.1. Washington, D.C.: Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.fm3d.1.

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We will cover deep learning-based virtual staining techniques that can generate different types of histological stains from label-free microscopic images of unstained samples by using, e.g., autofluorescence microscopy, quantitative phase imaging and reflectance confocal microscopy. Full-text article not available; see video presentation
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Stegmann, Heiko, and Flavio Cognigni. "Few-Shot AI Segmentation of Semiconductor Device FIB-SEM Tomography Data." In ISTFA 2024, 13–21. ASM International, 2024. http://dx.doi.org/10.31399/asm.cp.istfa2024p0013.

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Abstract Image segmentation is a valuable tool for visual image data inspection of semiconductor device structures. For the large amounts of data provided by recent advancements in automated scanning electron microscope (SEM) and focused ion beam-scanning electron microscope (FIB-SEM) data acquisition, automatic segmentation becomes indispensable to fully exploit the information contained in the data in automated characterization workflows. Using two exemplary FIB-SEM tomography datasets, we explored artificial intelligence based image segmentation using only a minimum amount of training images annotated by a human user.
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Kurumundayil, Leslie, Theresa Trötschler, Jonas Schönauer, Doga Can Öner, Stefan Rein, and Matthias Demant. "Microscopic Image Analysis of Printed Structures Without a Microscope: A Deep Learning Approach." In 2024 IEEE 52nd Photovoltaic Specialist Conference (PVSC), 0802–4. IEEE, 2024. http://dx.doi.org/10.1109/pvsc57443.2024.10749537.

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Khoubafarin, Somaiyeh, Peuli Nath, Hannah Popofski, and Aniruddha Ray. "High resolution Multi-Modal Microscopy using Microlens Substrates." In CLEO: Applications and Technology, ATu4B.1. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_at.2024.atu4b.1.

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The resolution of optical microscopes is limited by the numerical aperture of objective lens. We introduced a cost-effective microlens substrate for multimodal optical microscopy, that enables imaging beyond the diffraction limit, which was used to image mammalian cells and tissues.
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Incardona, Nicolo, Angel Tolosa, Gabriele Scrofani, Manuel Martinez-Corral, and Genaro Saavedra. "The Lightfield Eyepiece: an Add-on for 3D Microscopy." In 3D Image Acquisition and Display: Technology, Perception and Applications. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/3d.2022.3tu5a.6.

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Fourier lightfield microscopy is an emerging technique for real-time acquisition of three-dimensional microscopic samples. Here, we present the lightfield eyepiece, an add-on device capable of converting any conventional microscope to a Fourier lightfield microscope.
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Xing, Z. G., C. M. Zhao, J. Wei, and Z. Wei. "3D Reconstruction Based on Single Defocused Microscopic Image." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-86644.

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Microscope has being limited by the depth of focus, while the focused image is clear, the defocused images are fuzzy and fuzzy degree of the object images vary with different defocused distances. This paper presented a 3D reconstruction method based on a defocused microscopic image. After the defocused microscopic image is divided the microscopic into M × N regions, the fuzzy degree of each region is quantitatively evaluated. A corresponding curve of the relation between fuzzy degree and defocus distance is drawn by the presented algorithm in this paper, and then the three-dimensional characteristics of objects are reconstructed. This method has the merits of little computation, low cost and high speed. And M and N values can be changed according to the needs of the measurement accuracy.
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Chao, S. H., M. R. Holl, J. H. Koschwanez, R. H. Carlson, L. S. Jang, and D. R. Meldrum. "Velocity Measurements in Microchannels With a Laser Scanning Microscope and Particle Linear Image Velocimetry." In ASME 2004 2nd International Conference on Microchannels and Minichannels. ASMEDC, 2004. http://dx.doi.org/10.1115/icmm2004-2432.

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A novel velocity measurement method for microscale flow field characterization is reported, particle linear image velocimetry (PLIV). The method records a series of one-dimensional images that represent the trace of particles in the flow across a one-dimensional imager. Linear imaging results in a faster frame rate than planar imaging, allowing observation of larger microscope magnification or measurement of faster flow rates in real-time than comparable techniques. In contrast to particle image velocimetry (PIV), PLIV does not require high-speed cameras or shutters. Furthermore, PLIV is adaptable to multiple linear imager formats and, as one example, can use laser scanning confocal microscopes (LSCM) that acquire images slowly but with high spatial resolutions and optical sectioning ability. Higher resolution can be obtained for flows where in-plane velocity gradient in the direction of the optical path (z-direction) is important. This paper presents the PLIV algorithm, and demonstrates its utility by measuring Poiseuille flow with 1-μm resolution in a microfluidic environment.
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Reports on the topic "Image de microscopie"

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Greaves, C., and J. B. R. Eamer. Focus stacking for cataloguing, presentation, and identification of microfossils in marine sediments. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331355.

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Microfossils represent an important part of studying past depositional environments and determining ages for the strata they are found within. The key to ascribing paleoenvironmental interpretations to the sediments in which a microfossil is found is accurate identification of the microfossil. A number of techniques can be used to identify microfossils, including ones that use key features, morphologies, and characteristics from imagery acquired using a scanning electron microscope. A low-cost, efficient alternative method is digital photography of optical microscope images. This technical note presents a method for acquiring photos of microfossils and two methods for compiling them into high-resolution images using focus stacking. The process is described in four main steps: image acquisition, exportation, focus stacking, and annotation.
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Moon, Bill. Employment of Crystallographic Image Processing Techniques to Scanning Probe Microscopy Images of Two-Dimensional Periodic Objects. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.699.

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Pennycook, S. J., and A. R. Lupini. Image Resolution in Scanning Transmission Electron Microscopy. Office of Scientific and Technical Information (OSTI), June 2008. http://dx.doi.org/10.2172/939888.

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Dabros, M. J., and P. J. Mudie. An Automated Microscope System For Image Analysis in Palynology and Micropaleontology. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/120356.

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Salapaka, Srinivasa M., and Petros G. Voulgaris. Fast Scanning and Fast Image Reconstruction in Atomic Force Microscopy. Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada495364.

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Bajcsy, Peter, and Nathan Hotaling. Interoperability of web computational plugins for large microscopy image analyses. Gaithersburg, MD: National Institute of Standards and Technology, March 2020. http://dx.doi.org/10.6028/nist.ir.8297.

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Wendelberger, James G. Localized Similar Image Texture in Images of Sample Laser Confocal Microscope for Area: FY15 DE07 SW C1 Zone 1 & 2 Section b. Office of Scientific and Technical Information (OSTI), February 2019. http://dx.doi.org/10.2172/1496724.

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Bolgert, Peter J. A Comparison of Image Quality Evaluation Techniques for Transmission X-Ray Microscopy. Office of Scientific and Technical Information (OSTI), August 2012. http://dx.doi.org/10.2172/1049731.

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Głąb, Tomasz, Jarosław Knaga, Tomasz Zaleski, Paweł Dziwisz, Jan Gluza, and Dariusz Glanas. Determination of soil particle size distribution using computer analysis of microscopic images. Publishing House of the University of Agriculture in Krakow, 2025. https://doi.org/10.15576/repourk/2025.1.3.

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The project aims to develop a prototype device for determining the texture of soils and mineral deposits. The innovation of the designed solution consists in a significant reduction in the time of composition analysis with the possibility of any division into granulometric groups and the complete automation of the measurement from the moment the sample is introduced into the apparatus until the result is obtained. As part of the project, industrial research and experimental development are planned to be divided into the following stages: 1. Development of the measuring system. 2. Development of the structure and construction of device prototypes. 3. Development of the construction of the measuring system 4. Development of a mathematical model for processing data from the measuring system. 5. Preparation of software for device control and data recording. 6. Making the final prototype of the device. 7. Test tests of the final version of the device. The research will be conducted by a research consortium consisting of the project leader, i.e. Aumatic sp. z o.o. and the University of Agriculture in Krakow. The developed product will be intended for sale both on the domestic market and for export. Due to the number of entities potentially interested in the apparatus and the financial possibilities of potential recipients, the largest market should be developed countries (e.g. EU countries, USA, Canada, etc.). The main target groups of clients were: 1. Scientific institutions (universities, research institutes). 2. Institutions and enterprises performing analyzes for the needs of precision farming. 3. Chemical and Agricultural Stations. 4. Ceramic clay mining plants. 5. Manufacturers of ceramic products. 6. Laboratories conducting geotechnical tests for the needs of construction. 7. Laboratories carrying out environmental tests in the field of soil quality. 8. Provincial Inspectorates for Environmental Protection, Regional Directorates for Environmental Protection
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Wendelberger, James. Template size and proper overlap detection in Laser Confocal Microscope (LCM) images. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1812643.

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