Dataset Open Access

PESO: Prostate Epithelium Segmentation on H&E-stained prostatectomy whole slide images

Bulten, Wouter; Bándi, Péter; Hoven, Jeffrey; Loo, Rob van de; Lotz, Johannes; Weiss, Nick; Laak, Jeroen van der; Ginneken, Bram van; Hulsbergen-van de Kaa, Christina; Litjens, Geert


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    "description": "<p>Large set of whole-slide-images (WSI) of prostatectomy specimens with various grades of prostate cancer (PCa). More information can be found in the corresponding paper:&nbsp;<a href=\"https://doi.org/10.1038/s41598-018-37257-4\">https://doi.org/10.1038/s41598-018-37257-4</a></p>\n\n<p>The WSIs in this dataset can be viewed using the open-source software <a href=\"https://github.com/computationalpathologygroup/ASAP\">ASAP</a>&nbsp;or <a href=\"https://openslide.org/\">Open Slide</a>.</p>\n\n<p>Due to the large size of the complete dataset, the data has been split up in to multiple archives.</p>\n\n<p>The data from the training set:</p>\n\n<ul>\n\t<li><strong>peso_training_masks.zip:&nbsp;</strong>Training masks (N=62)&nbsp;that have been used to train the main network of our paper. These masks are generated by a trained U-Net on the corresponding IHC slides.</li>\n\t<li><strong>peso_training_masks_corrected.zip:&nbsp;</strong>A subset of the color deconvolution masks (N=25)&nbsp;on which manual annotations have been made. Within these regions, stain and other artifacts have been removed.</li>\n\t<li><strong>peso_training_colordeconvolution.zip:&nbsp;</strong>Mask files (N=62)&nbsp;containing the P63&amp;CK8/18 channel&nbsp;of the color deconvolution operation. These masks mark all regions that are stained by either P63 or CK8/18 in the IHC version of the slides.</li>\n\t<li><strong>peso_training_wsi_{1-6}.zip:&nbsp;</strong>Zip files containing the whole slide images of the training set (N=62). Each archive contains 10 slides, excluding the last which contains 12.&nbsp;These images are exported at a pixel resolution of 0.48mu/pixels.&nbsp;</li>\n</ul>\n\n<p>The data from the test set:</p>\n\n<ul>\n\t<li><strong>peso_testset_regions.zip:&nbsp;</strong>Collection of annotation XML files with outlines of the test regions. These can be used to view the test regions in more detail using ASAP.</li>\n\t<li><strong>peso_testset_png.zip:&nbsp;</strong>Export of the test set regions in PNG format (2500x2500 pixels per region).</li>\n\t<li><strong>peso_testset_png_padded.zip:&nbsp;</strong>Export of the test regions in PNG format padded with a 500 pixel wide border (3500x3500 pixels per region). Useful for segmenting pixels at the border of the regions.</li>\n\t<li><strong>peso_testset_mapping.csv:&nbsp;</strong>A csv file mapping files from the test set (numbered 1-160) to regions in the xml files. The csv file also contains the label (benign or cancer) for each region.</li>\n\t<li><strong>peso_testset_wsi_{1-4}.zip:&nbsp;</strong>Zip files containing the whole slide images of the test set (N=40). Each archive contains 10 slides of the test set. These images are exported at a pixel resolution of 0.48mu/pixels.&nbsp;</li>\n</ul>\n\n<p>This study was financed by a grant from the Dutch Cancer Society (KWF), grant number KUN 2015-7970.</p>\n\n<p><strong>If you make use of this dataset please cite both the dataset itself and the corresponding paper:&nbsp;</strong><a href=\"https://doi.org/10.1038/s41598-018-37257-4\">https://doi.org/10.1038/s41598-018-37257-4</a></p>", 
    "license": {
      "id": "CC-BY-NC-SA-4.0"
    }, 
    "title": "PESO: Prostate Epithelium Segmentation on H&E-stained prostatectomy whole slide images", 
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    "references": [
      "https://doi.org/10.1038/s41598-018-37257-4"
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    "keywords": [
      "pathology", 
      "prostate", 
      "cancer", 
      "epithelium", 
      "whole slide image"
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    "publication_date": "2018-11-20", 
    "creators": [
      {
        "orcid": "0000-0002-6129-5039", 
        "affiliation": "Radboud University Medical Center", 
        "name": "Bulten, Wouter"
      }, 
      {
        "affiliation": "Radboud University Medical Center", 
        "name": "B\u00e1ndi, P\u00e9ter"
      }, 
      {
        "affiliation": "Radboud University Medical Center", 
        "name": "Hoven, Jeffrey"
      }, 
      {
        "affiliation": "Radboud University Medical Center", 
        "name": "Loo, Rob van de"
      }, 
      {
        "affiliation": "Fraunhofer MEVIS", 
        "name": "Lotz, Johannes"
      }, 
      {
        "affiliation": "Fraunhofer MEVIS", 
        "name": "Weiss, Nick"
      }, 
      {
        "affiliation": "Radboud University Medical Center", 
        "name": "Laak, Jeroen van der"
      }, 
      {
        "affiliation": "Radboud University Medical Center", 
        "name": "Ginneken, Bram van"
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      {
        "affiliation": "Radboud University Medical Center", 
        "name": "Hulsbergen-van de Kaa, Christina"
      }, 
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        "affiliation": "Radboud University Medical Center", 
        "name": "Litjens, Geert"
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