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27
datasets available to search
ShareScore release 0.9.0
Dataset results
27 results for “automatic segmentation”
Semi-automatic Segmentation Method for Determining 177Lu-DOTATATE Tumor Dosimetry
ClinicalTrials.gov study NCT06460467. IPD Sharing: Not stated. Countries: 1. Publications: 0.
REGISTRY on the Implementation of Artificial Intelligence in the Automatic Analysis of Vascular Network Segmentation
ClinicalTrials.gov study NCT06451315. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Automatic Segmentation Ultrasound-based Radiomics Technology in Diabetic Kidney Disease
ClinicalTrials.gov study NCT05025540. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Accuracy of 3D Slicer Software for Automatic Segmentation Versus Manual Segmentation Using Commercial Software to Evaluate Impacted and Unerupted Maxillary Canine: An Observational Study
ClinicalTrials.gov study NCT06972797. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Detection and Automatic Segmentation of Liver Nodules in Patients With Colorectal Adenocarcinoma
ClinicalTrials.gov study NCT04834596. IPD Sharing: NO. Countries: 1. Publications: 0.
Semi-automatic segmentation of optic radiations and LGN, and their relationship to EEG alpha waves
<p>Spreadsheet containing structural and functional data</p>
Dataset and code for "FK-means: Automatic Atrial Fibrosis Segmentation using Fractal-guided K-means Clustering with Voronoi-Clipping Feature Extraction of Anatomical Structures": FKmeans for fibrosis segmentation
<p>Assessment of left atrial (LA) fibrosis from late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) adds to the management of patients with atrial fibrillation (AF). However, accurate assessment of fibrosis in the LA wall remains challenging. Excluding anatomical structures in the LA proximity using clipping techniques can reduce misclassification of LA fibrosis. A novel FK-means approach for combined automatic clipping and automatic fibrosis segmentation was developed. This approach combines a feature-based Voronoi diagram with a hierarchical 3D K-means fractal-based method. The proposed automatic Voronoi clipping method was applied on LGE MRI data and achieved a Dice score of 0.75, similar as the score obtained by a deep learning method (3D UNet) for clipping (0.74). The automatic fibrosis segmentation method, which utilizes the Voronoi clipping method, achieved a Dice score of 0.76. This outperformed a 3D U-Net method for clipping and fibrosis classification, which had a Dice score of 0.69. Moreover, the proposed automatic fibrosis segmentation method achieved a Dice score of 0.90, using manual clipping of anatomical structures. The findings suggest that the automatic FK-means analysis approach enables reliable LA fibrosis segmentation and that clipping of anatomical structures in the atrial proximity can add to the assessment of atrial fibrosis. </p>
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.