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438 results for “3D imaging”

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ClinicalTrials.gov32/100

3D-printed Bone Models in Addition to CT Imaging for Intra-articular Fracture Repair

ClinicalTrials.gov study NCT04748016. IPD Sharing: YES. Countries: 1. Publications: 18.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

Evaluation of Vascular Pathology With 3D, Time-Resolved Phase Contrast Magnetic Resonance Imaging (MRI)

ClinicalTrials.gov study NCT00722904. IPD Sharing: Not stated. Countries: 1. Publications: 12.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Optimization of Fetal Biometry With 3D Ultrasound and Image Recognition

ClinicalTrials.gov study NCT03812471. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

3D Imaging: Prognostic Role in Pulmonary Arterial Hypertension

ClinicalTrials.gov study NCT02799979. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

3D Contrast Enhanced Acoustic Perfusion Imaging in Adult After Subarachnoid Hemorrhage

ClinicalTrials.gov study NCT06793839. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2

ClinicalTrials.gov study NCT06646133. IPD Sharing: YES. Countries: 1. Publications: 6.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

Pilot Study of Topographic Imaging of the Calf Muscle in Patients With PAD Using 3D Reconstruction of MSOT Images

ClinicalTrials.gov study NCT05110677. IPD Sharing: NO. Countries: 1. Publications: 3.

closedIPD-NOFeb 2026View details →
dryad32/100

3D images of a turtle embryo

Open the record for dataset details and reuse information.

publicSep 2021View details →
dryad32/100

Data from: A new dimension in documenting new species: high-detail imaging for myriapod taxonomy and first 3D cybertype of a new millipede species (Diplopoda, Julida, Julidae)

Open the record for dataset details and reuse information.

publicJul 2016View details →
dryad32/100

Morphometric analysis of retinal ganglionic cells (3D confocal images) analyzed using filament tracer from Imaris software

Open the record for dataset details and reuse information.

publicDec 2024View details →
dryad32/100

fMRI/fPACT 3D image stacks and analysis codes for function

Open the record for dataset details and reuse information.

publicMar 2021View details →
dryad32/100

Original CT image stacks of five fossil petrosal bones from Siberia, 3D PDF files of reconstructed endocasts, blood vessels and innervation patterns, 3D PDF instruction file, STL files of the petrosals

Open the record for dataset details and reuse information.

publicDec 2021View details →
zenodo28/100

Fig. 6.12 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.12. Cost/efficiency ratio of digitisation for middle sized specimens. (CT is based on a rental service, while the others include the purchase of the equipment).

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 6.11 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.11. Comparison between the Focus Stacking Photogrammetry model (left) and the µCT model (right) of the Omorgus beetle. The models are very close, with the µCT model perhaps showing a little more detail. The µCT scan was made using a XRE UniTom at 60 kV and with a voxelsize of 29 µm. https://sketchfab.com/models/ad5fd157c5424c8fb793c1c282450d33

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 6.9 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.9. Omorgus beetle structured light scanning with MechScan (left) comparison to µCT scan (right). The main difference is the lack of artefacts due to the needle with the MechScan 3D model. But the MechScan model lacks almost the entire ventral area of the abdomen between the legs. https://sketchfab.com/models/9dc5082c8db14c92879947da927f07dc

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 6.8 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.8. Comparison between different treatments of the µCT model. Top and bottom left: µCT model without any treatment regarding removal of the artefacts https://sketchfab.com/models/169c2b29a1404e5cb5f6b6ea0928d075. Top and bottom in the middle: area affected by the metal artefact quickly cut out in GOM Inspect https://sketchfab.com/models/ f40a108e43ea44d78ca3d04ac41ad0a0; Top and bottom right: Carefully removed the needle through segmentation in Dragonfly 3.5. https://sketchfab.com/models/dc194a4e05da4f7ab787c8c7b028d2e7

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 6.7. Bone retoucher digitised with photogrammetry using a in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.7. Bone retoucher digitised with photogrammetry using a zoom lens (Ptg 18–55), a fixed focal macro lens (Ptg 100), focus stacking photogrammetry (FS-Ptg 60), structured light (SL) and microCT (µCT).

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 6.6 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.6. Detailed view of the sea urchins digitised with different equipment. The goal was to digitise the small punctures on the surface as these aid in identifying the species of the sea urchin.

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 5.2 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 5.2. Micro-contrast enhancement and relighting in DxO OpticsPro 11. The original image is on the left, the post-processed picture on the right. The dark area in the middle is now sufficiently exposed, without losing the look and feel of the specimen.

opencc-by-4.0Apr 2020View details →
zenodo28/100

Fig. 6.10 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.10. Comparison of the Photogrammetry (left) vs µCT models (right) of the Omorgus beetle. The large difference between them is the less pronounced detail in the photogrammetry model. To fully see the detailed differences, check the models online: https://sketchfab.com/models/a1fb6b8289f74c428782f43d502e771e

opencc-by-4.0Apr 2020View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record