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45 results for “segmentation methods”
Supplementary data to 'Coupling between cohesive element method and Node-to-segment contact algorithm : Implementation and application'
<p>This archive contains the data and the scripts for the simulations presented in the paper</p> <p>Pundir, M., Guillaume, A. "Coupling between cohesive element method and Node-to-segment contact algorithm : Implementation and application'" (2020)</p>
Preoperative and Intraoperative Sonographic Assessment of Lower Uterine Segment Thickness at Term in Women With Previous Cesarean Delivery - a Ultrasound Method Comparison Study
ClinicalTrials.gov study NCT02827604. IPD Sharing: NO. Countries: 1. Publications: 1.
Automated X-ray computer tomography segmentation method for finite element analysis of non-crimp fabrics reinforced composites
<p>Data behind the publications:</p> <p>Auenhammer, R.M., Mikkelsen, L.P., Asp, L., Blinzler, B. Automated X-ray computer tomography segmentation method for finite element analysis of non-crimp fabric reinforced composites. <em>Composite Structures, </em><strong>256</strong>, 113136, <a href="https://doi.org/10.1016/j.compstruct.2020.113136">https://doi.org/10.1016/j.compstruct.2020.113136</a>, 2021.</p> <p>Auenhammer, Robert M., Lars P. Mikkelsen, Leif E. Asp, Brina J. Blinzler, Dataset of non-crimp fabric reinforced composites for an X-ray computer tomography aided engineering process, <em>Data in Brief, </em><strong>33</strong>, 106518, <a href="https://doi.org/10.1016/j.dib.2020.106518">https://doi.org/10.1016/j.dib.2020.106518</a>, 2020.</p> <p>Auenhammer, R.M., L.P. Mikkelsen, L.E. Asp, B.J. Blinzler, X-ray tomography based numerical analysis of stress concentrations in non-crimp fabric reinforced composites - assessment of segmentation methods. <em>IOP Conf. Ser.: Mater. Sci. Eng.</em> <strong>942</strong>, 012038, <a href="https://doi.org/10.1088/1757-899X/942/1/012038">https://doi.org/10.1088/1757-899X/942/1/012038</a>, 2020</p> <p>The data-set contain data from three samples: A, E and G. </p> <p>For each sample the data are saved in the follow format</p> <ul> <li>X-ray scan: nii-files</li> <li>SEM scan: tif-files</li> <li>Abaqus files: inp-files </li> <li>X-ray setting: pdf-files</li> <li>SEM settings: hdr-ascii files</li> </ul> <p> </p>
Data from: Effects of different segmentation methods on geometric morphometric data collection from primate skulls
1. Increasing numbers of studies are analysing the shapes of objects using geometric morphometrics with tomographic data, which are often segmented and transformed to three-dimensional (3D) surface models before measurement. The present study aimed to evaluate the effects of different image segmentation methods on geometric morphometric data collection using computed tomography data collected from non-human primate skulls. 2. Three segmentation methods based on a visually-selected threshold, a half-maximum height protocol and a gradient and watershed algorithm were compared. For each method, the efficiency of surface reconstruction, the accuracy of landmark placement and the level of variation in shape and size compared with various levels of biological variation were evaluated. 3. The visual-based method inflated the surface in high-density anatomical regions, whereas the half-maximum height protocol resulted in large numbers of artificial holes and erosion. However, the gradient-based method overcame these issues and generated the most efficient surface model. The segmentation method used had a much smaller effect on shape and size variation than interspecific and inter-individual differences. However, this effect was statistically significant and not negligible when compared with intra-individual (fluctuating asymmetric) variation. 4. Although the gradient-based method is not widely used in geometric morphometric analyses, it may be one of the most appropriate options for reconstructing 3D surfaces. When evaluating small variations, such as fluctuating asymmetry, care should be taken around combining 3D data that were obtained using different segmentation methods.
movement in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
movement
mass properties in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
mass properties
Outputs from new methods for 3D+time image segmentation and tracking
<p>Segmentation and tracking of 3D+time images of artificially generates spheres. <br> The file named _20_frames_of_moving_spheres.avi is a 20-frame video of artificially generated spheres moving in time, the file <br> named _resulf_of_20_frames_of_moving_spheres.avi has the result of 4D segmentation, using our new segmentation methods, of the spheres (colored blue) moving in time, and the file _tracking_of_artificial_data_in_20_frames.mp4 has the tracking of these spheres. Additionally, the file named _one_moving_sphere.avi is also a 20-frame video of an artificially generated sphere moving in time, the file named _segmentation_result_one_moving_sphere.avi has the result of 4D segmentation of the sphere (colored blue) moving in time, and the file named _segmentation_result_one_moving_sphere_with_some_missing_spheres.avi has the result of 4D segmentation of the sphere (colored blue) moving in time when frames 5, 10, and 15 are missing in the file _one_moving_sphere.avi.</p>
Toward an Automated Method of Abdominal Fat Segmentation of MR Images
ClinicalTrials.gov study NCT01228968. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Airway segmentation and centerline extraction from thoracic CT – comparison of a new method to state of the art commercialized methods
Open the record for dataset details and reuse information.
Data from: Effects of different segmentation methods on geometric morphometric data collection from primate skulls
Open the record for dataset details and reuse information.
Data from: A novel mouse segmentation method based on dynamic contrast enhanced micro-CT images
Open the record for dataset details and reuse information.
Straightened segmentation in 4D cardiac CT: A practical method for multiparametric characterization of the landing zone for transcatheter pulmonary valve replacement
<p>Supplementary files (8 videos, 2 tables) for ''Straightened segmentation in 4D cardiac CT: A practical method for multiparametric characterization of the landing zone for transcatheter pulmonary valve replacement''</p>
Efficacy and Safety Comparison of the Open and Endovascular Surgical Methods for the Treatment of Long Atherosclerotic Lesions of the Femoral-popliteal Segment Below the Knee, TASC D in Patients With
ClinicalTrials.gov study NCT04583436. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Semi-automatic Segmentation Method for Determining 177Lu-DOTATATE Tumor Dosimetry
ClinicalTrials.gov study NCT06460467. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Efficacy and Safety Comparison of the Open Surgical and Endovascular Methods for the Treatment of Long Atherosclerotic Lesions of the Femoral-popliteal Segment Above the Knee, TASC II, Type D.
ClinicalTrials.gov study NCT04588571. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Semi-automated Segmentation Methods of SSTR PET for Dosimetry Prediction
ClinicalTrials.gov study NCT05537675. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Efficacy and Safety Comparison of the Endovascular and the Hybrid Methods for the Treatment of Prolonged Atherosclerotic Lesions of the Femoral-popliteal Segment Above the Knee, TASC II, Type D
ClinicalTrials.gov study NCT04590131. IPD Sharing: NO. Countries: 1. Publications: 0.
Fig. 7 in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
Fig. 7. The six cavities embedded in Tyrannosaurus Model 1's head, neck, and trunk segments, shown in right lateral (A) and dorsal (B) views. 'bc' indicates the buccal cavity; and 'pc' indicates the pharyngeal cavity.
Fig. 8 in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
Fig. 8. Six Tyrannosaurus models (in right lateral view) from our sensitivity analysis, representing the extreme high and low values obtained for mass, CM, and inertia. Shown: Model 1 (original 'skinny' model), Model 3 (largest torso), Model 7 (largest torso and legs), Model 21 (largest cavities), Model 27 (largest legs and cavities), and Model 30 ('best guess'). The right hip joint (pink circle; to left) and total body COM with respect to that point (red circle; to right) are indicated, with the x; y; z world axes (right hip joint) and the x; y; z principal axes for inertia calculations (COM) indicated by arrows.
Fig. 4 in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
Fig. 4. Ostrich trunk mass set models: (A) photograph of original trunk carcass in right lateral view, suspended on a cable for CM and inertia estimation experiments; (B) point cloud of carcass landmarks from digitization; (C) B-spline solid shrinkwrapped to fit underlying carcass landmarks (carcass model); (D) photograph of skeleton after defleshing of carcass, (E) point cloud of skeletal landmarks from digitization; (F) B-spline solid shrinkwrapped to fit underlying skeletal landmarks (skeleton model); and (G) Skeleton model with B-spline solid expanded laterally to simulate added flesh (fleshed-out model). Not to scale. The right hip joint (pink and black disk; caudal) and CM (red and black disk; cranial) are shown for the models, with principal axes (arrows). A dotted curve outlines the acetabulum in the carcass and skeleton pictures.
ScienceDex guides
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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.