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4 results for “Body Part Regression”
Files from TCGA-KIRC Study for Body Part Regression Tutorial
<p>The data here are in whole based upon data generated by the TCGA Research Network: <a href="https://cancergenome.nih.gov/">http://cancergenome.nih.gov/</a>.</p> <p><br> The DICOM files from the <a href="https://wiki.cancerimagingarchive.net/display/Public/TCGA-KIRC#580038695f8cd691bda43dda71b4093c69c7318">TCGA-KIRC </a>study were converted to nifti files. Moreover, the nifti files with greater size than 35 MB and smaller size than 5 MB were removed (to reduce the size of the dataset and to remove the files with few slices). Furthermore, the metadata from the DICOM files is saved in a separate excel-file.</p>
Downsampling of CT-Lymph-Node Dataset for Body Part Regression Tutorial
<p>Down sampling of the<a href="https://wiki.cancerimagingarchive.net/display/Public/CT+Lymph+Nodes#19726546f04e74ab3631480694fcb72cac2e5477"> CT Lymph Node</a> dataset from the TCIA.<br> The files were down sampled to a pixel spacing of 7 mm/pixel. Through zero padding and cropping, all images are provided in the size of 64px x 64 px. Moreover, the HU values were clipped between -1000 HU and 1500 HU and rescaled to -1 and 1. To avoid aliasing effects, an additional Gaussian smoothing filter was applied before down sampling.</p> <p>This dataset was created for a Body Part Regression tutorial.</p>
Covid-19 CT dataset for Body Part Regression Tutorial
<p>The dataset is a subset of CT scans from the <a href="https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=70226443">Covid-19-AR</a> dataset from the Cancer Image Archive. The data were converted from the DICOM file format to the NifTI file format for better and easier handling. The converted dataset was created for a tutorial of the <a href="https://github.com/MIC-DKFZ/BodyPartRegression">bpreg</a> python package.</p> <p>Acknowledgment:<br> The dataset was funded with federal funds from the National Center for Advancing Translational Sciences UL1 TR003107 and the National Cancer Institute, Contract No. 75N91019D00024, Subcontract 20X023F. </p>
CT Images from the APOLLO-5-LSCC study for Body Part Regression Tutorial
<p>The dataset includes CT images from the <a href="https://wiki.cancerimagingarchive.net/display/Public/APOLLO-5-LSCC#95224279953c510266704797bf4c0bb2e8e7e04f">APOLLO-5-LSCC</a> study for a tutorial from the <a href="https://github.com/MIC-DKFZ/BodyPartRegression">Body Part Regression</a> python package. The CT images are saved in the npy-format. Moreover, an additional Excel file exists, which saves for each image the corresponding pixel spacings in x, y and z-direction.</p> <p>The original data was generated by the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Research Network, a Federal Precision Oncology and Cancer Moonshot Program of the Department of Defense, Department of Veterans Affairs, and National Cancer Institute.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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