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438 results for “3D imaging”
Figures 25-30 from: Schmidt J, Scholz S, Will K (2022) Character analysis and descriptions of Eocene sphodrine fossils (Coleoptera, Carabidae) using light microscopy, micro-CT scanning, and 3D imaging. Deutsche Entomologische Zeitschrift 69(1): 19-44. https://doi.org/10.3897/dez.69.79931
Figures 25-30 Quasicalathus agonicollis sp. nov., light microscopic images of specimen "GZG 16188" (25–26.) and the holotype (28–30.). 25. Posterior part of pronotum and anterior part of elytra, right side; 26. Anterior part of fifth interval of left elytra showing microsculpture; 27. Posterior part of elytra (the arrows point to the insertions of the discal setae); 28. General view of the amber piece; 29. Right dorsal view of beetle body (the arrow points to the insertion of the discal seta on left elytron); 30. Left ventral view. Abbreviations: bs – insertion of the pronotal laterobasal seta; hm – humerus; m – mite (syninclusion).
Supplementary 1: Underwater photogrammetry for close-range 3D imaging of dry-sensitive objects: The case study of cephalopod beaks
<ul> <li>Technical advances in 3D imaging have contributed to quantifying and understanding biological variability and complexity. However, small, dry-sensitive objects are not easy to reconstruct using common and easily available techniques such as photogrammetry, surface scanning, or micro-CT scanning. Here we use cephalopod beaks as an example as their size, thickness, transparency, and dry-sensitive nature make them particularly challenging. We developed a new, underwater, photogrammetry protocol in order to add these types of biological structures to the panel of photogrammetric possibilities.</li> <li>We used a camera with a macro-photography mode in a waterproof housing fixed in a tank with clear water. The beak was painted and fixed on a colored rotating support. Three angles of view, two acquisitions, and around 300 pictures per specimen were taken in order to reconstruct a full 3D-model. These models were compared to others obtained with micro-CT scanning to verify their accuracy.</li> <li>The models can be obtained quickly and cheaply compared to micro-CT scanning, and have sufficient precision for quantitative inter-specific morphological analyses. Our work shows that underwater photogrammetry is a fast, non-invasive, efficient, and accurate way to reconstruct 3D models of dry-sensitive objects while conserving their shape. While the reconstruction of the shape is accurate, some internal parts cannot be reconstructed with photogrammetry as they are not visible. In contrast, these structures are visible using reconstructions based on micro-CT scanning. The mean difference between both methods is very small (10<sup>-5</sup> to 10<sup>-4</sup> mm) and is significantly lower than differences between meshes of different individuals.</li> <li>This photogrammetry protocol is portable, easy-to-use, fast, and reproducible. Micro-CT scanning, in contrast, is time-consuming, expensive and non-portable. This protocol can be applied to reconstruct the 3D shape of many other dry-sensitive objects such as shells of shellfish, cartilage, plants and other chitinous materials.</li> </ul>
Data from: Ellipsoid segmentation model for analyzing light-attenuated 3D confocal image stacks of fluorescent multi-cellular spheroids
In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.
3D ground truth annotations of cleared whole mouse brain nuclei imaged with a mesoSPIM system
<p>Please see Achard et al. 2024 for Data Card and other information.</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).
Figure 2 from: Mendez PK, Lee S, Venter CE (2018) Imaging natural history museum collections from the bottom up: 3D print technology facilitates imaging of fluid-stored arthropods with flatbed scanners. ZooKeys 795: 49-65. https://doi.org/10.3897/zookeys.795.28416
Figure 2 Fluid material scanning box: A dimensions of top-down and cross-section view of box plans, and finished box with glass affixed in B top and C bottom view.
Figure 3 from: Mendez PK, Lee S, Venter CE (2018) Imaging natural history museum collections from the bottom up: 3D print technology facilitates imaging of fluid-stored arthropods with flatbed scanners. ZooKeys 795: 49-65. https://doi.org/10.3897/zookeys.795.28416
Figure 3 Scanning process images: A scanning process with scan view setup, box covers, full scan, and cropped image B required fill levels of fluid for box covers to prevent bubbles and standoffs (left) to prevent an uneven scan (right) C six boxes set up on scanner; and D resulting full scan. Clear Plexiglas cube standoffs B and slip-joint rings D (lower-right) improve scans.
Figure 4 from: Mendez PK, Lee S, Venter CE (2018) Imaging natural history museum collections from the bottom up: 3D print technology facilitates imaging of fluid-stored arthropods with flatbed scanners. ZooKeys 795: 49-65. https://doi.org/10.3897/zookeys.795.28416
Figure 4 Cropped scan and scan resolution comparison: A final cropped scan of EMEC 37259, Psychoglyphaormiae (Ross, 1938) ♂, with standard layout of labels and specimens B–D comparison of scan resolution settings of 600 dpi, 1200 dpi, and 2400 dpi to show 100% scale display quality differences. Black scale bar is 5 mm for Rhyacophilaharmstoni Ross, 1944 ♂ (EMEC 41255, NV: White Pine Co.) in all images. Images are unmodified in software (e.g., no sharpening, white balance, or color correction).
Figure 1 from: Mendez PK, Lee S, Venter CE (2018) Imaging natural history museum collections from the bottom up: 3D print technology facilitates imaging of fluid-stored arthropods with flatbed scanners. ZooKeys 795: 49-65. https://doi.org/10.3897/zookeys.795.28416
Figure 1 Fluid-stored arthropods in A a museum jar with shell vials B shell vials in a jar rack C racks in storage shelves at the Essig Museum of Entomology. Other fluid-based storage approaches include D screw-top scintillation vials and stoppered vials. Individually capped vials are commonly stored in racks on shelves.
Figure 5 from: Mendez PK, Lee S, Venter CE (2018) Imaging natural history museum collections from the bottom up: 3D print technology facilitates imaging of fluid-stored arthropods with flatbed scanners. ZooKeys 795: 49-65. https://doi.org/10.3897/zookeys.795.28416
Figure 5 Example scans of different species and life stages of Essig Museum of Entomology Trichoptera showing detail of morphological features ADolophilodesnovusamericana (Ling, 1938) ♂, CA: Marin Co., EMEC 373433 BWormaldia sp. larvae, CA: Nevada Co., EMEC 1194742 CLimnephilusfrijole Ross, 1944 genitalic dissections of ♀♂, CA: Modoc Co., EMEC 373223 D larva and E case of Yphriacalifornica (Banks, 1907), CA: El Dorado Co., EMEC 373355 FLimnephilidae pupa, no location data, EMEC 373316 GPsychoglyphaormiae ♀ (Ross, 1938), CA: Nevada Co., EMEC 373259 HPsychoglypha sp. ♀, CA: Nevada Co., EMEC 373266 and IHesperophylaxdesignatus (Walker, 1852) case, CA: Mono Co., EMEC 373246. All scans are unmodified in software (no sharpening, white balance, or color correction). Scale bar: 5mm.
Mosaic and Non-mosaic Raw 3D TFM Images
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Test Dataset for 3D semantic image segmentation of the Liver and Tumor
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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.