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ShareScore release 0.9.0
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23 results for “Code Extraction”
The EMG source data, data processing code and feature extraction source code
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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>
Data and supplementary materials for the paper "DuplicatesExtractor: Extracting Code Duplicates As Soon As They Are Introduced in the IDE"
<p>This package presents all the necessary data for the paper "DuplicatesExtractor: Extracting Code Duplicates As Soon As They Are Introduced in the IDE".</p> <p>The package contains the following items:</p> <p>- The "source_code" directory contains the full source code of the plugin, along with its own README.<br> - The "DuplicatesExtractor-2021.2-1.0.zip" archive contains the pre-built version of the plugin. You can find the instructions on how to use it in the above-mentioned README in the "source_code" directory.<br> - The "supplementary.pdf" documents contains supplementary materials: the full list of the used metrics, the full list of the used projects, along with the list of the used models.<br> - The "demo.mp4" video contains the demonstration video for the tool.</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.