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469
datasets available to search
ShareScore release 0.9.0
Dataset results
469 results for “Image analysis”
Computational Cardiac Imaging Analysis to Guide Ventricular Tachycardia Ablation Procedures (AI-VT)
ClinicalTrials.gov study NCT06964152. IPD Sharing: YES. Countries: 1. Publications: 1.
The Application of Non-invasive and Cellular Level Resolution Fullfield Optical Coherence Tomography: Establishment and Analysis of Subcutaneous Cellular Level Image Database of Anatomical Locations i
ClinicalTrials.gov study NCT04406454. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Retrospective Analysis of the Correlation Between Imaging Features and Pathology, Prognosis in Renal Tumors
ClinicalTrials.gov study NCT06167863. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Efficient Automated Localization of ECoG Electrodes in CT Images Via Shape Analysis
ClinicalTrials.gov study NCT04479410. IPD Sharing: NO. Countries: 1. Publications: 7.
Age Estimation From Pulp Cavity Analysis Using Cone Beam Computed Tomographic Images for Forensic Purposes
ClinicalTrials.gov study NCT05130164. IPD Sharing: NO. Countries: 1. Publications: 1.
Semi-manual Vessel Density Analysis on Optical Coherence Tomography Angiography Images of Healthy Adults
ClinicalTrials.gov study NCT03590899. IPD Sharing: NO. Countries: 1. Publications: 20.
Analysis of Headache Chronification With Imaging, Deep Phenotyping, and Proteomics
ClinicalTrials.gov study NCT03231241. IPD Sharing: NO. Countries: 1. Publications: 1.
Differentiating three Indian shads by applying shape analysis from digital images
Open the record for dataset details and reuse information.
Data from: BMI and WHR are reflected in female facial shape and texture: a geometric morphometric image analysis
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Data from: Ranking quantitative resistance to Septoria tritici blotch in elite wheat cultivars using automated image analysis
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Data from: Using R-based image analysis to quantify rusts on perennial ryegrass
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Data from: LiDAR and RGB-image analysis to predict hairy vetch biomass in breeding nurseries
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Orbit Image Analysis: an open-source whole slide image analysis tool
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Diagnostic Accuracy of Adrenal Imaging for Subtype Diagnosis in Primary Aldosteronism: Systematic Review and Meta-Analysis
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Morphometric analysis of retinal ganglionic cells (3D confocal images) analyzed using filament tracer from Imaris software
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fMRI/fPACT 3D image stacks and analysis codes for function
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Automated analysis of scanning electron microscopic images for assessment of hair surface damage
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Root crown images of soybean and wheat and statistical analysis for RhizoVision Crown
<p>This repository contains raw image data of root crowns imaged using the backlit RhizoVision Crown platform of soybean and wheat plants phenotyped in Missouri and Oklahoma, respectively, as described in the below manuscript. Data files and the R scripts are included for complete statistical analysis associated with the imaged root crown set as well as validation using images of copper wires and simulated root images. We request any reuse of this data to both cite this repository and also the publication given below.</p> <p><strong>Citation:</strong></p> <p>Seethepalli, A., Guo, H., Liu, X., Griffiths. M. G., Almtarfi, H., Li, Z., Liu, S., Zare, A., Fritschi, F., Blancaflor, E., Ma, X., and York, L. M. (2020). RhizoVision Crown: An integrated hardware and software platform for root crown phenotyping. <em>Plant Phenomics. doi:10.34133/2020/3074916</em></p> <p><strong>Link: </strong><a href="https://spj.sciencemag.org/plantphenomics/2020/3074916/">https://spj.sciencemag.org/plantphenomics/2020/3074916/</a></p> <p>Root crown images were acquired using the RhizoVision Imager software available at:</p> <p><a href="https://zenodo.org/record/2585882#.XWgOAeNKiUk">https://zenodo.org/record/2585882#.XWgOAeNKiUk</a></p> <p>Image analysis of physical wires, simulated dicot and monocot root systems, and soybean and wheat root crowns was originally conducted with RhizoVision Analyzer. However, Analyzer has been replaced by RhizoVision Explorer that uses the same underlying algorithms and the analysis can be recreated using the 'whole root' mode of Explorer, available here:</p> <p><a href="https://zenodo.org/record/4095629">https://zenodo.org/record/4095629</a></p> <p><strong>Image Files</strong></p> <p>physical_validation_wires.zip - A set for validation of physical units using 10 images of 2 individual wires of 5 gauges (10, 16, 22, 28, 32) in PNG format acquired using the RhizoVision Crown hardware platform. Includes a CSV file containing measured length and diameters as well as those from image analysis using RhizoVision Analyzer.</p> <p>Soybean_RVC_RootCrowns.zip - 2,778 greyscale images in PNG format of field excavated soybean root crowns.</p> <p>Wheat_RVC_RootCrowns.zip - 1,754 greyscale images in PNG format of field excavated wheat root crowns.</p> <p>metadata_Analyzer_allImageSets.zip - CSV files with the metadata files output by the RhizoVision Analyzer software for the physical validation, validation of simulated dicots and monocots (described in preprint), and the soybean and wheat root crown images. Useful to see thresholding and physical resolution settings.</p> <p>The simulated monocot and dicot root systems images and associated data are described in the preprint and available from Lobet et al. here:</p> <p>Lobet, Guillaume, Koevoets, Iko, Noll, Manuel, Tocquin, Pierre, Meyer, Patrick E, Pagès, Loic, & Périlleux, Claire. (2016). Library of simulated root images, with different noise levels [Data set]. Zenodo.</p> <p><a href="https://zenodo.org/record/208214">https://zenodo.org/record/208214</a></p> <p><strong>Statistical Analysis</strong></p> <p>Rcode_allData.zip - Contains a single .R text file with code to reproduce all statistics and data figures. Contains several .CSV data files used by the R code. Assumption for running is that R code and data files are in the same working directory and setwd() is set there. Also, libraries needed are called at the top of the script and need to be previously installed.</p> <p><strong>Hardware Plans</strong></p> <p>RhizoVision_Crown_Hardware_Plans_Details.pdf - For completeness, hardware plans for the RhizoVision Crown platform as described in the manuscript are included. Currently, we recommend the following camera and lens to use in this system:</p> <p>Basler 5472 monochrome usb camera</p> <p><a href="https://graftek.biz/products/basler-aca5472-17um">https://graftek.biz/products/basler-aca5472-17um</a></p> <p>This Moritex 25 mm lens:</p> <p><a href="https://graftek.biz/products/moritex-ml-u2515sr-18c?">https://graftek.biz/products/moritex-ml-u2515sr-18c?</a></p> <p><br> <br> ⇒ Version 2 of this repository includes updates based on peer-review of the manuscript. New versions of physical_validation_wires.zip and Rcode_allData.zip were uploaded.</p> <p>⇒ Version 3 of this repository includes updates based on peer-review of the manuscript. A new version of Rcode_allData.zip was uploaded.</p>
Data from: Image Calibration and Analysis Toolbox – a free software suite for measuring reflectance, colour, and pattern objectively and to animal vision
1. Quantitative measurements of colour, pattern, and morphology are vital to a growing range of disciplines. Digital cameras are readily available and already widely used for making these measurements, having numerous advantages over other techniques, such as spectrometry. However, off-the-shelf consumer cameras are designed to produce images for human viewing, meaning that their uncalibrated photographs cannot be used for making reliable, quantitative measurements. Many studies still fail to appreciate this, and of those scientists who are aware of such issues, many are hindered by a lack usable tools for making objective measurements from photographs. 2. We have developed an image processing toolbox that generates images that are linear with respect to radiance from the RAW files of numerous camera brands, and can combine image channels from multispectral cameras, including additional ultraviolet photographs. Images are then normalised using one or more grey standards to control for lighting conditions. This enables objective measures of reflectance and colour using a wide range of consumer cameras. Furthermore, if the camera's spectral sensitivities are known, the software can convert images to correspond to the visual system (cone-catch values) of a wide range of animals, enabling human and non-human visual systems to be modelled. The toolbox also provides image analysis tools that can extract luminance (lightness), colour, and pattern information. Furthermore, all processing is performed on 32-bit floating point images rather than commonly used 8-bit images. This increases precision and reduces the likelihood of data loss through rounding error or saturation of pixels, while also facilitating the measurement of objects with shiny or fluorescent properties. 3. All cameras tested using this software were found to demonstrate a linear response within each image and across a range of exposure times. Cone-catch mapping functions were highly robust, converting images to several animal visual systems and yielding data that agreed closely with spectrometer-based estimates. 4. Our imaging toolbox is freely available as an addition to the open source ImageJ software. We believe that it will considerably enhance the appropriate use of digital cameras across multiple areas of biology, in particular researchers aiming to quantify animal and plant visual signals.
Data from: High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: application to invasive breast cancer detection
Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200x200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500x500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (~6 million of samples in 24 hours) with far fewer samples (~2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%.
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.