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ShareScore release 0.9.0
Dataset results
224 results for “ROI”
May to July 2018 regions of interest (ROIs) of tidal marsh and tidal forest plant species to be used as ground reference data in habitat mapping
We collected field data from sites distributed in habitats along the salinity axis of the Altamaha River estuary and the Duplin River to be used as ground reference data for habitat mapping. Regions of interest (ROIs) for tidal marsh (salt, brackish, tidal fresh) and tidal fresh forest vegetation species were generated near ground control points (GCP) by digitizing vegetation areas in ArcGIS 10.4 based on field maps.These observations will be used to create habitat maps from aerial photographs of the Altamaha River estuary, GA taken following Hurricane Irma to better understand how the storm surge affected tidal vegetation and to examine any shifts in vegetation type.
Kidney glomeruli-ROIs extracted from histological slides stained with HE or PAS.
<p>Kidney glomeruli-ROIs extracted from histological slides stained with HE or PAS. The multicenter test set of 78 regions of interest together with annotations. ROIs were extracted from 20 WSIs representing various human kidney pathologies. WSI's came from four sources: three independent medical centers and TCGA. Slides from three sources were stained with HE and slides from one center were stained with PAS. Slides were digitalized on Pannoramic 250 Flash II (3DHISTECH, Budapest, Hungary), Hamamatsu NanoZoomer S60 Digital slide scanner, or using Aperio AT Turbo (Leica Biosystems, Vista, CA). ROIs were extracted for x10, that corresponding to the pixel size ~10um.</p>
Quantification of ROIs corresponding to MQs from fluorescence in vivo imaging experiments
<p>We injected DIr labelled macrophages into mice carring immunolgical hot and cold KPC pancreatic tumors and quantified the recruitment to the tumor sites and lungs of the injected cells at different days after injection using fluorescence imaging. We hypotesized that macrophages would be recruited into tumor tissue and in prevalence into cold tumors.</p>
Language ROIs mixed between hemispheres
<p>We developed a new approach that assesses laterality of certain circuitry by calculating seedmaps using ROIs that involve <em>n </em>left-hemisphere (LH) and <em>m</em> right-hemisphere (RH) grayordinates, where <em>n+m</em> equals the total size of the original ROI.</p> <p>In essence, <em>n</em> grayordinates are randomly removed from the LH and added to the RH. This is done for each value of <em>n</em> 10 times to create different source ROIs to sample from.</p> <p>This project was done to study the language network, and so we publish three sets of ROIs: for "Broca's area" (inferior frontal gyrus), middle temporal gyrus, and a "Wernicke's area" near the temperoparietal junction.</p> <p>These ROIs were generated from the ventral attention network atlas published at <a href="http://neuroatlas.org">neuroatlas.org</a>.</p>
High-throughput in-situ plankton imaging from the East China Sea: raw images and acantharian ROIs
<p>Vertical imaging profiles were performed at four stations (3, 10, 15, 17; closed circles on the map) during the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) MR17-03C cruise from May 29 to June 13, 2017 with an ISIIS small-imager (<a href="https://www.planktonimaging.com/smaller-imagers">https://www.planktonimaging.com/smaller-imagers</a>) attached to the JAMSTEC DEEP TOW 6KCTD (<a href="https://www.jamstec.go.jp/e/about/equipment/ships/deeptow.html">https://www.jamstec.go.jp/e/about/equipment/ships/deeptow.html</a>). The ISIIS camera was programmed to take 1 photo per second coinciding with an LED flash. Each photo imaged 0.39 L (st. 3 and 10) or 0.35 L (st. 15 and 17) parcels of water in 2448 x 2050 pixel resolution, with each pixel being 22.5 µm. A Sea-Bird SBE 9 CTD was deployed with the DEEP TOW and the ISIIS internal clock was calibrated to match the CTD’s so that CTD data could be used to determine the depth at which each image was taken. Raw images are labeled with the time stamp. Acantharian ROIs are labeled with the timestamp for the raw image from which they were cropped. If more than one acantharian ROI was found in a single raw image, a letter was appended to the ROI file name. </p> <p>Accompanying data (CTD, sequencing) and analyses are available from the GitHub repository: <a href="https://github.com/maggimars/Acanth_ImageSeq">https://github.com/maggimars/Acanth_ImageSeq</a>.</p> <p> </p>
Crataegus crus-galli Du Roi (BR0000024837118)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000012593569)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000024837132)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000024837163)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000024837149)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000012562374)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000024837156)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Crataegus crus-galli Du Roi (BR0000024837101)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Hypericum kalmianum Du Roi (BR0000012453368)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
BOLD5000 Additional ROIs and RDMs for neural network research
<p>Artificial neural networks (ANNs) are sensitive to perturbations and adversarial attacks. One hypothesized solution to adversarial robustness is to align manifolds in the embedded space of neural networks with biologically grounded manifolds. Recent state-of-the-art works that emphasize learning robust neural representations, rather than optimizing for a specific target task like classification, support the idea that researchers should investigate this hypothesis. While works have shown that fine-tuning ANNs to coincide with biological vision does increase robustness to both perturbations and adversarial attacks, these works have relied on proprietary datasets- the lack of publicly available biological benchmarks make it difficult to evaluate the efficacy of these claims. Here, we deliver a curated dataset consisting of biological representations of images taken from two commonly used computer vision datasets, ImageNet and COCO, that can be easily integrated into model training and evaluation. Specifically, we take a large functional magnetic resonance imaging (fMRI) dataset (BOLD5000), preprocess it into representational dissimilarity matrices (RDMs), and establish an infrastructure that anyone can use to train models with biologically grounded representations. Using this infrastructure, we investigate the representations of several popular neural networks and find that as networks have been optimized for tasks, their correspondence with biological fidelity has decreased. Additionally, we use a previously unexplored graph-based technique, Fiedler partitioning, to showcase the viability of the biological data, and the potential to extend these analyses by extending RDMs into Laplacian matrices. Overall, our findings demonstrate the potential of utilizing our new biological benchmark to effectively enhance the robustness of models.</p>
Betula lenta Du Roi (BR0000014433597)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Betula lenta Du Roi (BR0000014433580)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Betula lenta Du Roi (BR0000014433566)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Betula lenta Du Roi (BR0000014433573)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Betula lenta Du Roi (BR0000014433559)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
ScienceDex guides
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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.