List of Data Sets
identifier | Preview | has imaging details | has biological terms | has format | has Ground truth | |
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Segmentation of membrane of mouse, sea urchin and human oocytes from transmitted light images |
1908 | Oocyte, Label free, Maturation, cell membrane, mouse, human oocyte, sea urchin oocyte | Binary images associated with each source image of the oocyte cytoplasmic contour. |
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Movies of mouse oocyte maturation in transmitted light |
1907 | 2D images, 1 channel (transmitted light). Temporal resolution: every 3 min. Spatial resolution: 0.227 µm/pixel |
Oocyte, Meiosis, Maturation, mouse | tiff | ||
ShareLoc |
1834 | Dna-paint Storm
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microtubules, Nuclear pores , Actin, Vimentin, cytoskeleton | txt | ||
LIVECell |
1824 | Several wells for each cell type were seeded in 96-well plates (Corning) and imaged over the course of 3–5 d, every 4 h using an Incucyte S3 Live-Cell Analysis system (Sartorius) equipped with its standard CMOS camera (Basler acA1920-155um). The Incucyte HD phase-contrast imaging algorithm allows visualization of phase delays produced by cells without the phase annulus or phase ring found in conventional Zernike phase images. Because of this, LIVECell phase-contrast images are characterized by less pronounced halo artifacts and more high-frequency content than other phase-contrast modalities. Phase-contrast images were acquired using a ×10 objective from two positions in each well adding up to a total of 1,310 images (1,408 × 1,040 pixels corresponding to 1.75 × 1.29 mm2) that were each cropped into four equally sized images (704 × 520 pixels corresponding to 0.875 × 0.645 mm2) that were then annotated. |
cells, glioblastoma, breast cancer, Microglia, neuroblastoma, ovarian cancer | tif | Annotations are in JSON format and follow the COCO - Common Objects in Context (cocodataset.org) format. |
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Nanotomy: Large-scale electron microscopy (EM) datasets |
1783 | Includes data from CLEM, TEM and STEM, EDX, ... |
brain, cells, cell organelles | jpg | No segmentation mask available, but all data associated papers are available. |
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SNEMI3D: 3D Segmentation of neurites in EM images |
1719 | Volume EM |
neuron, neurites | tif | All labels (2D membrane probabilities and 3D labels) for 3D segmentation are provided for one data set, the other data sets has not known ground truth since it is used for the competition. |
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Cell-IDR |
1718 | Large range of imaging modalities, ranging from wide-field, super resolution,.. to spatial DNA sequencing |
cells | tif | ||
Tissue-IDR |
1717 | Both Brightfield with stains and fluorescence datasets of tissues |
tissue | tiff | ||
EMPIAR |
1716 | Contains 3D cryo-EM tomographs and maps, volume-em data sets , or hard and soft X-Ray tomography. FIB-SEM, SBF-SEM It also contains CLEM Correlative Light Electron Microscopy experiments... See the experiment list EMDB < Search results (ebi.ac.uk) for full list of modalities. |
cells, proteins | tiff | ||
Cytomine Open Collection |
1715 | From Brightfield slide scanning, with different stains. Available in tiff, svs or ndpi. |
tissue | tiff | No annotations associated |
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CXIDB |
1714 | Only from Coherent X-Ray imaging |
cells, yeast, Virus | No ground truth associated |
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Cell Image Library |
1713 | All Microscopy format accepted |
cells, cell organelles, tissue | tif | not associated to ground truth (such as segmentation mask) |
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Cell Tracking Challenge Dataset |
1667 | Microscopy settings for each dataset are available by clicking on the "More Details Button" |
cell motility, cell migration | tif | ||
Systems Science of Biological Dynamics database (SSBD:database) |
1644 | Diverse microscopes (mostly light microscopy, but some electronic microscopy as well). SSBD tries to store and curate 4D datasets, ie images that are 3D together with time element. |
It also stores all the qualitative data (i.e. segmented data or ROIs) separately as numerical datasets. Quantitative data are represented by using a unified data format, the Biological Dynamics Markup Language. |
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Nuclei segmentation in histopathology images |
1602 | histopathology, nuclei | The dataset contains ground truth annotation for the segmentation of the nuclei. |
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MoNuSeg - Multi-organ nuclei segmentation challenge |
1601 | histopathology, nuclei | ||||
FAIRsharing Euro-BioImaging collection |
1579 | Diverse |
Some have ground truth available, such as the Broad Bioimage Benchmark Collection (BBBC, https://doi.org/10.25504/FAIRsharing.j766zb, https://data.broadinstitute.org/bbbc). |
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muscle cross-sections |
1577 | Immunofluorescent sections were imaged on a Nikon AR1 confocal or Nikon Widefield CCD Microscope. Each confocal image is a composite of maximum projections, derived from stacks of optical sections. |
Muscle Stem Cells, Muscle | tiff | NO. Data used to exemplify muscleQNT: Muscle fiber counting |
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Mouse embryos |
1576 | There are 15 images. The images were acquired using a Nikon Eclipse TE200 microscope with a 20x, 0.45 NA objective lens and a 0.52 NA condenser lens, and are provided courtesy of the W.M. Keck 3D Fusion Microscope Facility at Northeastern University. Each image contains 640 x 480 pixels with an approximate size of 0.42 x 0.42 μm. |
embryo, cells | tiff | For the purpose of collecting ground truth, the samples were Hoechst-stained and imaged by confocal microscopy, and the cells were counted by a simple human. A tab-delimited text file contains cell counts in each of the 15 images. |
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two-photon images of dendritic spines |
1575 | Two-photon imaging was performed using a galvanometer-based scanning system (Prairie Technologies, acquired by Bruker Inc.) on an Olympus BX61WI equipped with 60X water immersion objective (0.9 NA), using a Ti:sapphire laser (Coherent Inc.) controlled by PrairieView software at 910 nm. Z-stacks (0.3 μm axial spacing) from secondary or tertiary dendrites from CA1 neurons were collected every 5 min for up to 4 h. The field of view was 19.8 × 19.8 μm at 1024 × 1024 pixels. |
Dendritic Spine | Annotated data and mask labels provided |
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Human colon tissue |
1574 | The dataset was generated using the virtual microscope imitating the microscope Zeiss S100 (objective Zeiss 63x/1.40 Oil DIC) attached to confocal unit Atto CARV and CCD camera Micromax 1300-YHS. |
tissue, cells | tiff | Ground Truth is provided as binary masks. |
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Clustered Cell Nuclei Data |
1573 | The dataset was generated using the virtual microscope imitating the microscope Zeiss S100 (objective Zeiss 63x/1.40 Oil DIC) attached to confocal unit Atto CARV and CCD camera Micromax 1300-YHS |
nuclei, HL60 cells | tiff | Ground Truth is provided as segmentation mask. |
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CSIRO science image library |
1571 | plant, textiles, minerals | ||||
Breast Cancer Histopathological Database (BreakHis) |
1569 | histopathology images - 700X460 pixels,RGB 8-bit images stored as PNG |
breast cancer, histopathology | Image patch classified as benign or malignant |
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Zebrafish larvae - Widefiled/Brightfield |
1559 | zebrafish | tif | |||
Medaka embryo in 96 well plate - Widefield Brightfield |
1558 | medaka, embryo | jpg | |||
ANHIR: Automatic Non-rigid Histological Image Registration |
1472 | pathology | The Ground truth is denoted using landmarks - key points that are marked consistently for each set of images with different stains. |
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BBBC002v1 |
1434 | There are 10 fields of view of each sample, for a total of 50 fields of view. The images were acquired on a Zeiss Axiovert 200M microscope. The images provided here are a single channel, DNA. The image size is 512 x 512 pixels. The images are provided as 8-bit TIFF files. |
Drosophila melanogaster, RNAi | tiff | A tab-delimited text file contains the number of cells in each image, as determined by two different human counters. To compare an algorithm's results to these, first compute for each sample the algorithm's mean cell count over the 10 images of the sample. Next, calculate the absolute difference between this mean and the average of the humans' counts for the sample, then divide by the latter to obtain the deviation from ground truth (in percent). The mean of these values over all 5 samples is the final result. Note: The two human observers vary by 16% for this image set. |
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Diadem challenge |
1191 | Imaging varies by neuron type and species, includes:
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neurite arbor, neuron, fiber | Manually traced digital neural reconstructions, |
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CREMI challenge |
1182 | Serial section Transmission Electron Microscopy (ssTEM). |
hdf5 |
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Arabidopsis plants (low resolution) |
1146 | Arabidopsis thaliana | jpg | |||
Arabidopsis plants (high resolution) |
1145 | Arabidopsis thaliana | ||||
leaves stained with gfp and rfp |
1143 | plant virurs, leaf infection | ||||
Artemia color images |
1139 | Artemia | tif | |||
Microtubules 3D |
1137 | microtubules, cytoskeleton | ||||
Arabidopsis thaliana seedlings |
1131 | Arabidopsis thaliana seedlings | jpg | |||
2D bright field yeast cell images with ground truth annotations |
41 | Bright field microscopy |
yeast | yes.
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