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Dataset results
232 results for “Optical images”
Wide-field optical imaging of electrical charge and chemical reactions at the solid-liquid interface
<p>Data availability for silica measurements</p>
In Situ Volumetric Imaging and Analysis of FRESH 3D Bioprinted Constructs Using Optical Coherence Tomography (Data and 3D models)
<p>These files contain 3D models and reconstructions of the 3D printed models after OCT imaging of the brain stem, circle of willis, kidney, vestibular apparatus, mixing network, and resolution text. These are from the journal article "In Situ Volumetric Imaging and Analysis of FRESH 3D Bioprinted Constructs Using Optical Coherence Tomography" published in <em>Biofabrication </em>(2022).</p>
Experimental Data for 'Beyond memory-effect matrix-based imaging in scattering media by acousto-optic gating'
<p>This repository contains the data used in Figures 3 and 4 of our study on noninvasive imaging beyond the optical memory-effect utilizing acousto-optic gating. The data files are organized into two folders: 'Figure 3' and 'Figure 4'. All data files can be loaded using PyTorch.</p> <p><strong>Folder Structure and Content:</strong></p> <ol> <li> <p><strong>Figure 3:</strong></p> <ul> <li>This folder contains the measurements that have been digitally propagated to the conjugated plane.</li> <li>The folder also includes a ground truth file named 'object_direct_imaging.trc'.</li> </ul> </li> <li> <p><strong>Figure 4:</strong></p> <ul> <li>This folder contains two data files: <ul> <li>One file includes measurements with acoustic modulation.</li> <li>The other file includes measurements without acoustic modulation.</li> </ul> </li> <li>The folder also contains a ground truth file named 'digits_direct_imaging.trc'.</li> </ul> </li> </ol> <p> </p>
Quantitative measures of corneal transparency, derived from objective analysis of depth-resolved corneal images, demonstrated with full-field optical coherence tomographic microscopy
<p>Supporting data for: <a href="https://zenodo.org/record/2579947">Quantitative measures of corneal transparency, derived from objective analysis of depth-resolved corneal images, demonstrated with full-field optical coherence tomographic microscopy</a></p>
Fig. 1 a –d Marine benthic organisms used for bio-optical measurements. a Boneccia viridis, b Isodictya pacmata, c Hymedesmia paupertas, d in Development of hyperspectral imaging as a bio-optical taxonomic tool for pigmented marine organisms
Fig. 1 a –d Marine benthic organisms used for bio-optical measurements. a Boneccia viridis, b Isodictya pacmata, c Hymedesmia paupertas, d Hymedesmia sp.
Imaging through scattering media by exploiting the optical memory effect: a tutorial
<p>Raw data used to generate figures 1, 4, 5, and 6, plus a Matlab and a Mathematica code to analyse the data.</p>
Input SAR and Optical images for DIL-SDS model
<p>This dataset contains the input SAR and Optical images used in the DIL-SDS model, described in the https://github.com/yongjingmao/DIL_SDS. </p>
Rock glacier inventory from multi-temporal InSAR measurement and optical image interpretation in southern Daxue Shan
<p>Based on the Sentinel-1A ascending SAR images acquired between June 2019 and June 2022, we derived a five-year-long annual average velocity map in southern Daxue Shan. Kinematic characteristics from InSAR measurement and geomorphic characteristics from optical image interpretation are then considered comprehensively for rock glaciers inventorying. A total of 860 rock glaciers are compiled and their geomorphic and kinematic parameters are calculated.</p>
Deep Ensemble Learning and Transfer Learning Methods for Classification of Senescent Cells from Nonlinear Optical Microscopy Images
<p>This Dataset contains the train and test NLO images in pickle format used for the following publication: Deep Ensemble Learning and Transfer Learning Methods for Classification of Senescent Cells from Nonlinear Optical Microscopy Images</p>
A Fundus Image Dataset for Domain Generalization in Joint Segmentation of Optic Disc and Optic Cup
<p>We provide a fundus image dataset for domain generalization, which includes 5 different medical centres.<br> This dataset is based on the REFUGE[1] dataset, Drishti-GS[2] dataset, ORIGA[3] dataset, and RIGA[4] dataset. We appreciate their efforts devoted by the authors of [1-4].</p> <table> <caption>Details of this dataset</caption> <tbody> <tr> <td>Domain</td> <td>Cases in Each Domain<br> (Training/Test)</td> </tr> <tr> <td>REFUGE</td> <td>320/80</td> </tr> <tr> <td>Drishti-GS</td> <td>50/51</td> </tr> <tr> <td>ORIGA</td> <td>500/150</td> </tr> <tr> <td>BinRushed (RIGA)</td> <td>156/39</td> </tr> <tr> <td>Magrabia (RIGA)</td> <td>76/19</td> </tr> </tbody> </table> <p>[1] Orlando J I, Fu H, Breda J B, et al. Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs[J]. Medical image analysis, 2020, 59: 101570.</p> <p>[2] Sivaswamy J, Krishnadas S R, Joshi G D, et al. Drishti-GS: Retinal image dataset for optic nerve head (onh) segmentation[C]//2014 IEEE 11th international symposium on biomedical imaging (ISBI). IEEE, 2014: 53-56.</p> <p>[3] Zhang Z, Yin F S, Liu J, et al. Origa-light: An online retinal fundus image database for glaucoma analysis and research[C]//2010 Annual international conference of the IEEE engineering in medicine and biology. IEEE, 2010: 3065-3068.</p> <p>[4] Almazroa A, Alodhayb S, Osman E, et al. Retinal fundus images for glaucoma analysis: the RIGA dataset[C]//Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications. SPIE, 2018, 10579: 55-62.</p> <p>If you find this dataset useful for your research, please consider citing the paper as follows:</p> <pre><code class="language-markdown">@article{chen2023treasure, title={Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image Segmentation}, author={Chen, Ziyang and Pan, Yongsheng and Ye, Yiwen and Cui, Hengfei and Xia, Yong}, booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2023}, year={2023} }</code></pre> <p> </p>
Data underlying: High-Field Optical Cesium Magnetometer for Magnetic Resonance Imaging
<p>This is the data used in the work "High-Field Optical Cesium Magnetometer for Magnetic Resonance Imaging" by Hans Stærkind, Kasper Jensen, Vincent O. Boer, Esben Thade Petersen and Eugene S. Polzik.</p> <p>Scripts for calculations done in the article are also included.</p>
Panitumumab IRDye800 Optical Imaging Study
ClinicalTrials.gov study NCT02415881. IPD Sharing: NO. Countries: 1. Publications: 3.
OPtical Frequency Domain Imaging vs. INtravascular Ultrasound in Percutaneous Coronary InterventiON
ClinicalTrials.gov study NCT01873027. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Spectral Domain OCT Imaging in Patients With Optic Nerve Head Drusen (Tuebingen SD-OCT IN OPTIC NERVE HEAD DRUSEN STUDY)
ClinicalTrials.gov study NCT02793206. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Real-time Quantitative Optical Perfusion Imaging in Surgery
ClinicalTrials.gov study NCT02902549. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Optical Imaging as a Tool for Monitoring Brain Function in Fragile X Syndrome
ClinicalTrials.gov study NCT06293027. IPD Sharing: NO. Countries: 1. Publications: 2.
Optical Surface Imaging Versus Conventional Photography as a Tool to Document the Surface Geometry of Pectus Excavatum
ClinicalTrials.gov study NCT04185870. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Adjunctive Efficacy Study Of The SoftScan® Optical Breast Imaging System
ClinicalTrials.gov study NCT00267449. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Ultrahigh-resolution Optical Coherence Tomography Imaging of the Anterior Eye Segment Structures
ClinicalTrials.gov study NCT03461978. IPD Sharing: NO. Countries: 1. Publications: 3.
Optical Frequency Domain Imaging (OFDI) Assessed Strut Coverage of New Terumo DES
ClinicalTrials.gov study NCT01844843. IPD Sharing: Not stated. Countries: 3. Publications: 1.
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.