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Dataset results
66 results for “3D Digitization”
Dataset for generation of LOD4 models for buildings towards the automated 3D modeling of BIMs and digital twins
<div> <div>This repository contains the dataset used for the automated image-based generation of LOD4 models for buildings, along with the corresponding results. The methodology utilizing this dataset was presented in the paper "Generation of LOD4 models for buildings towards the automated 3D modeling of BIMs and digital twins" by Pantoja-Rosero et., al. (2024) (https://doi.org/10.1016/j.autcon.2024.105822).</div> </div>
Dataset for Robot-mounted digital 3D-microscope versus standard microscope for spinal decompression surgery
<p>Compilation of all data collected in the study.</p> <p>- Depth Perception Robotc: Data collected during depth perception experiments with the BHS RoboticScope</p> <p>- Depth Perception Cons: Data collected during depth perception experiments with the OM</p> <p>- Both Scopes Combined: Combined data regarding depth perception experiments</p> <p>- Questionaire Combined: Combined data regarding cadaveric experiments</p> <p>- Questionaire expsurg1: completed questionnaire by the experienced surgeon 1</p> <p>- Questionaire expsurg3: completed questionnaire by the experienced surgeon 3</p>
Clinical Evaluation and Cost-effectiveness Analysis of 3D Digital Surgery in Traumatology
ClinicalTrials.gov study NCT06603831. IPD Sharing: YES. Countries: 1. Publications: 22.
Multi-Detector CT Angiography With 3D Reconstruction Versus Digital Subtraction Angiography
ClinicalTrials.gov study NCT05304572. IPD Sharing: Not stated. Countries: 1. Publications: 12.
Conventional Versus Digital 3D Printed Complete Removable Dentures
ClinicalTrials.gov study NCT05845099. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Data from: A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture
A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness.
Digital anthropomorphic breast simulators for 3D printing
<p><span>This work aims to provide STL file formats for the 3D printing of anthropomorphic digital breast simulators with varying complexities, including different tumour sizes. </span></p>
Collaborative annotation of 3D digital cultural heritage: A new FOSS toolchain
<p>A suite of tools for semantic annotation of 3D cultural artefacts is being developed as part of the <a href="https://nfdi4culture.de/">NFDI4Culture</a> project across several partner organisations (led by the <a href="https://www.tib.eu/de/forschung-entwicklung/forschungsgruppen-und-labs/open-science">Open Science Lab at TIB, Hannover</a>). Operating within Task area 1: Data capture and enrichment, the proposed toolchain focuses on the annotation of 3D data within an open knowledge graph environment, so that 3D objects’ metadata and related annotations can be linked to various resources, part of the semantic web and all data is searchable via a public SPARQL endpoint. </p>
Figure 8 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 8 Comparison of images taken with a Keyence VHX 5000 digital microscope (lens: Z20, A–C) and DISC3D (D). The whole specimen of Pogonocherus hispidus can be imaged at once with the VHX 5000 with a X30-magnification (A). To compare the digital resolution, we focus on the pronotum of the beetle (B: VHX 5000, ×30; C: VHX 5000, ×100, D: DISC3D, ×1.26). Scale bars: 1 mm.
Figure 7 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 7 Osmia adunca, two exemplary raw images of the front-light stack, with the focal plane going through the proximal (A) and the distal part (B) of the sample, the EDOF image (C), and a detail of the latter (D) demonstrate the resolution. Scale bars: 1 mm.
Figure 2 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 2 Illumination by two hemispherical white-coated domes (A–C). The back-light-dome can be removed for specimen mounting (D, E). No direct light from the LED-stripes hits the specimens (C, E).
Figure 17 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 17 Relation of surface area and volume for all insect species presented here. While the dipteran, hymenopteran and lepidopteran species had their wings unfolded, all beetles had the wings folded underneath their elytra. Models are not to scale.
Figure 3 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 3 The camera is mounted on a macro-rail (A). The camera position and orientation can be fine-tuned in all directions (B–D). The camera lens is covered by a pinhole-cap (B).
Figure 10 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 10 Comparison of dense-cloud-based mesh generation and visual consistency meshing of Thricops sp. (A EDOF image). Thin and delicate structure like wings and setae are not well modelled from the dense cloud (B) but well preserved by visual consistency meshing (C).
Figure 11 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 11 Comparison of mesh quality and number of polygons, exemplified by a model of the shell of Discus rotundatus. The model with 1 million faces (A) has a file size (3D-PDF) of 35 MB and shows more detail, but the reduced model with 75.000 faces (B) still well resembles the structure with a file size (3D-PDF) of only 3 MB.
Figure 9 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 9 Workflow of model generation of Pogonocherus hispidus with PhotoScan Pro. In total, 398 EDOF-images are taken with DISC3D (one example is shown in A). Using the image data, masks and camera positions estimated with the calibration sphere (see Fig. 6), a sparse cloud with optimized camera positions is generated (B). Two options for model generation are available: direct mesh calculation based on a dense point cloud (C) or meshing with visual consistency (D). Resulting meshes can be textured (E, F). Scale bar: 1mm.
Figure 12 from: Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1-27. https://doi.org/10.3897/zookeys.759.24584
Figure 12 Overview and size comparison of the specimens used in this study. Coleoptera: a Prosopocoilus savagei b Anoplotrupes stercorosus, *: specimen was broken during comparative measurements c Stenocorus meridianus d Typhaeus typhoeus e Rutpela maculata f Valgus hemipterus g Cryptocephalus sericeus h Pogonocherus hispidus i Phyllobius pyri j Tytthaspis sedecimpunctata; Lepidoptera: k Zygaena filipendulae; Hymenoptera: l Paraponera clavata m Osmia adunca n Sphecodes ephippius; Diptera: o Thricops sp., p Culex pipiens q Oscinella frit; Gastropoda: r Helicodonta obvoluta s Aegopinella nitens t Discus rotundatus.; Scale bar: 1 cm (keep in mind that not all specimens are equidistant to the lens; i.e., at the same height of the needle).
FIG. 32. Digital 3D in Cranial Morphology And Phylogenetic Relationships Of Trigonostylops Wortmani, An Eocene South American Native Ungulate
FIG. 32. Digital 3D reconstructions of the osseous labyrinths of Cochilius volvens AMNH VP-29651, Tetramerorhinus lucarius AMNH VP-9245, Tapirus indicus AMNH M-200300, Ceratotherium simum AMNH M-51882, and Equus caballus AMNH M-204155 (above and on opposite page), in lateral, ventral, and dorsal views. In each ventral view, arrow indicates position of fenestra cochleae.
Applicability of 3D Printing and 3D Digital Image Reconstruction in the Planning of Complex Liver Surgery (LIV3DPRINT).
ClinicalTrials.gov study NCT03416387. IPD Sharing: YES. Countries: 1. Publications: 0.
A Preliminary Study on Digital Learning Aids for Special Children With TRIZ and 3D Printing Technology
ClinicalTrials.gov study NCT05935462. IPD Sharing: Not stated. Countries: 1. Publications: 9.
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.