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Journal articles on the topic 'Image de microscopie'
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1
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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Crutcher, Russ, and Heidie Crutcher. "How We See: The Light Microscope, Visual Routines, and the Microscopist." Microscope 69, no. 4 (2022): 147–59. http://dx.doi.org/10.59082/iwig3530.
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This paper addresses three critical aspects of analysis using the light microscope: 1) the human visual system, 2) the versatility of the light microscope, and 3) the importance of training and visual routines. The image of a particle produced by the light microscope is only an image, but it reveals important information about the shape, chemistry, and ontology of the particle. Changing the configuration of the microscope alters the image and provides additional information about the particle itself. While other analytical equipment generates graphs, tables, and charts, the microscope generates an image in the eye and brain of the microscopist. The microscopist is the detector for the microscope and the analyst of the signal generated by the detector. This is a two-part process. A fitting analogy is the concept of visual routines as used in the fields of computer vision and artificial intelligence. It refers to program modules that take raw images and process them into something intelligible. The term visual routines is being used here in this paper to address the relationship between the image generated by the retina, mental manipulation of the image, and by a specific configuration of the microscope. The microscopist needs to be trained to appreciate the analytical significance of different images of an object as the illumination system is changed. The addition of two polarizing filters to a transmitted brightfield image is one example. Understanding the light microscope as a sophisticated optical bench is part of the approach. Polarized light microscopy (PLM) and phase contrast microscopy (PCM) are limiting configurations but useful as two tools in the microscopist’s toolbox. There are many more transmitted light systems before even considering reflected light systems. An optimized light microscope is equipped with both a transmitted and reflected light system.
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Prakash, S. Saravana, and S. Pravin Kumar. "Mobile Recording Microscope." International Journal of Advance Research and Innovation 3, no. 4 (2015): 4–7. http://dx.doi.org/10.51976/ijari.341502.
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Microscope is an important diagnostic tool used widely in Science Technology. The widespread use of this tool can be seen in Medicine, Nuclear Sciences, and Education etc. Several attempts are being carried out to make microscopes easy to handle and user friendly. One such approach is the Mobile Recording Microscope which can be built using a simple smart phone. Unlike conventional microscopes, the mobile recording microscope uses the camera integrated in smart phones to record images. This reduces the efforts needed to store and transfer the recorded data. The replacement of wired medium and computer for recording images reduces the cost, space and difficulties incurred in use of microscopic devices. The hand-held smart phone for recording images assures anywhere and anytime use of the microscope. These advantages favour common man to use it independently without the assistance of a skilled person.
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Jester, J. V., H. D. Cavanagh, and M. A. Lemp. "In vivo confocal imaging of the eye using tandem scanning confocal microscopy (TSCM)." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 56–57. http://dx.doi.org/10.1017/s0424820100102365.
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New developments in optical microscopy involving confocal imaging are now becoming available which dramatically increase resolution, contrast and depth of focus by optically sectioning through structures. The transparency of the anterior ocular structures, cornea and lens, make microscopic visualization and optical sectioning of the living intact eye an interesting possibility. Of the confocal microscopes available, the Tandem Scanning Reflected Light Microscope (referred to here as the Tandem Scanning Confocal Microscope), developed by Professors Petran and Hadravsky at Charles University in Pilzen, Czechoslovakia, permits real-time image acquisition and analysis facilitating in vivo studies of ocular structures.Currently, TSCM imaging is most successful for the cornea. The corneal epithelium, stroma, and endothelium have been studied in vivo and photographed in situ. Confocal scanning images of the superficial epithelium, similar to those obtained by scanning electron microscopy, show both light and dark surface epithelial cells.
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Fraundorf, P., and B. Armbruster. "Scanned-probe microscope roughness spectroscopy." Proceedings, annual meeting, Electron Microscopy Society of America 51 (August 1, 1993): 530–31. http://dx.doi.org/10.1017/s0424820100148484.
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Air based scanning tunneling and scanning force microscopes are capable of producing images very easily, but oft-times that is all that they produce. Since microscopic regions of specimens of course differ in detail from one to another, often judgements about how two regions differ fundamentally are left to qualitative intuition. Given a quarter of a million numbers, in the case of a typical large SPM image, we should be able to quantitatively compare the statistical properties evidenced therein from one specimen to another. Such quantitative insight may also yield information on artifacts (like timedomain noise and feedback-loop effects) in an image. To accomplish this most intuitively, we recommend simply decomposing the rms height variations in the specimen into two and one dimensional (azimuthally averaged) logarithmic (per decade frequency) roughness spectra. The basic properties of such a decomposition of topographic images are discussed in a paper submitted separately to this conference. We here discuss scanned probe microscope results.
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Hariharan, H., A. Koschan, B. Abidi, D. Page, M. Abidi, J. Frafjord, and S. Dekanich. "Extending Depth of Field in LC-SEM Scenes by Partitioning Sharpness Transforms." Microscopy Today 16, no. 2 (March 2008): 18–21. http://dx.doi.org/10.1017/s1551929500055875.
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When imaging a sample, it is desirable to have the entire area of interest in focus in the acquired image. Typically, microscopes have a limited depth of field (DOF) and this makes the acquisition of such an all-in-focus image difficult. This is a major problem in many microscopic applications and applies equally in the realm of scanning electron microscopy as well. In multifocus fusion, the central idea is to acquire focal information from multiple images at different focal planes and fuse them into one all-in-focus image where all the focal planes appear to be in focus.Large chamber scanning electron microscopes (LC-SEM) are one of the latest members in the SEM family that has found extensive use for nondestructive evaluations. Large objects (~1 meter) can be scanned in micro- or nano-scale using this microscope. An LC-SEM can provide characterization of conductive and non-conductive surfaces with a magnification from 10× to 200,000×. The LC-SEM, as with other SEMs, suffers from the problem of limited DOF making it difficult to inspect a large object while keeping all areas in focus.
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Schatten, G., S. Paddock, P. Cooke, and J. Pawley. "Confocal microscopy at the integrated microscopy resource for biomedical research (IMR) of the university of wisconsin." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 92–93. http://dx.doi.org/10.1017/s0424820100102547.
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Confocal microscopy holds great promise for improved imaging of fluorescent or reflective biomedical specimens. The IMR is actively investigating the advantages and optimal usage of the Medical Research Council's Lasersharp laser - scanning confocal microscope and Tracor/Northern's Tandem Scanning Microscope, which benefits from the principles outlined by Petran et al. and Boyde.Quantitative evaluation of microscopic images has always been complicated by the effect of out-of-focus structures on the final image. These effects can be greatly reduced if the conventional light microscope is replaced by a scanning-confocal light microscope. In such an instrument two conditions are met: 1) only a single point of the sample is illuminated at any time and 2) this point on the sample is then imaged onto the pinhole at the entrance to the photodetector. Because little light from out-of-focus planes will pass through the pinhole, only in-focus data is recorded.
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A S M, Waliullah. "FEASIBILITY STUDY ON BLOOD CELL COUNTING USING MOBILE PHONE-BASED PORTABLE MICROSCOPE." International Journal of Clinical and Biomedical Research 4, no. 3 (July 31, 2018): 76–79. http://dx.doi.org/10.31878/ijcbr.2018.43.16.
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Objectives: To check the feasibility of using the mobile phone-based microscope for blood cell counting from human blood histological sample. Methodology: A feasibility study was performed by imaging blood histology samples with one novel type of microscope “Foldscope” and image compared with a conventional microscope in the laboratory facility. The image acquired from both modalities were processed further and compared and analyzed. Results: Mobile phone-based microscope acquired images were observed and compared with a conventional microscope and found the blood cell counting feasibility and morphology analysis of the blood histology sample were significantly similar as of conventional light microscope images. Conclusion: By comparing the image from both microscopes, it could be stated that this method is feasible for human blood histopathological sample investigations like blood cell counting and morphology analysis especially in the low resource area or in case of any emergency situations.
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Bell, David C. "Contrast Mechanisms and Image Formation in Helium Ion Microscopy." Microscopy and Microanalysis 15, no. 2 (March 16, 2009): 147–53. http://dx.doi.org/10.1017/s1431927609090138.
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AbstractThe helium ion microscope is a unique imaging instrument. Based on an atomic level imaging system using the principle of field ion microscopy, the helium ion source has been shown to be incredibly stable and reliable, itself a remarkable engineering feat. Here we show that the image contrast is fundamentally different to other microscopes such as the scanning electron microscope (SEM), although showing many operational similarities due to the physical ion interaction mechanisms with the sample. Secondary electron images show enhanced surface contrast due the small surface interaction volume as well as elemental contrast differences, such as for nanowires imaged on a substrate. We present images of nanowires and nanoparticles for comparison with SEM imaging. Applications of Rutherford backscattered ion imaging as a unique and novel imaging mechanism are described. The advantages of the contrast mechanisms offered by this instrument for imaging nanomaterials are clearly apparent due to the high resolution and surface sensitivity afforded in the images. Future developments of the helium ion microscope should yield yet further improvements in imaging and provide a platform for continued advances in microscope science and nanoscale research.
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Vokes, Martha S., and Anne E. Carpenter. "CellProfiler: Open-Source Software to Automatically Quantify Images." Microscopy Today 16, no. 5 (September 2008): 38–39. http://dx.doi.org/10.1017/s1551929500061757.
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Researchers often examine samples by eye on the microscope — qualitatively scoring each sample for a particular feature of interest. This approach, while suitable for many experiments, sacrifices quantitative results and a permanent record of the experiment. By contrast, if digital images are collected of each sample, software can be used to quantify features of interest. For small experiments, quantitative analysis is often done manually using interactive programs like Adobe Photoshop©. For the large number of images that can be easily collected with automated microscopes, this approach is tedious and time-consuming. NIH Image/ImageJ (http://rsb.info.nih.gov/ij) allows users comfortable writing in a macro language to automate quantitative image analysis. We have developed Cell- Profiler, a free, open-source software package, designed to enable scientists without prior programming experience to quantify relevant features of samples in large numbers of images automatically, in a modular system suitable for processing hundreds of thousands of images.
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Prater, C. B., A. L. Weisenhorn, B. Dixon Northern, C. M. Peterson, S. A. C. Gould, and P. K. Hansma. "Imaging Molecules and Cells with the Atomic Force Microscope." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 1 (August 12, 1990): 254–55. http://dx.doi.org/10.1017/s0424820100180021.
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The atomic force microscope (AFM) gives topographic images by scanning a sharp stylus over a surface. The stylus is attached to a spring lever which is deflected when the stylus interacts with the surface. The AFM images a surface by measuring deflection as a function of position over the surface. The AFM has given atomic resolution images of both conductors and nonconductors. The AFM has also given images of amino acid polymers with subnanometer resolution. The AFM has imaged samples covered with a liquid and biological processes like blood clotting have been imaged. In this report we present several images that demonstrate the variety of samples that can be imaged with the AFM.The AFM has imaged adsorbed molecules at subnanometer resolution. Figure 1A is an image of the bare (010) surface of the natural zeolite, clinoptilolite. Molecules of t-butanol were then adsorbed onto the surface from the liquid and the sample was imaged again (Fig. IB).Figure 2 is an image of double stranded DNA dried onto mica. The resolution is sufficient to reveal corrugation due to the major groove of the double helix. We are currently working to gain resolution sufficient to sequence single-stranded DNA.
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Curtin, Alexandra E., Ryan Skinner, and Aric W. Sanders. "A Simple Metric for Determining Resolution in Optical, Ion, and Electron Microscope Images." Microscopy and Microanalysis 21, no. 3 (May 26, 2015): 771–77. http://dx.doi.org/10.1017/s1431927615000343.
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AbstractA resolution metric intended for resolution analysis of arbitrary spatially calibrated images is presented. By fitting a simple sigmoidal function to pixel intensities across slices of an image taken perpendicular to light–dark edges, the mean distance over which the light–dark transition occurs can be determined. A fixed multiple of this characteristic distance is then reported as the image resolution. The prefactor is determined by analysis of scanning transmission electron microscope high-angle annular dark field images of Si<110>. This metric has been applied to optical, scanning electron microscope, and helium ion microscope images. This method provides quantitative feedback about image resolution, independent of the tool on which the data were collected. In addition, our analysis provides a nonarbitrary and self-consistent framework that any end user can utilize to evaluate the resolution of multiple microscopes from any vendor using the same metric.
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Stuurman, Nico, Nenad Amdodaj, and Ron Vale. "μManager: Open Source Software for Light Microscope Imaging." Microscopy Today 15, no. 3 (May 2007): 42–43. http://dx.doi.org/10.1017/s1551929500055541.
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No longer are biologists content to peer through the oculars of a microscope. Eyes have been replaced by digital cameras. Instead of manual control of microscope stages, filters and light sources, modern microscopes have become fully robotic. Image acquisition and robotic movements require computer control. With such equipment it is possible to automatically record images at multiple wavelengths, carry out time-lapse recordings of living cells using very short exposure times and low light doses, and even to record images at multiple positions (e.g. from a multi-well plate) without operator intervention. Clearly, computer control of light microscope image acquisition is making many new experimental imaging strategies possible in the biological sciences.
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Lee, Jiyoung, Seunghyun Jang, Jungbin Lee, Taehan Kim, Seonghan Kim, Jongbum Seo, Ki Hean Kim, and Sejung Yang. "Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images." Sensors 21, no. 21 (November 5, 2021): 7371. http://dx.doi.org/10.3390/s21217371.
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The non-invasive examination of conjunctival goblet cells using a microscope is a novel procedure for the diagnosis of ocular surface diseases. However, it is difficult to generate an all-in-focus image due to the curvature of the eyes and the limited focal depth of the microscope. The microscope acquires multiple images with the axial translation of focus, and the image stack must be processed. Thus, we propose a multi-focus image fusion method to generate an all-in-focus image from multiple microscopic images. First, a bandpass filter is applied to the source images and the focus areas are extracted using Laplacian transformation and thresholding with a morphological operation. Next, a self-adjusting guided filter is applied for the natural connections between local focus images. A window-size-updating method is adopted in the guided filter to reduce the number of parameters. This paper presents a novel algorithm that can operate for a large quantity of images (10 or more) and obtain an all-in-focus image. To quantitatively evaluate the proposed method, two different types of evaluation metrics are used: “full-reference” and “no-reference”. The experimental results demonstrate that this algorithm is robust to noise and capable of preserving local focus information through focal area extraction. Additionally, the proposed method outperforms state-of-the-art approaches in terms of both visual effects and image quality assessments.
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Misaki, Daigo, Ryuhei Kurokawa, Satoshi Nakajima, and Shigeomi Koshimizu. "Use of AR / VR in Micro Manipulation Support System for Recognition of Monocular Microscopic Images." International Journal of Automation Technology 5, no. 6 (November 5, 2011): 866–74. http://dx.doi.org/10.20965/ijat.2011.p0866.
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This study researches the use of Augmented Reality / Virtual Reality (AR / VR) in an affordable and highly flexible micro manipulation system for the recognition of microscopic images, images that support microscopic manipulation in the interface between the manipulation space and the operator. The application of AR / VR usually requires sensing of the manipulation space with more than one microscope or sensor, not only making the system more complex and costly but also making the manipulation space under the microscope smaller. In this research, therefore, we use the background finite-difference method with background models for monocular microscopic images of the manipulation space; we can build up information needed formanipulation support with AR / VR while removing the effects of any disturbance to the recognition of the manipulation space. We also use liquid bridging forces for the manipulations. The experimental results confirmthat the information processing of the image processing method used in this research is adequate in both terms of accuracy and time efficiency to support microscopic manipulation using liquid bridging forces.
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Li, Sen, Qi Yang, Hao Jiang, Jesús A. Cortés-Vecino, and Yang Zhang. "Parasitologist-level classification of apicomplexan parasites and host cell with deep cycle transfer learning (DCTL)." Bioinformatics 36, no. 16 (May 15, 2020): 4498–505. http://dx.doi.org/10.1093/bioinformatics/btaa513.
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Abstract Motivation Apicomplexan parasites, including Toxoplasma, Plasmodium and Babesia, are important pathogens that affect billions of humans and animals worldwide. Usually a microscope is used to detect these parasites, but it is difficult to use microscopes and clinician requires to be trained. Finding a cost-effective solution to detect these parasites is of particular interest in developing countries, in which infection is more common. Results Here, we propose an alternative method, deep cycle transfer learning (DCTL), to detect apicomplexan parasites, by utilizing deep learning-based microscopic image analysis. DCTL is based on observations of parasitologists that Toxoplasma is banana-shaped, Plasmodium is generally ring-shaped, and Babesia is typically pear-shaped. Our approach aims to connect those microscopic objects (Toxoplasma, Plasmodium, Babesia and erythrocyte) with their morphological similar macro ones (banana, ring, pear and apple) through a cycle transfer of knowledge. In the experiments, we conduct DCTL on 24 358 microscopic images of parasites. Results demonstrate high accuracy and effectiveness of DCTL, with an average accuracy of 95.7% and an area under the curve of 0.995 for all parasites types. This article is the first work to apply knowledge from parasitologists to apicomplexan parasite recognition, and it opens new ground for developing AI-powered microscopy image diagnostic systems. Availability and implementation Code and dataset available at https://github.com/senli2018/DCTL. Supplementary information Supplementary data are available at Bioinformatics online.
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Cogswell, Carol J., Matthew R. Arnison, Edward R. Dowski, Sara C. Tuckert, and W. Thomas Catheyt. "A New Generation, Fast 3D Fluorescence Microscope using Wavefront Coding Optics." Microscopy and Microanalysis 5, S2 (August 1999): 466–67. http://dx.doi.org/10.1017/s1431927600015658.
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We are developing a “new-generation” fluorescence microscope that will allow very fast (milliseconds) acquisition of fully three-dimensional (3D) images for a wide spectrum of biological applications. This new system will overcome the slow image acquisition constraint of existing confocal and widefield deconvolution microscopes (the two most commonly used instruments for 3D fluorescence imaging) that has prevented them from being used for investigations of live-cell dynamics in three dimensions. Our new microscope incorporates the innovative techniques of optical wavefront coding, pioneered by W. T. Cathey and E. R. Dowski, University of Colorado. With this new system, as compared to the normal sequential plane-by-plane image acquisition requirement of confocal and widefield microscopes, we need acquire only a single CCD camera image to obtain an equivalent extended-depth-of-focus (EDF) rendering of a thick specimen, and a minimum of only two images for a 3D stereo view that has full depth.Our microscope system uses a special-purpose optical element to uniformly “code” the information from all planes throughout the specimen volume onto a single CCD camera image. Specimen-independent digital processing is then used to “decode” this raw image. In effect, the coded raw image is blurred by a special type of aberration which produces an image that is nearly independent of focus. The system then uses a fast, non-iterative, digital filtering algorithm to remove this special blur so that a large volume of the specimen image appears sharply focused all at once.
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Liu, Sanya, Xiao Weng, Xingen Gao, Xiaoxin Xu, and Lin Zhou. "A Residual Dense Attention Generative Adversarial Network for Microscopic Image Super-Resolution." Sensors 24, no. 11 (May 31, 2024): 3560. http://dx.doi.org/10.3390/s24113560.
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With the development of deep learning, the Super-Resolution (SR) reconstruction of microscopic images has improved significantly. However, the scarcity of microscopic images for training, the underutilization of hierarchical features in original Low-Resolution (LR) images, and the high-frequency noise unrelated with the image structure generated during the reconstruction process are still challenges in the Single Image Super-Resolution (SISR) field. Faced with these issues, we first collected sufficient microscopic images through Motic, a company engaged in the design and production of optical and digital microscopes, to establish a dataset. Secondly, we proposed a Residual Dense Attention Generative Adversarial Network (RDAGAN). The network comprises a generator, an image discriminator, and a feature discriminator. The generator includes a Residual Dense Block (RDB) and a Convolutional Block Attention Module (CBAM), focusing on extracting the hierarchical features of the original LR image. Simultaneously, the added feature discriminator enables the network to generate high-frequency features pertinent to the image’s structure. Finally, we conducted experimental analysis and compared our model with six classic models. Compared with the best model, our model improved PSNR and SSIM by about 1.5 dB and 0.2, respectively.
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Conchello, José-Angel, Joanne Markham, and James G. McNally. "All Models are Wrong an Overview of 3D Deconvolution Methods." Microscopy and Microanalysis 3, S2 (August 1997): 375–76. http://dx.doi.org/10.1017/s143192760000876x.
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Three dimensional (3D)microscopy is a powerful toll for the visualization of biological specimens and processes. In 3D microscopy, a 3D image is collected by recording a series of two-dimensional (2D) images focusing the microscope at different planes through the specimen. Each 2D optical slice in this through focus series contains the in-focus information plus contributions from out-of-focus structures that obscure the image and reduce its contrast. There are two complementary approaches to reduce or ameliorate the effects of the out-of-focus contributions, optical and computational. In the optical approach a microscope is used that avoids collecting out-of-focus light, such as a confocal microscope (see and references therein), a two-photon or three-photon fluorescence excitation microscope, or atwo-sided microscope. In the computational approach, the through-focus series is processed in a computer using any of a number of debluring algorithms to reduce or ameliorate the out-of-focus contributions. In the past two decades, several methods for debluring microscopic images have been developed whose common aim is to undo the degradations introduced by the process of image formation and recording
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Wang, Yi Hong. "Research on Segmentation of Protozoan and Metazoan Image in Microscopic Examination of Activated Sludge." Applied Mechanics and Materials 448-453 (October 2013): 367–70. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.367.
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Monitoring water quality using biological monitoring technology based on microscopic examination of activated sludge, machine vision replaces manual observation. The contrast between target and background is relatively low in the images obtained by automatic electron microscope. It is difficult to accurately distinguish the target and background if single image segmentation method is used. Therefore, the image which is segmented by single image segmentation method will be regarded as the source image, and image fusion is performed on these source images using wavelet transform. The fused image will be regarded as the final segmentation image. The result of experiments shows that using this idea can get better image edge detection effect, and it will provide good technical basis for the next protozoan and metazoan identification and statistics.
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Wang, Yao L., Noa W. F. Grooms, Sabrina C. Civale, and Samuel H. Chung. "Confocal imaging capacity on a widefield microscope using a spatial light modulator." PLOS ONE 16, no. 2 (February 16, 2021): e0244034. http://dx.doi.org/10.1371/journal.pone.0244034.
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Confocal microscopes can reject out-of-focus and scattered light; however, widefield microscopes are far more common in biological laboratories due to their accessibility and lower cost. We report confocal imaging capacity on a widefield microscope by adding a spatial light modulator (SLM) and utilizing custom illumination and acquisition methods. We discuss our illumination strategy and compare several procedures for postprocessing the acquired image data. We assessed the performance of this system for rejecting out-of-focus light by comparing images taken at 1.4 NA using our widefield microscope, our SLM-enhanced setup, and a commercial confocal microscope. The optical sectioning capability, assessed on thin fluorescent film, was 0.85 ± 0.04 μm for our SLM-enhanced setup and 0.68 ± 0.04 μm for a confocal microscope, while a widefield microscope exhibited no sectioning capability. We demonstrate our setup by imaging the same set of neurons in C. elegans on widefield, SLM, and confocal microscopes. SLM enhancement greatly reduces background from the cell body, allowing visualization of dim fibers nearby. Our SLM-enhanced setup identified 96% of the dim neuronal fibers seen in confocal images while a widefield microscope only identified 50% of the same fibers. Our microscope add-on represents a very simple (2-component) and inexpensive (<$600) approach to enable widefield microscopes to optically section thick samples.
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Zhao, Qichao, Jinwu Kang, and Kai Wu. "Study on the Recognition of Metallurgical Graphs Based on Deep Learning." Metals 14, no. 6 (June 20, 2024): 732. http://dx.doi.org/10.3390/met14060732.
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Artificial intelligence has been widely applied in image recognition and segmentation, achieving significant results. However, its application in the field of materials science is relatively limited. Metallography is an important technique for characterizing the macroscopic and microscopic structures of metals and alloys. It plays a crucial role in correlating material properties. Therefore, this study investigates the utilization of deep learning techniques for the recognition of metallo-graphic images. This study selected microscopic images of three typical cast irons, including ductile, gray, and white ones, and another alloy, cast aluminum alloy, from the ASM database for recognition investigation. These images were cut and enhanced for training. In addition to coarse classification of material type, fine classification of material type, composition, and the conditions of image acquisition such as microscope, magnification, and etchant was performed. The MobileNetV2 network was adopted as the model for training and prediction, and ImageNet was used as the dataset for pre-training to improve the accuracy. The metallographic images could be classified into 15 categories by the trained neural networks. The accuracy of validation and prediction for fine classification reached 94.44% and 93.87%, respectively. This indicates that neural networks have the potential to identify types of materials with details of microscope, magnification, etchants, etc., supplemental to compositions for metallographic images.
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Govil, Anurag, David M. Pallister, and Michael D. Morris. "Three-Dimensional Digital Confocal Raman Microscopy." Applied Spectroscopy 47, no. 1 (January 1993): 75–79. http://dx.doi.org/10.1366/0003702934048497.
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We describe an iterative image restoration technique which functions as digital confocal microscopy for Raman images. We deconvolute the lateral and axial components of the microscope point spread function from a series of optical sections, to generate a stack of well-resolved Raman images which describe the three-dimensional topology of a sample. The technique provides an alternative to confocal microscopy for three-dimensional microscopic Raman imaging.
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Shahani, Kamran, Hong Song, Syed Raza Mehdi, Awakash Sharma, Ghulam Tunio, Junaidullah Qureshi, Noor Kalhoro, and Nooruddin Khaskheli. "Design and Testing of an Underwater Microscope with Variable Objective Lens for the Study of Benthic Communities." Journal of Marine Science and Application 20, no. 1 (March 2021): 170–78. http://dx.doi.org/10.1007/s11804-020-00185-9.
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AbstractMonitoring the ecology and physiology of corals, sediments, planktons, and microplastic at a suitable spatial resolution is of great importance in oceanic scientific research. To meet this requirement, an underwater microscope with an electrically controlled variable lens was designed and tested. The captured microscopic images of corals, sediments, planktons, and microplastic revealed their physical, biological, and morphological characteristics. Further studies of the images also revealed the growth, degradation, and bleaching patterns of corals; the presence of plankton communities; and the types of microplastics. The imaging performance is majorly influenced by the choice of lenses, camera selection, and lighting method. Image dehazing, global saturation masks, and image histograms were used to extract the image features. Fundamental experimental proof was obtained with micro-scale images of corals, sediments, planktons, and microplastic at different magnifications. The designed underwater microscope can provide relevant new insights into the observation and detection of the future conditions of aquatic ecosystems.
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Krakow, W. "Real-time computer simulation of electron microscope images via a digital television frame store system." Proceedings, annual meeting, Electron Microscopy Society of America 44 (August 1986): 542–43. http://dx.doi.org/10.1017/s0424820100144188.
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Digital television frame store devices and software packages have made it possible to obtain images directly from electron microscopes, photographic prints and transparencies in real time and obtain the power spectrum (optical diffraction pattern) and filtered image of various electron micrographs. Enhancements have been added to the Fourier analysis program package which include the use of offset filter functions and the computation of high resolution electron microscope images by including the microscope lens aberration phase shifts and illumination conditions. Because of the use of the frame store and a large mainframe computer, it is possible to have several orders of magnitude gain in image computational speed which makes real-time interactive computations possible.
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Seraphin, Supapan, Gary W. Chandler, and Michelle S. Switala. "Computer Network Laboratory for Microscopy Education at the Materials Science and Engineering Department, The University of Arizona." Microscopy Today 3, no. 1 (February 1995): 14–15. http://dx.doi.org/10.1017/s1551929500062210.
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We report here on the first year of development of a novel teaching facility which incorporates new techniques designed to reach new audiences without diluting subject content. Interactive computer software coupled with rich scientific content of microscopic images provides a unique opportunity to help students learn science and technology, the laboratory is comprised of twenty student workstations networked to various microscopes, thus expanding the number of students capable of "hands-on" data acquisition and analysis by twenty times. Two scanning electron microscopes (SEM), a transmission electron microscope (TEM), and several light microscopes (LM) are interfaced through a server to the workstations.
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Aoyama, Tadayoshi, Sarau Takeno, Masaru Takeuchi, and Yasuhisa Hasegawa. "Head-Mounted Display-Based Microscopic Imaging System with Customizable Field Size and Viewpoint." Sensors 20, no. 7 (April 1, 2020): 1967. http://dx.doi.org/10.3390/s20071967.
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In recent years, the use of microinjections has increased in life science and biotechnology fields; specific examples include artificial insemination and gene manipulation. Microinjections are mainly performed based on visual information; thus, the operator needs high-level skill because of the narrowness of the visual field. Additionally, microinjections are performed as the operator views a microscopic image on a display; the position of the display requires the operator to maintain an awkward posture throughout the procedure. In this study, we developed a microscopic image display apparatus for microinjections based on a view-expansive microscope. The prototype of the view-expansive microscope has problems related to the variations in brightness and focal blur that accompany changes in the optical path length and amount of reflected light. Therefore, we propose the use of a variable-focus device to expand the visual field and thus circumvent the above-mentioned problems. We evaluated the observable area of the system using this variable-focus device. We confirmed that the observable area is 261.4 and 13.9 times larger than that of a normal microscope and conventional view-expansive microscopic system, respectively. Finally, observations of mouse embryos were carried out by using the developed system. We confirmed that the microscopic images can be displayed on a head-mounted display in real time with the desired point and field sizes.
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Yin, Juan Juan, Guo Jian Cheng, Na Liu, Xin Jian Qiang, and Ye Liu. "Rock Core Thin Section Image Stitching Based on SIFT Features." Advanced Materials Research 1049-1050 (October 2014): 398–401. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.398.
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Because of the inherent conflict between visual area and resolution in rock microscope structure, during the study of the RCTS (Rock Core Thin Section) microstructure, we cannot focus on the multi-scale structure characteristics of the particles, pores and throats, and it is fail to satisfy the demands of a more comprehensive study. In order to solve this problem, a microscopic image stitching method in RCTS is proposed by applying SIFT (Scale Invariant Feature Transform) detection algorithm. This method can successfully solve the conflict between the visual area and resolution, overcoming the problem of inclining and deformation in images acquisition under the microscope and finally, achieving the seamless stitching of RCTS microscopic image for big visual area. The experimental results show that this method can improve the accuracy of rock analysis in microstructure and has important practical and theoretical significance for the development of tight sandstone reservoir.
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Carrington, W. A., F. S. Fay, K. E. Fogarty, and L. Lifshitz. "Analysis of 3-d molecular distribution with the digital imaging microscope." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 40–41. http://dx.doi.org/10.1017/s0424820100102286.
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Advances in digital imaging microscopy and in the synthesis of fluorescent dyes allow the determination of 3D distribution of specific proteins, ions, GNA or DNA in single living cells. Effective use of this technology requires a combination of optical and computer hardware and software for image restoration, feature extraction and computer graphics.The digital imaging microscope consists of a conventional epifluorescence microscope with computer controlled focus, excitation and emission wavelength and duration of excitation. Images are recorded with a cooled (-80°C) CCD. 3D images are obtained as a series of optical sections at .25 - .5 μm intervals.A conventional microscope has substantial blurring along its optical axis. Out of focus contributions to a single optical section cause low contrast and flare; details are poorly resolved along the optical axis. We have developed new computer algorithms for reversing these distortions. These image restoration techniques and scanning confocal microscopes yield significantly better images; the results from the two are comparable.
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Haselgrove, John, Lou Fodor, and Lee Peachey. "Automatic alignment of stereo images." Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 502–3. http://dx.doi.org/10.1017/s0424820100170244.
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Stereoscopic pairs of electron microscope images are used for quantitative 3D information. A prerequisite for the measurement is to position the two images correctly relative to each other and with the stereo rotation axis of each image aligned vertically for viewing. Although this alignment procedure is relatively straightforward to perform using prints of the images, it is not straightforwardto do once the images have been digitized directly from the microscope. We have developed an algorithm for determining the parameters needed for orienting digitized images. Four parameters are needed: The displacements Δx and Δy by which one of the images must be translated to be superimposed on the other, and the angles Θ1 and Θr by which the left and right images must be rotated to bring the stereo-rotation axis vertical.The microscopist first uses an interactive routine to identify the coordinates xl(i),yl(i) and xr(i),yr(i) of a number (N) of fiducial points which can easily be recognized on each image.
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Shotton, D. M. "Video-enhanced light microscopy and its applications in cell biology." Journal of Cell Science 89, no. 2 (February 1, 1988): 129–50. http://dx.doi.org/10.1242/jcs.89.2.129.
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The combination of novel optical microscopic techniques with advanced video and digital image-processing technology now permits dramatic improvements in the quality of light-microscope images. Such video-enhanced light microscopy has lead to a renaissance in the applications of the light microscope for the study of living cells in two important areas: the intensification of faint fluorescence images, permitting observation of fluorescently labelled cells under conditions of very low illuminating intensity; and the enhancement of extremely low contrast images generated by minute cellular structures, so that these may be clearly seen and their normal intracellular movements recorded. Application of both these aspects of video-enhanced light microscopy have recently led to major discoveries concerning the functioning of the living cell. In this review I discuss the equipment, procedures and image-processing principles employed in these applications, and describe and illustrate some of the spectacular results that have recently been obtained.
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Jędral, Arnold, and Anna Bona. "Validation of Microscopy Measured Porosity in Carbon Fibbers Composites." Journal of KONES 26, no. 4 (December 1, 2019): 83–90. http://dx.doi.org/10.2478/kones-2019-0093.
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AbstractOne of the most common defects in carbon fibre reinforced plastics (CFRP) is porosity. Too much of those defects could be serious problems to mechanical properties, which directly take effect on elements safety, like aircrafts. Therefore, the evaluation of porosity is very important test. Microscopic observations are widely used as a quality instrument in materials and constructions inspections. Cross section image of a material is easy to prepare and analyse. Porosity of a carbon fibre reinforced plastic can be clearly spot in such kind of images. Study shows that in the most cases porosity appear between layers of fibres, rather between fibres. Unfortunately, image from microscope is only 2D picture from a small representative region. Because of that, comparison of 2D image to a real porosity distribution in all volume of a material is very difficult. To verify 2D microscopic observation method is necessary to perform another kind of tests. In this article, authors focused on non-destructive (NDT) and destructive testing methods. 2D porosity images from light microscope were compared with three different testing methods: ultrasonic test (UT), computed tomography (CT) test and constituent content of composite materials standard test method according to ASTM D3171 – 15, procedure B. Porosity results obtained from dissolution of resin from the carbon-epoxy resin sample.
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Ross, Frances M. "Materials Science in the Electron Microscope." MRS Bulletin 19, no. 6 (June 1994): 17–21. http://dx.doi.org/10.1557/s0883769400036691.
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This issue of the MRS Bulletin aims to highlight the innovative and exciting materials science research now being done using in situ electron microscopy. Techniques which combine real-time image acquisition with high spatial resolution have contributed to our understanding of a remarkably diverse range of physical phenomena. The articles in this issue present recent advances in materials science which have been made using the techniques of transmission electron microscopy (TEM), including holography, scanning electron microscopy (SEM), low-energy electron microscopy (LEEM), and high-voltage electron microscopy (HVEM).The idea of carrying out dynamic experiments involving real-time observation of microscopic phenomena has always had an attraction for materials scientists. Ever since the first static images were obtained in the electron microscope, materials scientists have been interested in observing processes in real time: we feel that we obtain a true understanding of a microscopic phenomenon if we can actually watch it taking place. The idea behind “materials science in the electron microscope” is therefore to use the electron microscope—with its unique ability to image subtle changes in a material at or near the atomic level—as a laboratory in which a remarkable variety of experiments can be carried out. In this issue you will read about dynamic experiments in areas such as phase transformations, thin-film growth, and electromigration, which make use of innovative designs for the specimen, the specimen holder, or the microscope itself. These articles speak for themselves in demonstrating the power of real-time analysis in the quantitative exploration of reaction mechanisms.The first transmission electron microscopes operated at low accelerating voltages, up to about 100 kV. This placed a severe limitation on the thickness of foils that could be examined: Heavy elements, for example, had to be made into foils thinner than 0.1 μm. It was felt that any phenomenon whose “mean free path” was comparable to the foil thickness would be significantly affected by the foil surfaces, and therefore would be unsuitable for study in situ. However, technology quickly generated ever higher accelerating voltages, culminating in the giant 3 MeV electron microscopes. At these voltages, electrons can penetrate materials as thick as 6–9 μm for light elements such as Si and Al, and 1 μm for very heavy ones such as Au and U.
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Agus Darmawan, Izzati Muhimmah, and Rahadian Kurniawan. "Integration of Microscopic Image Capturing System for Automatic Detection of Mycobacterium Tuberculosis Bacteria." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 7, no. 2 (March 26, 2023): 367–75. http://dx.doi.org/10.29207/resti.v7i2.4495.
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The Ministry of Health of the Republic of Indonesia is running a program to eliminate Tuberculosis (TB) by 2030. At the Primary Health Care level, AFB (acid-fast bacteria) examination confirms the TB diagnosis. In this process, the patient's sputum is prepared in the form of preparation and observed by the laboratory analyst through the lens of a microscope. The reporting process to establish this diagnosis requires calculating the number of TB bacteria in 100 fields of view per preparation. This manual microscopic observation process is tedious, and the reading results are subjective. This study offers an integrated design for automatic microscopic imaging with a computer-integrated TB bacteria detection system. The process of taking pictures is automatically obtained with the help of a driving motor added to the microscope. With the addition of this motor, the process of taking microscopic images for 100 fields of view takes ±450 seconds. The proposed system integration process can reduce laboratory analysts' work fatigue in conducting microscopic observations manually. The TB bacteria detection system utilizes the working principle of image processing techniques by combining color-deconvolution, segmentation, and contour-detection methods. The comparative value of the TB object detection system with experts resulted in a sensitivity value of 77% and a specificity value of 68%. However, the low detection rate is because the image obtained is still blurry. Thus, further investigation is needed to determine the driving motor's movement rate and the right timing for taking microscopic images so that the resulting image is not blurry. The final result that is the focus of this paper is the successful integration of the system carried out between the motor drive system on the preparation stand and the TB bacteria detection system to become a unified system.
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Rahman, Atta-ur, Abdullah Alqahtani, Nahier Aldhafferi, Muhammad Umar Nasir, Muhammad Farhan Khan, Muhammad Adnan Khan, and Amir Mosavi. "Histopathologic Oral Cancer Prediction Using Oral Squamous Cell Carcinoma Biopsy Empowered with Transfer Learning." Sensors 22, no. 10 (May 18, 2022): 3833. http://dx.doi.org/10.3390/s22103833.
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Oral cancer is a dangerous and extensive cancer with a high death ratio. Oral cancer is the most usual cancer in the world, with more than 300,335 deaths every year. The cancerous tumor appears in the neck, oral glands, face, and mouth. To overcome this dangerous cancer, there are many ways to detect like a biopsy, in which small chunks of tissues are taken from the mouth and tested under a secure and hygienic microscope. However, microscope results of tissues to detect oral cancer are not up to the mark, a microscope cannot easily identify the cancerous cells and normal cells. Detection of cancerous cells using microscopic biopsy images helps in allaying and predicting the issues and gives better results if biologically approaches apply accurately for the prediction of cancerous cells, but during the physical examinations microscopic biopsy images for cancer detection there are major chances for human error and mistake. So, with the development of technology deep learning algorithms plays a major role in medical image diagnosing. Deep learning algorithms are efficiently developed to predict breast cancer, oral cancer, lung cancer, or any other type of medical image. In this study, the proposed model of transfer learning model using AlexNet in the convolutional neural network to extract rank features from oral squamous cell carcinoma (OSCC) biopsy images to train the model. Simulation results have shown that the proposed model achieved higher classification accuracy 97.66% and 90.06% of training and testing, respectively.
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SAKAI, Toshihide, and Tetsuya TSUJIKAMI. "PS17 Microscopic Strain Measurement by Image Correlation Method using Microscope Image." Proceedings of the Materials and Mechanics Conference 2008 (2008): _PS17–1_—_PS17–2_. http://dx.doi.org/10.1299/jsmemm.2008._ps17-1_.
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Iskandarova, S. N., and J. K. Saydazimov. "IMPROVING THE VISUAL DIAGNOSIS OF DISEASES USING HYBRID NEURAL NETWORKS." Oriental Journal of Medicine and Pharmacology 02, no. 05 (November 1, 2022): 20–25. http://dx.doi.org/10.37547/supsci-ojmp-02-05-03.
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Computer recognition algorithms based on microscopic images of blood particles can be used as a decision support mechanism to help specialists speed up the diagnostic process. The purpose of this work is to evaluate the quantitative analysis of hybrid neural networks (CNN + RNN). It can visually check the solution area of the input image used by CNN + LSTM. Based on the microscope image, the recognition results of blood composition particles according to their shape have been achieved up to 90%.
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Durai Anand Thangarajan and Sivasangari Rajeswaran. "Bacteria identification using digital image processing." International Journal of Science and Research Archive 12, no. 2 (July 30, 2024): 818–20. http://dx.doi.org/10.30574/ijsra.2024.12.2.1268.
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The identification of bacteria is an important and unavoidable task in medical disciplines and nutritional hygiene. But in the field of microbiology, No direct method is available for determination of bacterial species. The common manual technique is the microscopic sample analysis combined with more than 20 biochemical tests to identify the bacterium. These tests are more time consuming processes and required the training person for conducting these tests. To overcome the above problems the digital image processing can be used. The primary objective of the proposed work is to use the digital image processing techniques to identify the bacteria from the microscopic images. In this work the image of bacterial species were captured using a digital camera attached with the transmission electron microscope. After capturing the image, the preprocessing, segmentation and morphological procedures of digital image processing techniques are used to identify the bacterial species.
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Eminizer, Margaret, Melinda Nagy, Elizabeth L. Engle, Sigfredo Soto-Diaz, Andrew Jorquera, Jeffrey S. Roskes, Benjamin F. Green, Richard Wilton, Janis M. Taube, and Alexander S. Szalay. "Comparing and Correcting Spectral Sensitivities between Multispectral Microscopes: A Prerequisite to Clinical Implementation." Cancers 15, no. 12 (June 8, 2023): 3109. http://dx.doi.org/10.3390/cancers15123109.
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Multispectral, multiplex immunofluorescence (mIF) microscopy has been used to great effect in research to identify cellular co-expression profiles and spatial relationships within tissue, providing a myriad of diagnostic advantages. As these technologies mature, it is essential that image data from mIF microscopes is reproducible and standardizable across devices. We sought to characterize and correct differences in illumination intensity and spectral sensitivity between three multispectral microscopes. We scanned eight melanoma tissue samples twice on each microscope and calculated their average tissue region flux intensities. We found a baseline average standard deviation of 29.9% across all microscopes, scans, and samples, which was reduced to 13.9% after applying sample-specific corrections accounting for differences in the tissue shown on each slide. We used a basic calibration model to correct sample- and microscope-specific effects on overall brightness and relative brightness as a function of the image layer. We tested the generalizability of the calibration procedure and found that applying corrections to independent validation subsets of the samples reduced the variation to 2.9 ± 0.03%. Variations in the unmixed marker expressions were reduced from 15.8% to 4.4% by correcting the raw images to a single reference microscope. Our findings show that mIF microscopes can be standardized for use in clinical pathology laboratories using a relatively simple correction model.
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Hang Ho, Yuen, Humaira Nisar, and Muhammad Burhan Khan. "Segmentation of Activated Sludge Filaments using Phase Contrast Images." Oriental journal of computer science and technology 11, no. 3 (July 23, 2018): 145–53. http://dx.doi.org/10.13005/ojcst11.03.03.
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Segmentation algorithms play an important role in image processing and analysis. The identification of objects and process monitoring strongly depends on the accuracy of the segmentation algorithms. Waste water treatment plants are used to treat wastewater from municipal and industrial plants. Activated sludge process is used in wastewater treatment plants to biodegrade the organic constituents present in waste water. This biodegradation is done with the help of microorganisms and bacteria. There are two important types of microscopic organisms present in the activated sludge plants, named as flocs as filaments, which are visible under microscope. In this paper we study the microscopic images of wastewater using phase contrast microscopy. The images are acquired from wastewater sample using a microscope. The samples of wastewater are collected from domestic wastewater treatment plant aeration tank. Our main aim is to segment threadlike organisms knows as filaments. Several segmentation algorithms (such as edge based algorithm, k-means algorithm, texture based algorithm, and watershed algorithm) will be explored and their performance will be compared using gold approximations of the images. The performance of the algorithms are evaluated using different performance metrics, such as Rand Index, specificity, variation of information, and accuracy. We have found that edge based segmentation works well for phase contrast microscopic images of activated sludge wastewater.
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Mund, Markus, and Jonas Ries. "How good are my data? Reference standards in superresolution microscopy." Molecular Biology of the Cell 31, no. 19 (September 1, 2020): 2093–96. http://dx.doi.org/10.1091/mbc.e19-04-0189.
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Superresolution microscopy is becoming increasingly widespread in biological labs. While it holds enormous potential for biological discovery, it is a complex imaging technique that requires thorough optimization of various experimental parameters to yield data of the highest quality. Unfortunately, it remains challenging even for seasoned users to judge from the acquired images alone whether their superresolution microscopy pipeline is performing at its optimum, or if the image quality could be improved. Here, we describe how superresolution microscopists can objectively characterize their imaging pipeline using suitable reference standards, which are stereotypic so that the same structure can be imaged everywhere, every time, on every microscope. Quantitative analysis of reference standard images helps characterizing the performance of one’s own microscopes over time, allows objective benchmarking of newly developed microscopy and labeling techniques, and finally increases comparability of superresolution microscopy data between labs.