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250 results for “3D scan”
EnderScope: A low-cost 3D printer based scanning microscope for microplastic detection
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Pelagomacellicephala iliffei MicroCT-Scans for 3D reconstruction
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Data from: Digitizing extant bat diversity: an open-access repository of 3D μCT-scanned skulls for research and education
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Harmothoe imbricata MicroCT-scans for 3D reconstruction
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Branchipolynoe sp. MicroCT-Scans for 3D reconstruction
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Gesiella jameensis MicroCT-scans for 3D reconstruction
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Macellicephala longipalpa MicroCT-scans for 3d reconstruction
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Drieschia sp. MicroCT-Scans for 3D reconstruction
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Measuring avian bill size: Comparing and evaluating 3D surface scanning with traditional size estimates in Australian birds
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Dynamic 3D X-ray micro-CT data of a tablet dissolution in a water-based gel with dynamic changes in the scanning geometry
<p><strong>Summary</strong></p> <p>This submission contains a dynamic tomographic X-ray data of a tablet dissolving in a water-based gel. The data is collected over a 5-minute period during which the sample is rotated rapidly as effervescent bubbles are formed and travelling to the surface of the gel.</p> <p>This is the second experiment detailed in Case Study 3 in [Coban 2020], and this submission can be treated as a follow up to [Coban&Lucka 2019]. </p> <p> </p> <p><strong>Apparatus</strong></p> <p>The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].</p> <p> </p> <p><strong>Sample Information</strong></p> <p>The setup consists of a store-bought denture cleaning tablet, placed at the bottom of a clear cylindrical plastic container. These tablets are typically designed to be fast-dissolving, and produce small and compact channels of bubbles. We use a denture cleaning tablet in particular as the dissolution time in water varies from 3 to 5 minutes, meaning the bubbles are produced at a slower rate. In addition, we use a store-bought water-based gel instead of water to slow down the bubble displacement during the experiment.</p> <p> </p> <p><strong>Experimental Plan</strong></p> <p>This experiment is performed such that 150 projections are collected over 360 degrees, for a total of 166 rotations, with exposure time 12 ms for each projection. This means that in total the submission contains 25000 projections. This experiment took 5 minutes of acquisition time, during which we (at user's command) zoom in onto the bottom of the sample holder (i.e. where the tablet rests). We later (again, at user's command) shift the view (i.e. the tube and the detector) upwards to the top of the sample to observe foaming on the surface. Finally, before the end of the 5-minute acquisition period, we zoom out to the original magnification. Every time the geometry undergoes a major change such as zooming in (which would affect the reconstruction), the system creates a new data settings file with the new geometrical information, appended by the projection number, therefore marking the change. However, since there is no major change created by the vertical shift of the tube and detector (as in no change in geometry that would affect the reconstructed images), there is no new data settings file for this event. </p> <p>The spatial resolution for this data is 193μm at the beginning (or end) of the experiment, which at an arbitrary point changes to 76μm. For a smooth data transfer, each projection image is binned down to the size of 486px-by-384px. No centrifugal force effect was observed on the bubbles travelling during the scan or in our test runs at the given rotational speed.</p> <p>All raw data (i.e. with no corrections) is made available in .tif format.</p> <p> </p> <p><strong>List of Contents</strong></p> <p>The contents of the submission is given below.</p> <ul> <li><strong>scan_1</strong>: A 5-minute dynamic CT data folder containing <ul> <li>dark-field (or closed-shutter) image, <em>di000000.tif,</em></li> <li>pre flat-field (or open-shutter before acquisition) image, <em>io000000.tif</em>,</li> <li>post flat-field (or open-shutter after acquisition) image, <em>io000001.tif</em>,</li> <li>raw (unprocessed or uncorrected) projections, <em>scan_*.tif</em> (25000 projections in total),</li> <li><em>data settings XRE.txt</em>, a text file with scanner metadata (this is the final geometry info file),</li> <li><em>data settings XRE_5220.txt</em> (geometry info recorded after the zoom-in)</li> <li><em>data settings XRE__22610.txt</em> (geometry info recorded after the zoom-out, same as <em>data settings XRE.txt</em>)</li> </ul> </li> </ul> <p> </p> <p><strong>Additional Links</strong></p> <p>These datasets are produced by the <a href="https://www.cwi.nl/research/groups/computational-imaging">Computational Imaging group</a> at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl</li> </ul> <p> </p> <p><strong>Acknowledgments</strong></p> <p>We thank Dr. Samuel McDonald and Prof. Philip Withers for the useful discussion, and Dr. Manuel Dierick for his advice in making this experiment possible.</p>
Landmarks and 3D scan data of Macaca fascicularis
<p><b>Objectives</b>: Magnitudes of morphological integration may constrain or facilitate craniofacial shape variation. The aim of this study was to analyze how the magnitude of integration in the skull of <i>Macaca fascicularis</i> changes throughout ontogeny in relation to developmental and/or functional modules.</p> <p><b>Materials and Methods</b>: Geometric morphometric methods were used to analyze the magnitude of integration in the macaque cranium and mandible in 80 juvenile and 40 adult <i>M. fascicularis</i> specimens. Integration scores in skull modules were calculated using ICV (Integration Coefficient of Variation of eigenvalues) based on a resampling procedure. Resultant ICV scores between the skull as a whole, and developmental and/or functional modules were compared using Mann-Whitney U tests.</p> <p><b>Results</b>: Results showed that most skull modules were more tightly integrated than the skull as a whole, with the exception of the chondrocranium in juveniles without canines, the chondrocranium/face complex and the mandibular corpus in adults, and the mandibular ramus in all juveniles. The chondrocranium/face and face/mandibular corpus complexes were more tightly integrated in juveniles than adults, possibly reflecting the influences of early brain growth/development, and the changing functional demands of infant suckling and later masticatory loading. This is also supported by the much higher integration of the mandibular ramus in adults compared with juveniles.</p> <p><b>Discussion</b>: Magnitudes of integration in skull modules reflect developmental/functional mechanisms in <i>M. fascicularis</i>. However, the relationship between 'evolutionary flexibility' and developmental/functional mechanisms was not direct or simple, likely because of the complex morphology, multifunctionality, and various ossification origins of the skull.</p>
Femur Bone 3D Scan
Femur bone scanned with Metron E 3D scanner. Source: Objaverse 1.0 / Sketchfab
Antique Axe Head 3D Scanned Model Vintage Tool
Antique Single Bit Axe head we scanned in the LITEStudio, our multi function photo studio and 3D scanner. Looks like a Kentucky style Axe head, could be a Georgia or Virginia style as well. Source: Objaverse 1.0 / Sketchfab
Old building 3d scan
Photogrammetry scan of old building 8k texture and normals Source: Objaverse 1.0 / Sketchfab
FIGURE 6. 3D in Confocal laser scanning microscopy technique for the study of internal genitalia and external morphology of eriophyoid mites (Acari: Eriophyoidea)
FIGURE 6. 3D-reconstruction of the internal genitalia of Phytoptus rigidus, bottom view (the same female as Fig. 2A). A. spermathecae, B. spherical spermathecal tube, C. capsule-like reservoir in the connection of two spermathecal tubes, D. transversal genital apodeme, E. distal folder of transversal genital apodeme, F. longitudinal genital? apodeme1 (includes two sclerotised plates), G. epigynium.
Hampi Snanagraha 3D Scan from drone
https://goo.gl/maps/DbSub8M4eHG2 Source: Objaverse 1.0 / Sketchfab
Femur Bone 3D Scan
Femur bone scanned with Metron E 3D scanner. Source: Objaverse 1.0 / Sketchfab
3d scan Sextant
textured sextant Source: Objaverse 1.0 / Sketchfab
Asphalt Texture 3D scan
Photogrammetry Asphalt Lowpoly model Source: Objaverse 1.0 / Sketchfab
Ganapathi Vigraha - 3D Scan with SLR
Source: Objaverse 1.0 / Sketchfab
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.