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54
datasets available to search
ShareScore release 0.9.0
Dataset results
54 results for “image diversity”
Image 10 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 10. Testudinella emarginula (Stenroos), ventral view
Image 8 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 8. Lecane stenroosi (Meissner), dorsal view
Image 9 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 9. Testudinella parva (Ternetz), ventral view
Image 6 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 6. Lecane haliclysta Harring & Myers, dorsal view
Image 4 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 4. Lophocharis salpina (Ehrenberg), lateral view
Image 3 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 3. Brachionus mirabilis Daday, ventral view
Image 2 in Faunal diversity of rotifers (Rotifera: Eurotatoria) of Nokrek Biosphere Reserve, Meghalaya, India
Image 2. Lecane unguitata (Fadeev), ventral view
Image 10 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 10, Rhacophorus pseudomalabaricus Vasudevan & Dutta, 2000
Image 4 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 4. Raorchestes anili (Biju & Bossuyt, 2006)
Image 1 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 1. Polypedates occidentalis Das & Dutta, 2006
Image 3 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 3. Raorchestes akroparallagi (Biju & Bossuyt, 2009)
Image 8. Rhacophorus calcadensis Ahl, 1927 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 8. Rhacophorus calcadensis Ahl, 1927
Image 2 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 2. Pseudophilautus kani (Biju & Bossuyt, 2009)
Image 2 in Studies on bird diversity of Overa- Aru Wildlife Sanctuary of Jammu and Kashmir, India
Image 2. Citrine Wagtail Motacilla
Image 5 in Diversity of rhacophorids (Amphibia: Anura) in Parambikulam Tiger Reserve, Western Ghats, Kerala, India
Image 5. Raorchestes jayarami (Biju & Bossuyt, 2009)
Image 7 in Catfish (Teleostei: Siluriformes) diversity in Karala River of Jalpaiguri District, West Bengal, India
Image 7. Mystus bleekeri (Day)
Image 6 in Catfish (Teleostei: Siluriformes) diversity in Karala River of Jalpaiguri District, West Bengal, India
Image 6. Wallago attu (Bloch & Schneider)
Image 1 in Catfish (Teleostei: Siluriformes) diversity in Karala River of Jalpaiguri District, West Bengal, India
Image 1. Amblyceps mangois (Hamilton)
Accompanying dataset for: "IBEX: An iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues"
<p>These datasets were acquired using either the manual or automated IBEX multiplex imaging protocols and accompany the manuscript “IBEX: An iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues”, A. Radtke <em>et al.</em>, 2021, Nature Protocols.</p> <p>All image data are stored using the <a href="https://imaris.oxinst.com/support/imaris-file-format">Imaris file format</a>. To view these multi-channel images, you can either use one of these <strong>free</strong> viewers, <a href="https://imaris.oxinst.com/imaris-viewer">Imaris viewer</a>, <a href="https://imagej.net/Fiji">Fiji</a>.</p> <p>Each experiment has an associated imaging meta-data file in xlsx format and the resulting image in Imaris format.</p> <p><strong>Human Jejunum (Automated)</strong></p> <p>Dataset is a 24 parameter IBEX experiment performed on a human jejunum section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Thunder 3D Cell Culture microscope with a high precision (Quantum) stage, a high quantum efficiency sCMOS camera (DFC9000 GTC), and a 40x (1.3) NA oil objective. The light source was an LED8 with 8 individual LED lines for excitation with millisecond triggering. All images were captured at a 16-bit depth with the following pixel dimensions: x (0.160 μm), y (0.160 μm), and z (1 μm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.7.1.21655).</p> <p><strong>Human Kidney (Automated)</strong></p> <p>Dataset is a 16 parameter IBEX experiment performed on a human kidney Formalin-Fixed Paraffin-Embedded (FFPE) section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Thunder 3D Cell Culture microscope with a high precision (Quantum) stage, a high quantum efficiency sCMOS camera (DFC9000 GTC), and a 40x (1.3) NA oil objective. The light source was an LED8 with 8 individual LED lines for excitation with millisecond triggering. All images were captured at a 16-bit depth with the following pixel dimensions: x (0.160 μm), y (0.160 μm), and z (1 μm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.7.1.21655).</p> <p><strong>Human Lymph Node (Automated)</strong></p> <p>Dataset is a 25 parameter IBEX experiment performed on a human lymph node section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Thunder 3D Cell Culture microscope with a high precision (Quantum) stage, a high quantum efficiency sCMOS camera (DFC9000 GTC), and a 40x (1.3) NA oil objective. The light source was an LED8 with 8 individual LED lines for excitation with millisecond triggering. All images were captured at a 16-bit depth with the following pixel dimensions: x (0.160 μm), y (0.160 μm), and z (1 μm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.7.1.21655).</p> <p><strong>Human Skin (Automated)</strong></p> <p>Dataset is an 18 parameter IBEX experiment performed on a human skin section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Thunder 3D Cell Culture microscope with a high precision (Quantum) stage, a high quantum efficiency sCMOS camera (DFC9000 GTC), and a 40x (1.3) NA oil objective. The light source was an LED8 with 8 individual LED lines for excitation with millisecond triggering. All images were captured at a 16-bit depth with the following pixel dimensions: x (0.160 μm), y (0.160 μm), and z (1 μm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.7.1.21655).</p> <p><strong>Human Liver (Manual)</strong></p> <p>Dataset is a 22 parameter IBEX experiment performed on a human liver section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976).</p> <p><strong>Human Lymph Node (Manual)</strong></p> <p>Dataset is a 38 parameter IBEX experiment performed on a human lymph node section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976).</p> <p><strong>Human Spleen (Manual)</strong></p> <p>Dataset is a 25 parameter IBEX experiment performed on a human spleen section labeled with the nuclear marker Hoechst and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976).</p>
PRMI: A dataset of minirhizotron images for diverse plant root study
<p>Understanding a plant's root system architecture (RSA) is crucial for a variety of plant science problem domains including sustainability and climate adaptation. Minirhizotron (MR) technology is a widely-used approach for phenotyping RSA non-destructively by capturing root imagery over time. Precisely segmenting roots from the soil in MR imagery is a critical step in studying RSA features. In this paper, we introduce a large-scale dataset of plant root images captured by MR technology. In total, there are over 72K RGB root images across six different species including cotton, papaya, peanut, sesame, sunflower, and switchgrass in the dataset. The images span a variety of conditions including varied root age, root structures, soil types, and depths under the soil surface. All of the images have been annotated with weak image-level labels indicating whether each image contains roots or not. The image-level labels can be used to support weakly supervised learning in plant root segmentation tasks. In addition, 63K images have been manually annotated to generate pixel-level binary masks indicating whether each pixel corresponds to root or not. These pixel-level binary masks can be used as ground truth for supervised learning in semantic segmentation tasks. By introducing this dataset, we aim to facilitate the automatic segmentation of roots and the research of RSA with deep learning and other image analysis algorithms.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.