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1,053 results for “Computed Tomography”
Fig. 1 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 1. Modified topology from Meredith et al. (2009) based on Bayesian analysis of five nuclear genes. Taxa for which I do not have nasal cavity data were pruned from the topology or if possible substituted for closely related species for which I do have nasal cavity data. Didelphis was used as a representative of Didelphinae; Dendrolagus was substituted for Aepyprymnus; Wallabia was substituted for Macropus; Sminthopsis was substituted for Phascolosorex. Substitutions within Marsupialia were based on the topologies by Cardillo et al. (2004). The outgroups were pruned from the topology of Meredith et al. (2009) and instead the following taxa for which I have nasal cavity data were included: Mus, Pteropus, Erinaceus, Ornithorhynchus, and Tachyglossus. The polytomy for the placental mammals reflects the uncertainty in higher level systematics for Placentalia, whereas the monotreme relationships are well established (e.g., Rowe et al., 2008).
Fig. 24 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 24. Coronal CT images showing the presence or absence of prominent lateral expanded bulges within the shaft of the ossified nasal septum (char. 31). (A) bulges present (char. 31.0), Dromiciops gliroides, C136 (FMNH 127463), scale bar equals 1 mm; (B) bulges absent (char. 31.1), Wallabia bicolor, C386 (TMM M-4169), scale bar equals 5 mm. Abbreviations: Ecto, ectoturbinal; Endo, endoturbinal; ONS, ossified nasal septum; SER, sphenethmoid recess.
Fig. 23 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 23. Digital renderings of the cribriform plate showing the presence or absence of a crista galli (char. 34). (A) crista galli is present (char. 34.0), Caluromys philander (AMNH 95526); (B) crista galli is absent (char. 34.1), Dendrolagus lumholtzi (AMNH 65254). Both scale bars equal 1 mm.
Fig. 13 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 13. Coronal CT images showing the morphology of the caudodorsal portion of caudal nasoturbinal (caudal to nasoturbinal division around endoturbinal I; char. 10). (A) caudodorsal portion is unfolded (ch. 10.0), Dromiciops gliroides, C245 (FMNH 127463), scale bar equals 1 mm; (B) caudodorsal portion curls (char. 10.1), Phalanger orientalis, C250 (AMNH 157211), scale bar equals 5 mm. Abbreviations: Ecto, ectoturbinal; Endo, endoturbinal; ONS, ossified nasal septum; SER, sphenethmoid recess.
Fig. 8. Schematic diagram showing a in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 8. Schematic diagram showing a dorsal view of the paries nasi of the chondrocranium of a marsupial. Rostral is to the left. Figure modeled after Smith and Rossie (2006: fig. 8.4). Abbreviations: EC, ectoturbinal; EN, endoturbinal.
Fig. 28 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 28. Coronal CT images showing the complexity of the rostral portion of the maxilloturbinal in marsupials (char. 1). (A) arborlike maxilloturbinal (char. 1.0), Dasyurus hallucatus, C208 (TMM M-6921); (B) simple maxilloturbinal (char. 1.1), Isoodon macrourus, C150 (TMM M-6922); (C) curled lamella (char. 1.1), Phascolarctos cinereus, C129 (TMM M-2946). All scale bars equal 5 mm. Abbreviations: Endo, endoturbinal; ONS, ossified nasal septum.
Fig. 16 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 16. Coronal CT images showing the caudalmost extent of ventral attachment of nasoturbinal (char. 13). (A) attachment is rostral to caudal terminus of maxilloturbinal (char. 13.0), Petauroides volans, C450 (AMNH 150055); (B) attachment is at coronal level of caudal terminus of maxilloturbinal (char. 13.1), Trichosurus vulpecula, C212 (TMM M-849); (C) attachment is caudal to caudal terminus of maxilloturbinal (char. 13.2), Isoodon macrourus, C374 (TMM M-6922). All scale bars equal 5 mm. Abbreviations: Ecto, ectoturbinal; Endo, endoturbinal; ONS, ossified nasal septum; PTL, posterior transverse lamina.
Fig. 12 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 12. Coronal CT images showing the morphology of the caudal nasoturbinal (char. 7). (A) caudal nasoturbinal is unbranched (char. 7.0), Dromiciops gliroides, C230 (FMNH 127463); (B) caudal nasoturbinal has at least one branch (char. 7.1), Caenolestes fuliginosus, C389 (KU 124015). Both scale bars equal 1 mm. Abbreviations: Ecto, ectoturbinal; Endo, endoturbinal; ONS, ossified nasal septum.
Fig. 27 in Comparative Morphology Of The Internal Nasal Skeleton Of Adult Marsupials Based On X-Ray Computed Tomography
Fig. 27. Coronal CT images showing the morphology of the maxillary recess (char. 26). (A) caudal portion of recess is medially enclosed by posterior transverse lamina (char. 26.0), Dasyurus hallucatus, C330 (TMM M-6921), scale bar equals 5 mm; (B) uncinate process of the caudal nasoturbinal also contributes to the medial wall of the recess (char. 26.1), Monodelphis domestica, C190 (TMM M-7599), scale bar equals 1 mm. Abbreviation: Ecto, ectoturbinal; Endo, endoturbinal; ONS, ossified nasal septum; NPM, nasopharyngeal meatus; PTL, posterior transverse lamina; SER, sphenethmoid recess.
3D Data from "New look at Concavicaris woodfordi (Euarthropoda: Pancrustacea?) using micro-computed tomography"
<p>It includes the tomograms (CT-scan), the segmentation project (Mimics) the 3D rendered data (STL) of the holotype of <em>Concavicaris woodfordi</em> (USNM PAL 112025).</p> <p><strong>Tomograms</strong>. The specimen was micro-CT scanned using the North Star Imaging µCT scanner housed at Vanderbilt University (Tennessee, USA). 1377 two-dimensional images were obtained with a voxel size of 46 µm at a voltage of 115 kV and current of 10 µA; the volume was reconstructed using EFX-CT (North Star Imaging, Minnesota, USA).</p> <p><strong>Segmentation. </strong>Rotation (178°), cropping and conversion to 8-bit were applied to every slice prior to segmentation. Manual and semi-automatic segmentation were done using Mimics 24.0 Research Edition (Materialise). The results of the segmentation were exported as STL files. 3D rendering and processing was done using Meshlab 2021.05 (GNU GPL 3.0)</p>
Phantom imaging data and analysis macros for the article "Monochromatic computed tomography using laboratory-scale setup"
<p>The raw and processed data and analysis macros of the article <em>A.-P.</em> <em>Honkanen et S. J. Huotari, Monochromatic computed tomography using laboratory-scale setup, Scientific Reports (2023), doi:<a href="http://doi.org/10.1038/s41598-023-27409-6">10.1038/s41598-023-27409-6</a></em></p> <p>The data set consists of the raw and reconstructed computed tomography projection data taken of an PMMA phantom embedded with three different chemical species of selenium taken with a monochromatic X-ray imaging setup based on a laboratory-scale Johann-type crystal X-ray spectrometer. In addition to the imaging data, the set contains also the Jupyter Notebooks used to process and analyse the data. The details of the instrument and the analysis are presented in the article.</p> <p>The dataset is licensed under Creative Commons Attribution 4.0 International License <a href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</a></p>
Computed tomography scan of Roman window glass from Ephesos
<p>Computed density scan of a window glass sample performed at Lucerne University of Applied Sciences and Arts (Luci, https://www.hslu.ch/luci). The glass fragment from Ephesos was provided by the Austrian Archaeological Institute (inventory ID EVH12/1017/1322), Vienna, Austria. The measurement covers an area of approx. 12 mm by 12 mm. The measured data is provided as a stacked Tag Image File Format (TIFF) image. A surface mesh that represents the boundary of the glass volume has been derived from the volumetric data and is included in this dataset in GL Transmission Format (gltf).</p>
SynthRAD2023 Grand Challenge validation dataset: synthetizing computed tomography for radiotherapy
<p><strong>Version 1.1</strong>, updated on 2023-06-04 --> the task2_val.zip has been modified with a new cbct file for patient 2BA078.<br> <br> The dataset can be downloaded from <a href="https://doi.org/10.5281/zenodo.7260705">https://doi.org/</a><a href="https://doi.org/10.5281/zenodo.7868169">10.5281/zenodo.7868169</a> and a detailed description is offered at <a href="https://doi.org/10.5281/zenodo.7260704">https://doi.org/10.5281/zenodo.7260704</a> in the "synthRAD2023_dataset_description.pdf".</p> <p>The<strong> </strong>input of the<strong> validation datasets</strong> for Task1 is in Task1_val.zip, while for Task2 in Task2_val.zip. After unzipping, each Task is organized according to the following folder structure:</p> <p>Task1_val.zip/</p> <p>├── Task1</p> <p> ├── brain</p> <p> ├── 1Bxxxx</p> <p> ├── mr.nii.gz</p> <p> └── mask.nii.gz</p> <p> ├── ...</p> <p>└── overview</p> <p> ├── 1_brain_val.xlsx</p> <p> ├── 1Bxxxx_val.png</p> <p> └── ... </p> <p> └── pelvis</p> <p> ├── 1Pxxxx</p> <p> ├── mr.nii.gz</p> <p> ├── mask.nii.gz</p> <p> ├── ...</p> <p>└── overview</p> <p> ├── 1_pelvis_val.xlsx</p> <p> ├── 1Pxxxx_val.png</p> <p> └── ....</p> <p>Task2_val.zip/</p> <p>├──Task2</p> <p> ├── brain</p> <p> ├── 2Bxxxx</p> <p> ├── cbct.nii.gz</p> <p> └── mask.nii.gz</p> <p> ├── ...</p> <p>└── overview</p> <p> ├── 2_brain_val.xlsx</p> <p> ├── 2Bxxxx_val.png</p> <p> └── ... </p> <p> └── pelvis</p> <p> ├── 2Pxxxx</p> <p> ├── cbct.nii.gz</p> <p> ├── mask.nii.gz</p> <p>├── ...</p> <p>└── overview</p> <p> ├── 2_pelvis_val.xlsx</p> <p> ├── 2Pxxxx_val.png</p> <p> └── ....</p> <p>Each patient folder has a unique name that contains information about the task, anatomy, center and a patient ID. The naming follows the convention below:</p> <p>[Task] [Anatomy] [Center] [PatientID]</p> <p>1 B A 001</p> <p>In each patient folder, two files can be found: </p> <ul> <li> <p>mr.nii.gz or cbct.nii.gz (depending on the task): CBCT/MR image</p> </li> <li> <p>mask.nii.gz: image containing a binary mask of the dilated patient outline </p> </li> </ul> <p>For each task and anatomy, an overview folder is provided which contains the following files:</p> <ul> <li> <p>[task]_[anatomy]_val.xlsx: This file contains information about the image acquisition protocol for each patient.</p> </li> <li> <p>[task][anatomy][center][PatientID]_val.png: For each patient a png showing axial, coronal and sagittal slices of CBCT/MR, CT, mask and the difference between CBCT/MR and CT is provided. These images are meant to provide a quick visual overview of the data.</p> </li> </ul> <p><strong>DATASET DESCRIPTION</strong></p> <p>This challenge dataset contains imaging data of patients who underwent radiotherapy in the brain or pelvis region. Overall, the population is predominantly adult and no gender restrictions were considered during data collection. For Task 1, the inclusion criteria were the acquisition of a CT and MRI during treatment planning while for task 2, acquisitions of a CT and CBCT, used for patient positioning, were required. Datasets for task 1 and 2 do not necessarily contain the same patients, given the different image acquisitions for the different tasks.</p> <p>Data was collected at 3 Dutch university medical centers:</p> <ul> <li> <p>Radboud University Medical Center;</p> </li> <li> <p>University Medical Center Utrecht;</p> </li> <li> <p>University Medical Center Groningen.</p> </li> </ul> <p>For anonymization purposes, from here on, institution names are substituted with A, B and C, without specifying which institute each letter refers to.</p> <p>The following number of patients is available in the validation set.</p> <p><strong>Validation</strong></p> <table> <tbody> <tr> <td> </td> <td> <p><strong>Brain</strong></p> </td> <td> <p><strong>Pelvis</strong></p> </td> </tr> <tr> <td> </td> <td> <p><strong>Center A</strong></p> </td> <td> <p><strong>Center B</strong></p> </td> <td> <p><strong>Center C</strong></p> </td> <td> <p><strong>Total</strong></p> </td> <td> <p><strong>Center A</strong></p> </td> <td> <p><strong>Center B</strong></p> </td> <td> <p><strong>Center C</strong></p> </td> <td> <p><strong>Tota</strong>l</p> </td> </tr> <tr> <td> <p><strong>Task 1</strong></p> </td> <td> <p>10</p> </td> <td> <p>10</p> </td> <td> <p>10</p> </td> <td> <p>30</p> </td> <td> <p>20</p> </td> <td> <p>0</p> </td> <td> <p>10</p> </td> <td> <p>30</p> </td> </tr> <tr> <td> <p><strong>Task 2</strong></p> </td> <td> <p>10</p> </td> <td> <p>10</p> </td> <td> <p>10</p> </td> <td> <p>30</p> </td> <td> <p>10</p> </td> <td> <p>10</p> </td> <td> <p>10</p> </td> <td> <p>30</p> </td> </tr> </tbody> </table> <p>In total, for all tasks and anatomies combined, 120 image pairs are available in this dataset. <strong>This repository only contains the validation data. </strong>The training data is provided at: h<a href="https://doi.org/10.5281/zenodo.7260704">ttps://doi.org/10.5281/zenodo.7260704</a>.</p> <p>All images were acquired with the clinically used scanners and imaging protocols of the respective centers and reflect typical images found in clinical routine. As a result, imaging protocols and scanner can vary between patients. A detailed description of the imaging protocol for each image, can be found in spreadsheets that are part of the dataset release (see dataset structure).</p> <p>Data was acquired with the following scanners:</p> <ul> <li> <p>Center A:</p> <ul> <li> <p>MRI: Philips Ingenia 1.5T/3.0T</p> </li> <li> <p>CT: Philips Brilliance Big Bore or Siemens Biograph20 PET-CT</p> </li> <li> <p>CBCT: Elekta XVI</p> </li> </ul> </li> <li> <p>Center B:</p> <ul> <li> <p>MRI: Siemens MAGNETOM Aera 1.5T or MAGNETOM Avanto_fit 1.5T</p> </li> <li> <p>CT: Siemens SOMATOM Definition AS</p> </li> <li> <p>CBCT: IBA Proteus+ or Elekta XVI</p> </li> </ul> </li> <li> <p>Center C:</p> <ul> <li> <p>MRI: Siemens Avanto fit 1.5T or Siemens MAGNETOM Vida fit 3.0T</p> </li> <li> <p>CT: Philips Brilliance Big Bore</p> </li> <li> <p>CBCT: Elekta XVI</p> </li> </ul> </li> </ul> <p>For task 1, MRIs were acquired with a T1-weighted gradient echo or an inversion prepared - turbo field echo (TFE) sequence and collected along with the corresponding planning CTs for all subjects. The exact acquisition parameters vary between patients and centers. For centers B and C, selected MRIs were acquired with Gadolinium contrast, while the selected MRIs of center A were acquired without contrast.</p> <p>For task 2, the CBCTs used for image-guided radiotherapy ensuring accurate patient position were selected for all subjects along with the corresponding planning CT.</p> <p>The following pre-processing steps were performed on the data:</p> <ul> <li> <p>Conversion from dicom to compressed nifti (nii.gz)</p> </li> <li> <p>Rigid registration between CT and MR/CBCT</p> </li> <li> <p>Anonymization (face removal, only for brain patients)</p> </li> <li> <p>Patient outline segmentation (provided as a binary mask)</p> </li> <li> <p>Crop MR/CBCT, CT and mask to remove background and reduce file sizes</p> </li> </ul> <p>The code used to preprocess the images can be found at: <a href="https://github.com/SynthRAD2023/">https://github.com/SynthRAD2023/</a>. Detailed information about the dataset are provided in SynthRAD2023_dataset_description.pdf published here along with the data and will also be submitted to Medical Physics.</p> <p><strong>ETHICAL APPROVAL</strong></p> <p>Each institution received ethical approval from their internal review board/Medical Ethical committee:</p> <ul> <li> <p>UMC Utrecht approved not-WMO on 4/03/2022 with number 22/474 entitled: “Synthetizing computed tomography for radiotherapy Grand Challenge (SynthRAD)”.</p> </li> <li> <p>UMC Groningen approved not-WMO on 20/07/2022 with number 202200310 entitled: “Synthesizing computed tomography for radiotherapy - Grand Challenge”.</p> </li> <li> <p>Radboud UMC declared the study not-WMO on 17/10/2022 with number 2022-15950 entitled “Synthetizing computed tomography for radiotherapy Grand Challenge”.</p> </li> </ul> <p><strong>CHALLENGE DESIGN</strong></p> <p>The overall challenge design can be found at <a href="https://doi.org/10.5281/zenodo.7746019">https://doi.org/10.5281/zenodo.7746019</a>.</p>
Dataset for "Computer vision assisted decomposition analysis of atom probe tomography data"
<p>Dataset for the article "Computer vision assisted decomposition analysis of atom probe tomography data". APT measurements were performed by Marcus Hans at Materials Chemistry (RWTH Aachen University) using a CAMECA LEAP 4000X HR. Training data was created by Janis A. Sälker.</p> <p>Content:</p> <p>- 13 (V,Al)N and 3 (Ti,Al)N APT reconstructions (.epos file format) and the corresponding range file (.rrng file format).</p> <p>- Training data (images & masks) for 9 labeled (V,Al)N APT samples (h5 file format). Image data with key "image" of shape (2, number_of_slices, 608, 192), where 2 corresponds to the V- and Al-contribution/channel and 608/192 to the height/width of the images. Masks/labels with key "label" of shape (number_of_slices, 608, 192)</p> <p> </p>
Data from: Stuck in the mud: experimental taphonomy and computed tomography demonstrate the critical role of sediment in stabilizing the three-dimensional external morphology of arthropod carcasses during early fossil diagenesis - DRAGONFLY sessions
Open the record for dataset details and reuse information.
Stuck in the mud: experimental taphonomy and computed tomography demonstrate the critical role of sediment in three-dimensional carcass stabilization during early fossil diagenesis - TIFF stack data
Open the record for dataset details and reuse information.
Data for: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation
<p>Collection of data files used in the paper titled: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation.</p> <p>Additional dataset which covers the noise study CT scans and digital volume correlation noise studies can be found in DOI: <a href="http://www.doi.org/10.5281/zenodo.3352268">10.5281/zenodo.3361832</a></p> <p><strong>Data contains the following:</strong></p> <ul> <li>X-ray CT data for the interrupted direct shear tests of a soil sample containing a Willow plant. The first file is the specimen scanned unloaded, followed by seven incremental shear load steps to 20 mm shear displacement. Files are 8-bit unsigned and 1800x1800x1600px. Voxel resolution is 0.04642 mm. <ol> <li><strong>20180430_HUTCH_1839_DJB_willow_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_A_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_B_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_D_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_E_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_F_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_G_8-bit_1800x1800x1600.raw</strong></li> </ol> </li> <li>Direct shear vs. displacement data is presented in an Excel spreadsheet: <ul> <li><strong>All_load_data_with_reducing_area.xlsx</strong></li> </ul> </li> <li>Normal and shear strain DVC data which has been averaged and plotted against specimen depth is presented in an Excel spreadsheet: <ul> <li><strong>Average_slice_vs_depth_data_all_samples_all_loads3.xlsx</strong></li> </ul> </li> <li>CT scan metadata giving information to the scan settings, voxel resolution, etc. is contained in a .zip file which consists of .xtekct and .XML files generated from the Nikon CT scanner. <ul> <li><strong>CT_Scan_Metadata.zip</strong></li> </ul> </li> <li>Drawings and Solidworks CAD files of the direct shear test rig are contained within the .zip file. There are a number of parts to the assembly. The file SSSB1003-5.SLDASM contains the complete assembly of the direct shear rig and will help identify the part names. The folder CAD_Drawings contains pdf documents of the part drawings. <ul> <li><strong>Direct_Shear_Drawings_Solidworks_Files.zip</strong></li> </ul> </li> <li>Tabulated DVC data taken at 32x32x32px subset size is contained inside a .zip file. These consist of tab separated .dat files from unloaded (data_1.dat) through incremental load steps Load A, Load B... Load G, (data_2.dat, data_3.dat... data_8.dat). The structure of the .dat file contains columns of data with each column number corresponding to the following: (1) x, (2) y (3) z, (4) vx, (5) vy, (6) vz, (7) exx, (8) eyy, (9) ezz, (10) exy, (11) exz, (12) eyz, (13) volumetric strain, (14) is valid. Columns 1-3 are subset positions in mm, 4-6 are displacements in mm, 7-9 are normal strains, 10-12 are shear strains, 13 is volumetric strain and 14 is a binary value indicating if the subset is valid. <ul> <li><strong>DVC_Load_Data_Willow_C.zip</strong></li> </ul> </li> <li>Tabulated DVC data applied to the load step CT data at 32, 48, 64, 96, 128 pixels is presented in the .zip files containing .dat tab separated files. The structure of the .dat files is described in the previous bullet point. These files were used to construct the noise study applied to incrementally loaded CT data by sampling regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>DVC_Noise_Study_Data_Load_Steps_Willow_C.zip</strong></li> </ul> </li> <li>Processed noise study data which compares the effects of DVC subset size is presented in the .xlsx file. This file contains both the controlled noise experiment data (stationary, magnification and rigid body motion) and noise study data applied to incrementally loaded data using sampled regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>Willow_C_Processed_Noise_study2.xlsx</strong></li> </ul> </li> <li>Tabulated data which compares the local x displacement vs depth profile from DVC and direct measurement of root position is contained in the following Excel spreadsheet file: <ul> <li><strong>X_Displacement_Root_and_DVC_Comparison_Willow C.xlsx</strong></li> </ul> </li> </ul>
Rapid divergent evolution of internal female genitalia and the coevolution of male genital morphology revealed by micro-computed tomography
<p>Animal genitalia are thought to evolve rapidly and divergently in response to sexual selection. Studies of genital evolution have focused largely on male genitalia, with our understanding of female genital evolution relatively limited. The paucity of work on female genital morphology is likely due to problems faced in quantifying shape variation, due to their composition and accessibility. Here we use a combination of micro-computed tomography, landmark-free shape quantification, and phylogenetic analysis to quantify the rate of female genital shape evolution among 29 species of Antichiropus millipedes, and the coevolution of male genitalia. We found significant variation in female and male genital shape among species. While male genital shape showed significant phylogenetic signal, female genital shape did not. Male genital shape was found to be evolving 1.2 times faster than female genital shape. Female and male genital shapes exhibited strongly correlated evolution, indicating that genital shape changes in one sex are associated with corresponding changes in the genital shape of the other sex. This study adds novel insight into our growing understanding of how female genitalia can evolve rapidly and divergently and highlights the advantages of three-dimensional techniques and multivariate analyses in studies of female genital evolution.</p>
Dataset for "Application of Generalized - Aurora Computed Tomography to the EISCAT_3D project"
<p>Dataset for "Application of Generalized - Aurora Computed Tomography to the EISCAT_3D project"</p>
The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study.
<p>Data used to perform statistical analysis in "The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study.". </p>
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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.