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4 results for “Path segmentation”
Correcting for probe wandering by precession path segmentation
<p>Scanning precession electron diffraction datasets and processing scripts used in the journal publication "<strong>Correcting for probe wandering by precession path segmentation</strong>".</p> <p>DOI link to publication: <a href="http://doi.org/10.1016/j.ultramic.2023.113715">https://doi.org/10.1016/j.ultramic.2023.113715</a></p> <p> </p> <p><strong>Prerequisites</strong></p> <p>To run the scripts necessary to process the data, the open source packages JupyterLab and HyperSpy need to be installed. These notebooks were created with these package versions:</p> <ul> <li>hyperspy 1.6.4</li> <li>jupyterlab 3.2.0</li> </ul> <p> </p> <p><strong>Data files</strong></p> <p>There are three data types:</p> <ul> <li>Scanning precession electron diffraction (SPED) datasets contain the .hspy extension. There are two SPED datasets acquired by precession path segmentation, and one regular dataset: <ul> <li><em>SPED_256x256_22x22_10186nm_NBD_a5_spot1nm_CL20cm_125msExp_3000msFB_subframing_x8_pivotoff_01.hspy</em> is a precession path segmentation dataset presented in figure 2 in the article.</li> <li><em>SPED_zoom1_256x256_12x12_5556nm_NBD_a5_spot1nm_CL20cm_10msExp_3000msFB_subframing_x8.hspy</em> is a precession path segmentation dataset presented in figures 1 and 3 in the article.</li> <li><em>SPED_zoom1_256x256_12x12_5556nm_NBD_a5_spot1nm_CL20cm_10msExp_300msFB.hspy</em> is a regular SPED dataset of the same region as the dataset just above (also containing "zoom1" in its name).</li> </ul> </li> <li>A series of diffraction patterns with de-rocking switched off can be found in the <em>eight_segments.npy</em> file. This dataset was recorded by Dr. Tina Bergh at Department of Chemical Engineering, Norwegian University of Science and Technology, and is meant to be used as an illustration of the precession segments used in figure 1 in the article.</li> <li>Virtual bright field images of the precession path segmented scans, before and after rigid correction in SmartAlign, can be found with the .png extension. The files starting with "pivot01..." are images from the precession path segmentation scan with an intentional pivot point misalignment, while the files starting with "small..." are from the well aligned scan. The files ending with "_reg" are regular, i.e., non-corrected compound VBF images, while the files ending with "_cor" are SmartAlign rigidly corrected VBF images.</li> </ul> <p> </p> <p><strong>Processing scripts</strong></p> <p>There are two processing scripts:</p> <ul> <li><em>p01_slicing_segments.ipynb</em> is used to process the precession path segmentation datasets, from slicing of the raw data to constructing virtual bright field images.</li> <li><em>p02_image_processing.ipynb</em> is used to create the images found in the article and for image analysis. The latter includes blur quantification and measuring edge sharpness.</li> </ul> <p> </p>
An information theory framework for movement path segmentation and analysis
Open the record for dataset details and reuse information.
Deploying Near Optimal Delay Constrained Paths with Segment-Routing in Massive Scale Networks
<p>Dataset consisting of 5 large topologies used for the evaluation of Best2cop - multi-area version. <br> <br> The topologies themselves are written as a list of edges following the format : <br> <strong>source target delay cost area</strong> <br> "cost" being the IGP cost of the link, and "area", the IGP area to which the edge belongs.</p> <p>Each topology has a descriptive file showcasing some of the network's properties (density, diameter...) as well as an HTML file allowing to see the topology on an actual world map. Note that while we consider the road infrastructure, the links are represented in an abstract fashion for readability purposes.</p> <p> </p>
Whole genome tiling path array CGH analysis of segmental copy number alterations in cervical cancer cells
GEO Series GSE5049. Homo sapiens. 8 samples. Type: Genome variation profiling by genome tiling array.
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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.