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226 results for “Microscope image”
Transmission electron microscope images dataset for AutoDetect-mNP (triangular prisms)
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Transmission electron microscope images dataset for AutoDetect-mNP (nanorods)
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Microscopic images of pollen captured in Graz, Austria
<p><strong>Images and Annotations</strong></p> <p>This dataset contains microscopic images of pollen captured in Graz, Austria. Additionally, bounding box annotations are provided for each image. The images were captured with an automated pollen detection system as described in the paper <a href="http://www.ewsn.org/file-repository/ewsn2020/108_119_cao.pdf">Automated and Continuous Pollen Detection with an Affordable Technology</a>. The annotations have been produced manually. This dataset contains data of two days (23.05.2019 and 26.05.2019).</p> <p>The dataset can be used to train an object classifier with the code from the following repository:</p> <p>https://github.com/osaukh/pollenpub</p> <p><strong>Weights</strong></p> <p>In addition, this dataset contains two pre-trained weight files. One weight file is pre-trained on ImageNet (provided by Joseph Redmon) and the other is pre-trained for pollen detection on the above mentioned image/annotation combination.</p> <p> </p> <p><strong>References</strong><br> The dataset (and related aspects) has partly been used and is described in more detail in the following publication:</p> <p>N. Cao, M. Meyer, L. Thiele, O. Saukh. Automated Pollen Detection with an Affordable Technology. Proc. of the International Conference on Embedded Wireless Systems and Networks (EWSN), February 2020. </p>
FIGURE 6. Compound microscopic images showing detailed morphology for L in A new species of the genus Loricula Curtis from central Honshu, Japan (Heteroptera: Microphysidae)
FIGURE 6. Compound microscopic images showing detailed morphology for L. mikawa sp. nov., female. A. Head and pronotum, dorsal view. B. Antenna. C. Labium. D. Thorax, ventral surface. E. Forewing base. F. Abdomen, ventral view. G. Apodemal process. H. Genital segments, ventral view. I. Three eggs found in abdomen (F).
Scripts and raw data for comparing 2D vs 3D image analysis of zebrafish embryo microscopic data
<p>Raw data and MatLab scripts used for image analysis of RNA polymerase II with serine 5 phosphorylation in the C-terminal domain (CTD) of the subunit 1 (Pol II Ser5P) in a fixed zebrafish embryo, comparing a 2D vs 3D approach to segment out the Pol II Ser5P clusters. Pol II Ser5P was labeled by immunofluorescence, microscopy images were acquired by instant-SIM microscopy and analyzed using MatLab scripts and the bioformats importer.</p>
Automated analysis of scanning electron microscopic images for assessment of hair surface damage
<p>Mechanical damage of hair can serve as an indicator of health status and its assessment relies on the measurement of morphological features via microscopic analysis, yet few studies have categorized the extent of damage sustained, and instead, have depended on qualitative profiling based on the presence or absence of specific features. We describe the development and application of a novel quantitative measure for scoring hair surface damage in scanning electron microscopic (SEM) images without predefined features, and automation of image analysis for characterization of morphological hair damage after exposure to an explosive blast. Application of an automated normalization procedure for SEM images revealed features indicative of contact with materials in an explosive device and characteristic of heat damage, though many were similar to features from physical and chemical weathering. Assessment of hair damage with tailing factor, a measure of asymmetry in pixel brightness histograms and proxy for surface roughness, yielded 81% classification accuracy to an existing damage classification system, indicating good agreement between the two metrics. Further ability of tailing factor to score features of hair damage reflecting explosion conditions demonstrates the broad applicability of the metric to assess damage to hairs containing a diverse set of morphological features. </p>
Data from: A double-sided microscope to realize whole-ganglion imaging of membrane potential in the medicinal leech
Studies of neuronal network emergence during sensory processing and motor control are greatly promoted by technologies that allow us to simultaneously record the membrane potential dynamics of a large population of neurons in single cell resolution. To achieve whole-brain recording with the ability to detect both small synaptic potentials and action potentials, we developed a voltage-sensitive dye (VSD) imaging technique based on a double-sided microscope that can image two sides of a nervous system simultaneously. We applied this system to the segmental ganglia of the medicinal leech Hirudo verbana. Double-sided VSD imaging enabled simultaneous recording of membrane potential events from almost all of the identifiable neurons. Using data obtained from double-sided VSD imaging we analyzed neuronal dynamics in both sensory processing and generation of behavior and constructed functional maps for identification of neurons contributing to these processes.
FIGURE 8. SEM images. A in Comparison of the predatory rotifers Pleurotrocha petromyzon (Ehrenberg, 1830) and Pleurotrocha sigmoidea Skorikov, 1896 (Rotifera: Monogononta: Notommatidae) based on light and electron microscopic observations
FIGURE 8. SEM images. A. Sculptured egg of Pleurotrocha petromyzon in Carchesium -colony. B. Remaining stalks of a Carchaesium -colony. eg egg.
IODP Expedition 391 Scanning electron microscope images
Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.
◂Fig. 8 Light microscope images of living specimens of Ramisyllis kingghidorahi n. sp. A Branching point. B, E–G Posterior ends showing pygidia. C, D, H, I Midbody segments in regions of long dorsal cirri. Arrows point to the ventral blood vessel in H and the digestive tract in I.A, D, E, and I in dorsal view. B, C, F and H in ventral view. G In lateral view. Scale bars: 500 µm A, E, 200 µm B, C, D, 100 µm F, H, I, and 50 µm G in Ramisyllis kingghidorahi n. sp., a new branching annelid from Japan
◂Fig. 8 Light microscope images of living specimens of Ramisyllis kingghidorahi n. sp. A Branching point. B, E–G Posterior ends showing pygidia. C, D, H, I Midbody segments in regions of long dorsal cirri. Arrows point to the ventral blood vessel in H and the digestive tract in I.A, D, E, and I in dorsal view. B, C, F and H in ventral view. G In lateral view. Scale bars: 500 µm A, E, 200 µm B, C, D, 100 µm F, H, I, and 50 µm G
Source data and code for "A diamond voltage imaging microscope"
<p>This data set contains both the source data and code used to generate figures and establish the conclusions of "A diamond voltage imaging microscope" (DOI: https://doi.org/10.1038/s41566-022-01064-1). It contains:</p> <p>- Raw source data (e.g., video data, fluorescence spectra).</p> <p>- Processed source data (e.g., calibration maps, calculated vales of contrast, sensitivity, etc).</p> <p>- Analysis code used to generate processed source data (this includes both MATLAB and Python scripts. MATLAB scripts require at least version R2021A).</p> <p>- Simulation code (Python) used to fit the equivalent RC circuit model described in the work to the experimental data.</p>
IODP Expedition 371 Scanning electron microscope images
Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.
Reporter CRISPR screens decipher cis- and trans-regulatory principles at the Xist locus [Microscope images - Xist act KDs]
<p>Microscope images related to Figure 5 in Schwämmle et al. 2025. </p> <p>The cells are day 2 differentiated TX1072 XX SP427 mESCs with the indicated knockdowns. (-2iLIF)</p> <p>Exonic Xist is stained using Cy5 Stellaris probes. The nuclei are stained using DAPI.</p> <p>These files were used to perform automated image analysis to detect and quantify Xist clouds (https://github.com/EddaSchulz/TFiScreen_Paper).</p>
Microscope Image Analysis Course Sept 2109 -- Images siRNA Screen
<p>Contains 380 Fluorescence images of DAPI stained HeLa nuclei, acquired in 42 wells of a 384 well plate. individual wells were treated with siRNA. Images were acquired with an Olympus ScanR system at 10x magnification.</p>
Microscope Image Analysis Course Sept 2109 -- Images siRNA Screen
<p>Contains 380 Fluorescence images of DAPI stained HeLa nuclei, acquired in 42 wells of a 384 well plate. individual wells were treated with siRNA. Images were acquired with an Olympus ScanR system at 10x magnification.</p>
Fig. 6 Cnidosacs and nematocysts. a–d Transmission electron microscopic images, longitudinal sections. a in Pseudovermis paradoxus 2.0-3D microanatomy and ultrastructure of a vermiform, meiofaunal nudibranch (Gastropoda, Heterobranchia)
Fig. 6 Cnidosacs and nematocysts. a–d Transmission electron microscopic images, longitudinal sections. a Overview of an entire cnidosac. b Close-up of nematocysts. c Intact nematocyst. d Degraded nematocyst and muscular lining. clw cell wall, cp cnidophage, cw capsule wall, dnc degraded nematocyst, fi filament thread, ha harpoon, inc intact nematocyst, lu lumen, m mitochondrion, ml muscular lining, mv microvilli, nc nematocyst, nu nucleus, vac vacuole
FIGURE 4. Scanning electron microscope images. A in Three new species of Acalypha (Euphorbiaceae, Acalyphoideae) from Argentina, Bolivia, Brazil and Paraguay
FIGURE 4. Scanning electron microscope images. A. Teeth of the female bract of Acalypha chaquensis showing the stellate crystalliferous papillae (from A. Schinini & E. Bordas 17839, MO). B. Detail of stellate crystal on the female bract of Acalypha communis subsp. apicalis (Nicholas Edward Brown) Cardiel & P.Muñoz (2013: 1296) (from J.C. Solomon 6911, MO).
Data from: Comparing ant morphology measurements from microscope and online AntWeb.org 2D z-stacked images
<p><span>Unprecedented technological advances in digitization and the steadily expanding open-access digital repositories are yielding new opportunities to quickly and efficiently measure morphological traits without transportation and advanced/expensive microscope machinery. A prime example is the AntWeb.org database, which allows researchers from all over the world to study taxonomic, ecological, or evolutionary questions on the same ant specimens with ease. However, the reproducibility and reliability of morphometric data deduced from AntWeb compared to traditional microscope measurements has not yet been tested.</span></p> <p><span>Here, we compared 12 morphological traits of 46 <em>Temnothorax</em> ant specimens measured either directly by stereomicroscope on physical specimens or via the widely used open access software tpsDig utilizing AntWeb digital images. We employed a complex statistical framework to test several aspects of reproducibility and reliability between the methods. We estimated (i) the agreement between the measurement methods and (ii) the trait value dependence of the agreement, then (iii) compared the coefficients of variation produced by the different methods, and finally, (iv) tested for systematic bias between the methods in a mixed modelling-based statistical framework.</span></p> <p><span>The stereomicroscope measurements were extremely precise. Our comparisons showed that agreement between the two methods was exceptionally high, without trait value dependence. Further, the coefficients of variation did not differ between the methods. However, we found systematic bias in eight traits: apart from one trait where software measurements overestimated the microscopic measurements, the former underestimated the latter.</span></p> <p><span>Our results shed light on the fact that relying solely on the level of agreement between methods can be highly misleading. In our case, even though the software measurements predicted microscope measurements very well, replacing traditional microscope measurements with software measurements, and especially mixing data collected by the different methods, might result in erroneous conclusions. We provide guidance on the best way to utilize virtual specimens (2D z-stacked images) as a source of morphometric data, emphasizing the method's limitations in certain fields and applications.</span></p>
Annotated dataset of microscope images of pollen grains from 40 beekeeping taxa
<p>The study of beekeeping flora and the analysis and identification of pollen collected by bees are important tools for beekeepers and researchers seeking to understand bee feeding habits and assess the ecological interactions between bees and plants. To identify the botanical origin of the pollen pellets collected by the bees, palynology method is mainly followed.</p><p>Pollen grains show great diversity, in terms of size, shape, symmetry and surface, as well as in terms of the number and type of their openings (apertures). They often present openings on their outer surface, serving as excellent diagnostic characters, as they show stability in their form and number. The most common types of openings are the pores, the sinuses, and the combination of the above, the anal canals. Pollen grains with pores are characterized as porate, those with sinuses as colpate, if they contain both as colporate. Depending on the number of openings, corresponding prefixes such as mono-, di-, tri- etc. precede the above terms. Also, the position of the openings, whether they are at the poles or in the equatorial zone, as well as their shape, are taken also into account.</p><p>Pollen size can be used as a diagnostic feature, but it shows great variability even within the same pollen grain. This is because it can be affected by various factors such as chemical treatment and the materials used in the creation of the preparations, genetic variability, etc. Specifically, a frequent phenomenon is the shrinking of pollen grains (harmomegathy or Wodehouse effect) resulting from the change in the bursting pressure of the cytoplasm during the hydration or dehydration of the pollen. Therefore, the degree of hydration is responsible for the actual shape and size of the pollen grains.</p><p>Considering all the above, a database was created including microscope images and characteristics (such as the type of pollen grain, the size, the type and number of openings, etc) of 40 taxa of major beekeeping importance.</p><p>Pollen in the form of pellets was crushed and a small amount was taken with special stainless steel forceps and then mixed with a drop of 20% glucose solution on a slide. Fuchsin solution was added and the preparation was spread over a 22 x 22 mm surface. The preparations were dried by gentle heating to 40°C, on a heating plate and a cover slip is placed to which a small amount of Entellan was added. All pollen grains were photographed on an optical microscope (Olympus SZX12), with lens 40× (Olympus DF PLAPO 1X DF), with a digital analysis camera (Olympus SC30), while a morphometry software (Image Pro Plus Software, V1.1.19) was used for their determination. For the microscopic identification of the pollen types, the collection of reference slides from the Laboratory of Apiculture of the Aristotle University of Thessaloniki, which is accredited to ISO 17025:2017, was used.</p><p>The dataset contains 3379 training captured microscope images of pollen grains from 40 major beekeeping taxa (class list can be found below) and 85 testing captured images. Polygon annotations (files train.json and val.json included) were created using LabelMe software and saved in COCO Annotation format.</p><p>Further information about the related project (SmartBeeKeep) can be found in the following article and presentation (please site if you use these data):</p><ul><li>Vasilios Liolios, Dimitrios Kanelis, Maria-Anna Rodopoulou, Chrysoula Tananaki (2023). A Comparative Study of Methods Recording Beekeeping Flora. Forests, 14(8), 1677; <a href="https://doi.org/10.3390/f14081677">https://doi.org/10.3390/f14081677</a> </li><li>Nikos Grammalidis, Andreas Stergioulas, Aggelos Avramidis, Konstantinos Karystinakis, Athanasios Partozis, Athanasios Topaloudis, Georgia Kalantzi, Chrisoula Tananaki, Dimitrios Kanelis, Vasilis Liolios, and Madesis Panagiotis "A smart beekeeping platform based on remote sensing and artificial intelligence", Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 127860C (21 September 2023); <a href="https://doi.org/10.1117/12.2681866%20">https://doi.org/10.1117/12.2681866</a> Event: Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprus <a href="https://smartbeekeep.eu/files/rscyp23_sbk_paper.pdf">Author preprint available</a></li></ul><p><strong>Annotation - Latin name</strong></p><p>Anthemis - Anthemis sp.</p><p>Asphodelus - Asphodelus fistulosus</p><p>Brassica napus - Brassica napus</p><p>Castanea - Castanea sativa </p><p>Cephalaria - Cephalaria transsylvanica</p><p>Chenopodium - Chenopodium album</p><p>Cichorium intybus - Cichorium intybus</p><p>Cistus - Cistus creticus</p><p>Cistus salvifolius - Cistus salvifolius</p><p>Convolvulus - Convolvulus arvensis</p><p>Daucus - Daucus carota</p><p>Echium - Echium plantagineum</p><p>Erica - Erica manipuliflora</p><p>Hederahelix - Hedera helix</p><p>Helianthus - Helianthus annuus</p><p>Heliotropium - Heliotropium europaeum</p><p>Hypericum - Hypericum perforatum</p><p>Lavandula - Lavandula angustifolia</p><p>Ligustrum - Ligustrum japonicum</p><p>Matricaria - Matricaria chamomilla</p><p>Olea - Olea europaea</p><p>Paliurus - Paliurus spina-christi</p><p>Papaver - Papaver rhoeas</p><p>Pinus - Pinus sp.</p><p>Polugonum - Polygonum aviculare</p><p>Portulaca - Portulaca oleracea</p><p>Pyrus spinosa - Pyrus spinosa</p><p>Quercussp - Quercus coccifera</p><p>Rosmarinus officinalis - Rosmarinus officinalis</p><p>Rubus - Rubus ulmifolius</p><p>Silybum marianum - Silybum marianum</p><p>Sinapis - Sinapis arvensis</p><p>sonchus - Sonchus asper</p><p>Taraxacum officinale - Taraxacum officinale</p><p>Tamarix - Tamarix sp.</p><p>Tilia intermedia - Tilia sp.</p><p>Tribulus - Tribulus terrestis</p><p>Trifolium - Trifolium campestre</p><p>Verbascum - Verbascum nigrum</p><p>Vicia vilosa - Vicia villosa</p>
Data from: Comparing ant morphology measurements from microscope and online AntWeb.org 2D z-stacked images
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.